Henrik I. Christensen

EDBT 2026 Demo / reviewers in the wild / expert

dblp:c/HIChristensen · also Henrik Iskov Christensen · DBLP profile ↗

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177ranked-venue papers

8as first author

15since 2021 · last 2025

0000-0002-7465-7502ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 160 · 7 first-author · 15 since 2021Systems, architecture and hardware · 107 · 10 since 2021Graphics, computer vision, multimedia, augmented reality and games · 22 · 3 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 18Applied, interdisciplinary, general and emerging computing · 17Databases, data management, data science and information retrieval · 2

Year	Publication	Venue	Position
2025	Planning for Tabletop Object Rearrangement abstract Finding an high-quality solution for the tabletop object rearrangement planning is a challenging problem. Compared to determining a goal arrangement [1], rearrangement planning is challenging due to the dependencies between objects and the buffer capacity available to hold objects. Although [3] has proposed an A* based searching strategy with lazy evaluation for the high-quality solution, it is not scalable, with the success rate decreasing as the number of objects increases. To overcome this limitation, we propose an enhanced A*-based algorithm that improves state representation and employs incremental goal attempts with lazy evaluation at each iteration. This approach aims to enhance scalability while maintaining solution quality. Our evaluation demonstrates that our algorithm can provide superior solutions compared to [3], in a shorter time, for both stationary and mobile robots. Jan Szczekulski, Sudhansh Peddabomma, Henrik I. Christensen	ICRA	4
2025	SMART: Advancing Scalable Map Priors for Driving Topology Reasoning abstract Topology reasoning is crucial for autonomous driving as it enables comprehensive understanding of connec-tivity and relationships between lanes and traffic elements. While recent approaches have shown success in perceiving driving topology using vehicle-mounted sensors, their scalability is hindered by the reliance on training data captured by consistent sensor configurations. We identify that the key factor in scalable lane perception and topology reasoning is the elimination of this sensor-dependent feature. To address this, we propose SMART, a scalable solution that leverages easily available standard-definition (SD) and satellite maps to learn a map prior model, supervised by large-scale geo-referenced high-definition (HD) maps independent of sensor settings. Attributed to scaled training, SMART alone achieves superior offline lane topology understanding using only SD and satellite inputs. Extensive experiments further demonstrate that SMART can be seamlessly integrated into any online topology reasoning methods, yielding significant improvements of up to 28% on the OpenLane-V2 benchmark. Project page: https://jay-ye.github.io/smart. Junjie Ye 0007, David Paz, Hengyuan Zhang 0001, Yuliang Guo, Xinyu Huang 0001, Henrik I. Christensen, Yue Wang 0041, Liu Ren 0001	ICRA	6
2025	Estimating Control Barriers from Offline Data abstract Learning-based methods for constructing control barrier functions (CBFs) are gaining popularity for ensuring safe robot control. A major limitation of existing methods is their reliance on extensive sampling over the state space or online system interaction in simulation. In this work we propose a novel framework for learning neural CBFs through a fixed, sparsely-labeled dataset collected prior to training. Our approach introduces new annotation techniques based on out-of-distribution analysis, enabling efficient knowledge propagation from the limited labeled data to the unlabeled data. We also eliminate the dependency on a high-performance expert controller, and allow multiple sub-optimal policies or even manual control during data collection. We evaluate the proposed method on real-world platforms. With limited amount of offline data, it achieves state-of-the-art performance for dynamic obstacle avoidance, demonstrating statistically safer and less conservative maneuvers compared to existing methods. Hongzhan Yu, Seth Farrell, Ryo Yoshimitsu, Zhizhen Qin, Henrik I. Christensen, Sicun Gao	ICRA	5
2025	SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs abstract High-definition maps (HD maps) are detailed and informative maps capturing lane centerlines and road elements. Although very useful for autonomous driving, HD maps are costly to build and maintain. Furthermore, access to these high-quality maps is usually limited to the firms that build them. On the other hand, standard definition (SD) maps provide road centerlines with an accuracy of a few meters. In this paper, we explore the possibility of enhancing SD maps by incorporating information from road manuals using LLMs. We develop SD++, an end-to-end pipeline to enhance SD maps with location-dependent road information obtained from a road manual. Our pipeline requires no sensor data input and only relies on road manuals and SD maps. We experiment several ways of using LLMs for map enhancement. Furthermore, we demonstrate the generalization ability of SD++ by showing results from six states in the United States and Japan. Code is available at https://github.com/AutonomousVehicleLaboratory/SDplusplus Hitvarth Diwanji, Jing-Yan Liao, Akshar Tumu, Henrik I. Christensen, Marcell Vazquez-Chanlatte, Chikao Tsuchiya	IV	4
2025	MapGS: Generalizable Pretraining and Data Augmentation for Online Mapping via Novel View Synthesis abstract Online mapping reduces the reliance of au-tonomous vehicles on high-definition (HD) maps, significantly enhancing scalability. However, recent advancements often overlook cross-sensor configuration generalization, leading to performance degradation when models are deployed on vehicles with different camera intrinsics and extrinsics. With the rapid evolution of novel view synthesis methods, we investigate the extent to which these techniques can be leveraged to address the sensor configuration generalization challenge. We propose a novel framework leveraging Gaussian splatting to reconstruct scenes and render camera images in target sensor configurations. The target config sensor data, along with labels mapped to the target config, are used to train online mapping models. Our proposed framework on the nuScenes and Ar-goverse 2 datasets demonstrates a performance improvement of 18 % through effective dataset augmentation, achieves faster convergence and efficient training, and exceeds state-of-the-art performance when using only 25 % of the original training data. This enables data reuse and reduces the need for laborious data labeling. Project page at https://henryzhangzhy.github.io/mapgs. Hengyuan Zhang 0001, David Paz, Yuliang Guo, Xinyu Huang 0001, Henrik I. Christensen, Liu Ren 0001	IV	5
2024	Robust Surgical Tool Tracking with Pixel-based Probabilities for Projected Geometric Primitives abstract Controlling robotic manipulators via visual feedback requires a known coordinate frame transformation between the robot and the camera. Uncertainties in mechanical systems as well as camera calibration create errors in this coordinate frame transformation. These errors result in poor localization of robotic manipulators and create a significant challenge for applications that rely on precise interactions between manipulators and the environment. In this work, we estimate the camera-to-base transform and joint angle measurement errors for surgical robotic tools using an image based insertion-shaft detection algorithm and probabilistic models. We apply our proposed approach in both a structured environment as well as an unstructured environment and measure to demonstrate the efficacy of our methods. Christopher D'Ambrosia, Florian Richter 0002, Zih-Yun Chiu, Nikhil Shinde, Fei Liu 0033, Henrik I. Christensen, Michael C. Yip	ICRA	6
2024	Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration abstract Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io. Abigail O'Neill, Abhiram Maddukuri, Abhishek Gupta 0004, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew E. Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu 0003, Charlotte Le, Chelsea Finn, Chen Wang 0053, Chenfeng Xu, Cheng Chi 0001, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Drieß, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia 0002, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su 0001, Haoshu Fang, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim 0001, Jaimyn Drake, Jan Peters 0001, Jan Schneider 0007, Jasmine Hsu, Jeannette Bohg, Jeffrey T. Bingham, Jensen Gao, Jiaheng Hu, Jiajun Wu 0001, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan 0001, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Kenneth Y. Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Zhang 0002, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Yunliang Chen 0001, Lerrel Pinto, Li Fei-Fei 0001, Liam Tan, Linxi Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang 0003, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma 0001, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen 0001, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Norman Di Palo, Nur Muhammad Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu 0010, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Rafael Rafailov, Ria Doshi, Roberto Martin Martin, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante-Gomez, Sean Kirmani, Sergey Levine, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair 0003, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wolfram Burgard, Xiaolong Wang 0004, Xinghao Zhu, Xinyang Geng, Liangwei Xu, Yecheng Jason Ma 0001, Yejin Kim 0003, Yevgen Chebotar, Yilin Wu 0003, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang 0001, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zichen Jeff Cui, Zichen Zhang 0016, Zipeng Lin	ICRA	79
2024	Enhancing Online Road Network Perception and Reasoning with Standard Definition Maps abstract Autonomous driving for urban and highway driving applications often requires High Definition (HD) maps to generate a navigation plan. Nevertheless, various challenges arise when generating and maintaining HD maps at scale. While recent online mapping methods have started to emerge, their performance especially for longer ranges is limited by heavy occlusion in dynamic environments. With these considerations in mind, our work focuses on leveraging lightweight and scalable priors–Standard Definition (SD) maps–in the development of online vectorized HD map representations. We first examine the integration of prototypical rasterized SD map representations into various online mapping architectures. Furthermore, to identify lightweight strategies, we extend the OpenLane-V2 dataset with OpenStreetMaps and evaluate the benefits of graphical SD map representations. A key finding from designing SD map integration components is that SD map encoders are model agnostic and can be quickly adapted to new architectures that utilize bird’s eye view (BEV) encoders. Our results show that making use of SD maps as priors for the online mapping task can significantly speed up convergence and boost the performance of the online centerline perception task by 30% (mAP). Furthermore, we show that the introduction of the SD maps leads to a reduction of the number of parameters in the perception and reasoning task by leveraging SD map graphs while improving the overall performance. Project Page: https://henryzhangzhy.github.io/sdhdmap/. Hengyuan Zhang 0001, David Paz, Yuliang Guo, Arun Das 0007, Xinyu Huang 0001, Karsten Haug, Henrik I. Christensen, Liu Ren 0001	IROS	7
2024	OSM vs HD Maps: Map Representations for Trajectory Prediction abstract High Definition (HD) Maps have long been favored for their precise depictions of static road elements. However, their accessibility constraints and vulnerability to rapid environmental changes impede the widespread deployment of highly map-reliant autonomous driving tasks, such as motion forecasting. In this context, we propose to leverage OpenStreetMap (OSM) as a promising alternative to HD Maps for long-term motion forecasting. The contributions of this work are threefold: firstly, we extend the application of OSM to long-horizon forecasting, doubling the forecasting horizon compared to previous studies. Secondly, through an expanded observation landscape and the integration of intersection priors, our OSM-based approach exhibits competitive performance, narrowing the gap with HD-map-based models. Lastly, we conduct an exhaustive context-aware analysis, providing deeper insights in motion forecasting across diverse scenarios as well as conducting class-aware comparisons. This research not only advances long-term motion forecasting with coarse map representations but additionally offers a scalable solution within the domain of autonomous driving. Jing-Yan Liao, Parth Doshi, David Paz, Henrik I. Christensen	IROS	5
2024	SemVecNet: Generalizable Vector Map Generation for Arbitrary Sensor Configurations abstract Vector maps are essential in autonomous driving for tasks like localization and planning, yet their creation and maintenance are notably costly. While recent advances in online vector map generation for autonomous vehicles are promising, current models lack adaptability to different sensor configurations. They tend to overfit to specific sensor poses, leading to decreased performance and higher retraining costs. This limitation hampers their practical use in real-world applications. In response to this challenge, we propose a modular pipeline for vector map generation with improved generalization to sensor configurations. The pipeline leverages probabilistic semantic mapping to generate a bird’s-eye-view (BEV) semantic map as an intermediate representation. This intermediate representation is then converted to a vector map using the MapTRv2 decoder. By adopting a BEV semantic map robust to different sensor configurations, our proposed approach significantly improves the generalization performance. We evaluate the model on datasets with sensor configurations not used during training. Our evaluation sets includes larger public datasets, and smaller scale private data collected on our platform. Our model generalizes significantly better than the state-of-the-art methods. The code will be available at https://github.com/AutonomousVehicleLaboratory/SemVecNet. Narayanan Elavathur Ranganatha, Hengyuan Zhang 0001, Shashank Venkatramani, Jing-Yan Liao, Henrik I. Christensen	IV	5
2023	FashionNTM: Multi-turn Fashion Image Retrieval via Cascaded Memory abstract Multi-turn textual feedback-based fashion image retrieval focuses on a real-world setting, where users can iteratively provide information to refine retrieval results until they find an item that fits all their requirements. In this work, we present a novel memory-based method, called FashionNTM, for such a multi-turn system. Our framework incorporates a new Cascaded Memory Neural Turing Machine (CM-NTM) approach for implicit state management, thereby learning to integrate information across all past turns to retrieve new images, for a given turn. Unlike vanilla Neural Turing Machine (NTM), our CM-NTM operates on multiple inputs, which interact with their respective memories via individual read and write heads, to learn complex relationships. Extensive evaluation results show that our proposed method outperforms the previous state-of-the-art algorithm by 50.5%, on Multi-turn FashionIQ [60] – the only existing multi-turn fashion dataset currently, in addition to having a relative improvement of 12.6% on Multi-turn Shoes – an extension of the singleturn Shoes dataset [5] that we created in this work. Further analysis of the model in a real-world interactive setting demonstrates two important capabilities of our model – memory retention across turns, and agnosticity to turn order for non-contradictory feedback. Finally, user study results show that images retrieved by FashionNTM were favored by 83.1% over other multi-turn models. Anwesan Pal, Sahil Wadhwa, Ayush Jaiswal, Rakesh Chada, Pradeep Natarajan, Henrik I. Christensen	ICCV	8
2023	Multi-Modal Planning on Regrasping for Stable Manipulation abstract Nowadays, a number of grasping algorithms [1], [2] have been proposed, that can predict a candidate of grasp poses, even for unseen objects. This enables a robotic manipulator to pick-and-place such objects. However, some of the predicted grasp poses to stably lift a target object may not be directly approachable due to workspace limitations. In such cases, the robot will need to re-grasp the desired object to enable successful grasping on it. This involves planning a sequence of continuous actions such as sliding, re-grasping, and transferring. To address this multi-modal problem, we propose a Markov-Decision Process-based multi-modal planner that can rearrange the object into a position suitable for stable manipulation. We demonstrate improved performance in both simulation and the real world for pick-and-place tasks. Zhao Tang, Henrik I. Christensen	IROS	3
2022	TridentNetV2: Lightweight Graphical Global Plan Representations for Dynamic Trajectory Generation abstract We present a framework for dynamic trajectory generation for autonomous navigation, which does not rely on HD maps as the underlying representation. High Definition (HD) maps have become a key component in most autonomous driving frameworks, which include complete road network information annotated at a centimeter-level that include traversable waypoints, lane information, and traffic signals. Instead, the presented approach models the distributions of feasible ego-centric trajectories in real-time given a nominal graph-based global plan and a lightweight scene representation. By embedding contextual information, such as crosswalks, stop signs, and traffic signals, our approach achieves low errors across multiple urban navigation datasets that include diverse intersection maneuvers, while maintaining real-time performance and reducing network complexity. Underlying datasets introduced are available online. David Paz, Hao Xiang 0001, Andrew Liang, Henrik I. Christensen	ICRA	4
2022	Place-and-Pick-Based Re-grasping Using Unstable Placement Akanimoh Adeleye, Henrik I. Christensen	ISRR	3
2021	Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications abstract Calibration of sensors is fundamental to robust performance for intelligent vehicles. In natural environments, disturbances can easily challenge calibration. One possibility is to use natural objects of known shape to recalibrate sensors. An approach based on recognition of traffic signs, such as stop signs, and use of them for recalibration of cameras is presented. The approach is based on detection, geometry estimation, calibration, and recursive updating. Results from natural environments are presented that clearly show convergence and improved performance. Yunhai Han, David Paz, Henrik I. Christensen	ICRA	4
2020	"Looking at the Right Stuff" - Guided Semantic-Gaze for Autonomous Driving abstract In recent years, predicting driver's focus of attention has been a very active area of research in the autonomous driving community. Unfortunately, existing state-of-the-art techniques achieve this by relying only on human gaze information, thereby ignoring scene semantics. We propose a novel Semantics Augmented GazE (SAGE) detection approach that captures driving specific contextual information, in addition to the raw gaze. Such a combined attention mechanism serves as a powerful tool to focus on the relevant regions in an image frame in order to make driving both safe and efficient. Using this, we design a complete saliency prediction framework - SAGE-Net, which modifies the initial prediction from SAGE by taking into account vital aspects such as distance to objects (depth), ego vehicle speed, and pedestrian crossing intent. Exhaustive experiments conducted through four popular saliency algorithms show that on 49/56 (87.5%) cases - considering both the overall dataset and crucial driving scenarios, SAGE outperforms existing techniques without any additional computational overhead during the training process. The augmented dataset along with the relevant code are available as part of the supplementary material. Anwesan Pal, Sayan Mondal, Henrik I. Christensen	CVPR	3
2020	Autonomous Vehicle Benchmarking using Unbiased Metrics abstract With the recent development of autonomous vehicle technology, there have been active efforts on the deployment of this technology at different scales that include urban and highway driving. While many of the prototypes showcased have been shown to operate under specific cases, little effort has been made to better understand their shortcomings and generalizability to new areas. Distance, uptime and number of manual disengagements performed during autonomous driving provide a high-level idea on the performance of an autonomous system but without proper data normalization, testing location information, and the number of vehicles involved in testing, the disengagement reports alone do not fully encompass system performance and robustness. Thus, in this study a complete set of metrics are applied for benchmarking autonomous vehicle systems in a variety of scenarios that can be extended for comparison with human drivers and other autonomous vehicle systems. These metrics have been used to benchmark UC San Diego's autonomous vehicle platforms during early deployments for micro-transit and autonomous mail delivery applications. David Paz, Po-Jung Lai, Nathan Chan, Yuqing Jiang, Henrik I. Christensen	IROS	5
2020	Probabilistic Semantic Mapping for Urban Autonomous Driving Applications abstract Recent advancements in statistical learning and computational abilities have enabled autonomous vehicle technology to develop at a much faster rate. While many of the architectures previously introduced are capable of operating under highly dynamic environments, many of these are constrained to smaller-scale deployments, require constant maintenance due to the associated scalability cost with highdefinition (HD) maps, and involve tedious manual labeling. As an attempt to tackle this problem, we propose to fuse image and pre-built point cloud map information to perform automatic and accurate labeling of static landmarks such as roads, sidewalks, crosswalks, and lanes. The method performs semantic segmentation on 2D images, associates the semantic labels with point cloud maps to accurately localize them in the world, and leverages the confusion matrix formulation to construct a probabilistic semantic map in bird’s eye view from semantic point clouds. Experiments from data collected in an urban environment show that this model is able to predict most road features and can be extended for automatically incorporating road features into HD maps with potential future work directions. David Paz, Hengyuan Zhang 0001, Qinru Li, Hao Xiang 0001, Henrik I. Christensen	IROS	5
2020	Multi-task Batch Reinforcement Learning with Metric Learning abstract We tackle the Multi-task Batch Reinforcement Learning problem. Given multiple datasets collected from different tasks, we train a multi-task policy to perform well in unseen tasks sampled from the same distribution. The task identities of the unseen tasks are not provided. To perform well, the policy must infer the task identity from collected transitions by modelling its dependency on states, actions and rewards. Because the different datasets may have state-action distributions with large divergence, the task inference module can learn to ignore the rewards and spuriously correlate \textit{only} state-action pairs to the task identity, leading to poor test time performance. To robustify task inference, we propose a novel application of the triplet loss. To mine hard negative examples, we relabel the transitions from the training tasks by approximating their reward functions. When we allow further training on the unseen tasks, using the trained policy as an initialization leads to significantly faster convergence compared to randomly initialized policies (up to 80% improvement and across 5 different Mujoco task distributions). We name our method \textbf{MBML} (\textbf{M}ulti-task \textbf{B}atch RL with \textbf{M}etric \textbf{L}earning). Minghua Liu, Kamil Ciosek, Henrik I. Christensen, Hao Su 0001	NeurIPS	6
2019	Coordinating multi-robot systems through environment partitioning for adaptive informative sampling abstract As robotic platforms have become more capable and autonomous, they have increasingly been utilized in time sensitive applications such as search and rescue. To that end, we have developed a system for teams of robots to efficiently explore an environment while taking sensor measurements. The system utilizes an information seeking algorithm that generates high priority points of interest based on the highest expected information gained per distance travelled. In order to coordinate multiple robots, the system partitions the area into different regions according to the effort needed to explore each region. Robots are assigned different regions to measure in order to minimize repetition of work and reduce interference between each robot.We present an information rate adaptive sampling approach for tasking robots within an environment to gather sensor measurements. We evaluated our approach within a simulation environment with one to four robots. Multiple robots are coordinated through our region segmentation approach. The data shows efficiency gains through the use of adaptive information gain rate tasking above a naïve closest point approach. We also see positive results from using the region segmentation technique. We further the experimentation by testing the algorithm on real world robots and verify the results in real world experimentation. Nicholas Fung, John G. Rogers III, Carlos Nieto, Henrik I. Christensen, Stephanie Kemna, Gaurav S. Sukhatme	ICRA	4
2019	Rorg: Service Robot Software Management with Linux Containers abstract Scaling up the software system on service robots increases the maintenance burden of developers and the risk of resource contention of the computer embedded on robots. As a result, developers spend much time on configuring, deploying, and monitoring the robot software system; robots may utilize significant computer resources when all software processes are running. We present Rorg, a Linux container-based scheme to manage, schedule, and monitor software components on service robots. Although Linux containers are already widely-used in cloud environments, this technique is challenging to efficiently adopt in service robot systems due to multi-tasking, resource constraints and performance requirements. To pave the way of Linux containers on service robots in an efficient manner, we present a programmable container management interface and a resource time-sharing mechanism incorporated with the Robot Operating System (ROS). Rorg allows developers to pack software into self-contained images and runs them in isolated environments using Linux containers; it also allows the robot to turn on and off software components on demand to avoid resource contention. We evaluate Rorg with a long-term autonomous tour guide robot: It manages 41 software components on the robot and relieved our maintenance burden, and it also reduces CPU load by 45.5% and memory usage by 16.5% on average. Shengye Wang, Xiao Liu 0033, Jishen Zhao, Henrik I. Christensen	ICRA	4
2019	DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments abstract In recent years, there has been a rapid increase in the number of service robots deployed for aiding people in their daily activities. Unfortunately, most of these robots require human input for training in order to do tasks in indoor environments. Successful domestic navigation often requires access to semantic information about the environment, which can be learned without human guidance. In this paper, we propose a set of DEDUCE1- Diverse scEne Detection methods in Unseen Challenging Environments algorithms which incorporate deep fusion models derived from scene recognition systems and object detectors. The five methods described here have been evaluated on several popular recent image datasets, as well as real-world videos acquired through multiple mobile platforms. The final results show an improvement over the existing state-of-the-art visual place recognition systems. Anwesan Pal, Carlos Nieto-Granda, Henrik I. Christensen	IROS	3
2019	A Taxonomy for Characterizing Modes of Interactions in Goal-driven, Human-robot Teams abstract As robots and other autonomous agents are increasingly incorporated into complex domains, characterizing interaction within heterogeneous teams that include both humans and machines becomes more necessary. Previous literature has addressed the task of characterizing human-robot interaction from different perspectives and in multiple contexts. However, the numerous factors behind interaction work in conjunction, and the insights gained from one perspective can inadvertently affect another, creating a need for unification of these taxonomies and frameworks within an overarching taxonomy that systematically defines these relationships. In this paper we review existing taxonomies related to human-robot interaction, the behavioral sciences, and social and algorithmic taxonomies, and propose an overarching ontology for the factors from these works. We identify three main components characterizing the structure of an interaction (environment, task, and team), and structure them over two levels: contextual factors and factors driven by local dynamics. Finally, we present an analysis of how these factors affect decisions about levels of robot automation and level of information abstraction in an interaction, and discuss curent gaps in the literature that can motivate future research. Priyam Parashar, Lindsay Sanneman, Julie A. Shah, Henrik I. Christensen	IROS	4
2018	Procedurally Provisioned Access Control for Robotic Systems abstract Security of robotics systems, as well as of the related middleware infrastructures, is a critical issue for industrial and domestic IoT, and it needs to be continuously assessed throughout the whole development lifecycle. The next generation open source robotic software stack, ROS2, is now targeting support for Secure DDS, providing the community with valuable tools for secure real world robotic deployments. In this work, we introduce a framework for procedural provisioning access control policies for robotic software, as well as for verifying the compliance of generated transport artifacts and decision point implementations. Ruffin White, Henrik I. Christensen, Gianluca Caiazza, Agostino Cortesi	IROS	2
2018	TritonBot: First Lessons Learned from Deployment of a Long-Term Autonomy Tour Guide Robot abstract Service robots perform flawless demos while their developers are keeping a close eye, but they often fail when working autonomously, especially in a long-term deployment. To study failure modes and human-robot interaction patterns in long-term deployments, we built TritonBot, a long-term autonomy robot working as a building receptionist and a tour guide. It recognizes people's face, talks to them, and guides people to the labs and facilities in an office building. This paper presents the design of TritonBot and the lessons we learned from the first-month deployment with respect to technical and human-robot interaction aspects. TritonBot and its variant BoxBot have worked for 108.7 hours, actively interacted with people for 22.1 hours, greeted people 2950 times, guided 150 tours, and traveled 9.9 kilometers. We share the components of TritonBot using an open licence to help the community to replicate the TritonBot platform and inspire long-term autonomy and human-robot interaction research. Shengye Wang, Henrik I. Christensen	RO-MAN	2
2017	Custom soft robotic gripper sensor skins for haptic object visualization abstract Robots are becoming increasingly prevalent in our society in forms where they are assisting or interacting with humans in a variety of environments, and thus they must have the ability to sense and detect objects by touch. An ongoing challenge for soft robots has been incorporating flexible sensors that can recognize complex motions and close the loop for tactile sensing. We present sensor skins that enable haptic object visualization when integrated on a soft robotic gripper that can twist an object. First, we investigate how the design of the actuator modules impact bend angle and motion. Each soft finger is molded using a silicone elastomer, and consists of three pneumatic chambers which can be inflated independently to achieve a range of complex motions. Three fingers are combined to form a soft robotic gripper. Then, we manufacture and attach modular, flexible sensory skins on each finger to measure deformation and contact. These sensor measurements are used in conjunction with an analytical model to construct 2D and 3D tactile object models. Our results are a step towards soft robot grippers capable of a complex range of motions and proprioception, which will help future robots better understand the environments with which they interact, and has the potential to increase physical safety in human-robot interaction. Please see the accompanying video for additional details. Benjamin Shih, Dylan Drotman, Caleb Christianson, Zhaoyuan Huo, Ruffin White, Henrik I. Christensen, Michael Thomas Tolley	IROS	6
2017	StuffNet: Using 'Stuff' to Improve Object Detection abstract We propose a Convolutional Neural Network (CNN) based algorithm - StuffNet - for object detection. In addition to the standard convolutional features trained for region proposal and object detection [33], StuffNet uses convolutional features trained for segmentation of objects and 'stuff' (amorphous categories such as ground and water). Through experiments on Pascal VOC 2010, we show the importance of features learnt from stuff segmentation for improving object detection performance. StuffNet improves performance from 18.8% mAP to 23.9% mAP for small objects. We also devise a method to train StuffNet on datasets that do not have stuff segmentation labels. Through experiments on Pascal VOC 2007 and 2012, we demonstrate the effectiveness of this method and show that StuffNet also significantly improves object detection performance on such datasets. Samarth Brahmbhatt, Henrik I. Christensen, James Hays	WACV	2
2016	Distributed trajectory estimation with privacy and communication constraints: A two-stage distributed Gauss-Seidel approach abstract We propose a distributed algorithm to estimate the 3D trajectories of multiple cooperative robots from relative pose measurements. Our approach leverages recent results [1] which show that the maximum likelihood trajectory is well approximated by a sequence of two quadratic subproblems. The main contribution of the present work is to show that these subproblems can be solved in a distributed manner, using the distributed Gauss-Seidel (DGS) algorithm. Our approach has several advantages. It requires minimal information exchange, which is beneficial in presence of communication and privacy constraints. It has an anytime flavor: after few iterations the trajectory estimates are already accurate, and they asymptotically convergence to the centralized estimate. The DGS approach scales well to large teams, and it has a straightforward implementation. We test the approach in simulations and field tests, demonstrating its advantages over related techniques. Siddharth Choudhary, Luca Carlone, Carlos Nieto-Granda, John G. Rogers III, Henrik I. Christensen, Frank Dellaert	ICRA	5
2016	Hierarchical rejection sampling for informed kinodynamic planning in high-dimensional spaces abstract We present hierarchical rejection sampling (HRS) to improve the efficiency of asymptotically optimal sampling-based planners for high-dimensional problems with differential constraints. Pruning nodes and rejecting samples that cannot improve the currently best solution have been shown to improve performance for certain problems. We show that in high-dimensional domains this improvement can be so large that rejecting samples becomes the bottleneck of the algorithm because almost all samples are rejected. This contradicts general wisdom that collision checking is always the bottleneck of sampling-based planners. Only samples in the informed subset of the state space can potentially improve the current solution. For systems without differential constraints the informed subset forms an ellipsoid, which can be parameterized and sampled directly. For systems with differential constraints the informed subset is more complicated and no such direct sampling methods exist. HRS improves the efficiency of finding samples within the informed subset without parameterizing it explicitly. Thus, it can also be applied to systems with differential constraints for which a steering method is available. In our experiments we demonstrate efficiency improvements of an RRT* planner of up to two orders of magnitude. Tobias Kunz, Andrea Thomaz, Henrik I. Christensen	ICRA	3
2016	Affordance-feasible planning with manipulator wrench spaces abstract This work introduces an affordance characterization employing mechanical wrenches as a metric for predicting and planning with workspace affordances. Although affordances are a commonly used high-level paradigm for robotic task-level planning and learning, the literature has been sparse regarding how to characterize the agent in this object-agent-environment framework. In this work, we propose decomposing a behavior into a vocabulary of characteristic requirements and capabilities that are suitable to predict the affordances of various parts of the workspace. Specifically, we investigate mechanical wrenches as a viable representation of these affordance requirements and capabilities. We then use this vocabulary in a planning system to compose complex motions from simple behavior types in continuous space. The utility of the framework for complex planning is demonstrated on example scenarios both in simulation and with real-world industrial manipulators. Stephen Balakirsky, Aaron F. Bobick, Henrik I. Christensen	ICRA	4
2016	An assembly sequence generation of a product family for robot programming abstract In this paper, we present an efficient assembly sequence generation method for robot programming, which can reduce the complexity of assembly sequence generation for products within a product family. Today, principle markets for robot assembly automation (e.g., automobile and consumer electronics) have a relatively short product run rate, ranging from six to twelve months. To accommodate this rapidly changing production demand, in most cases, manufacturers design a series of new products within a product family (i.e., a group of products derived from a common product platform) so that they have similar assembly sequences. Seemingly robot programming for a new product within a product family does not require extensive programming adjustments, but it is still complex and manufacturers spend large amount time and money in programming robots for each new product. To solve this problem, we present a new assembly sequence generation method. With a case-based planner, we generate feasible and similar-to-real assembly sequence candidates for a new product from assembly sequences of old products within a product family. Then, we use geometric information extracted from its CAD model to evaluate those candidate sequences. Unlike those used by previous studies, our method can generate an assembly sequence that is more suitable for the concept of a reconfigurable assembly system for general-purpose robots (assembly sequence generation for robot programming); more similar to assembly sequences used in real assembly systems (case-based planning); and more properly evaluated for robot assembly (a CAD model). We apply the proposed method to a toy airplane assembly scenario and demonstrate its feasibility. Kimoon Lee, Sungmoon Joo, Henrik I. Christensen	IROS	3
2016	Active planning based extrinsic calibration of exteroceptive sensors in unknown environments abstract Existing Simultaneous Localization and Mapping systems require an extensive manual pre-calibration process. Non-manual calibration procedures use manipulators to create known patterns in order to estimate the unknown calibration. Calibration is often time-consuming and involves humans performing repetitive tasks such as aligning a known calibration target at different poses with respect to the sensor. We propose an algorithm that plans a trajectory which actively reduces the uncertainty of the robot's calibration given a rough initial calibration estimate. Calibration is performed autonomously in a previously unknown environment by maintaining the belief over landmarks, poses, and the calibration parameters. We present experimental results to demonstrate the approach's ability to autonomously calibrate the exteroceptive sensor in simulated and real environments. We show that even a greedy approach can reduce the effort needed to perform calibration every time the robot is reconfigured for autonomous tasks and mitigates the possibility of human error added into the calibration. Varun Murali, Carlos Nieto-Granda, Siddharth Choudhary, Henrik I. Christensen	IROS	4
2016	Navigation Among Movable Obstacles with learned dynamic constraints abstract In this paper we present the first planner for the problem of Navigation Among Movable Obstacles (NAMO) on a real robot that can handle environments with under-specified object dynamics. This result makes use of recent progress from two threads of the Reinforcement Learning literature. The first is a hierarchical Markov-Decision Process formulation of the NAMO problem designed to handle dynamics uncertainty. The second is a physics-based Reinforcement Learning framework which offers a way to ground this uncertainty in a compact model space that can be efficiently updated from data received by the robot online. Our results demonstrate the ability of a robot to adapt to unexpected object behavior in a real office scenario. Jonathan Scholz, Nehchal Jindal, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen	IROS	5
2016	Anticipatory robot path planning in human environments abstract Robot path planning in human environments benefits significantly from considering more than obstacle avoidance, and recent works in this area proposed safety and comfort considerations. One shortcoming of current approaches is that humans' behavior is modeled as independent of robot's motions. In this work, we aim to give this anticipation ability to a robot by simulating people's reaction to robot's motion during planning. Our approach is based on extracting a static plan using A* search on the grid map by minimizing safety, disturbance and path length costs and then refining it by simulating humans' reaction using the Social Force Model. With two example scenarios in simulation and two on the real system, we provide qualitative examination of the resulting robot paths and demonstrate that robots can exhibit social behaviors that is not possible to model with standard approaches. This work serves as a primer for quantitative user studies, and we hope will urge future robot path planners to consider a richer set of social capabilities. Akansel Cosgun, Akin Sisbot, Henrik I. Christensen	RO-MAN	3
2015	Occlusion-Aware Object Localization, Segmentation and Pose Estimation abstract We present a learning approach for localization and segmentation of objects in an image in a manner that is robust to partial occlusion. Our algorithm produces a bounding box around the full extent of the object and labels pixels in the interior that belong to the object. Like existing segmentation aware detection approaches, we learn an appearance model of the object and consider regions that do not fit this model as potential occlusions. However, in addition to the established use of pairwise potentials for encouraging local consistency, we use higher order potentials which capture information at the level of im- age segments. We also propose an efficient loss function that targets both localization and segmentation performance. Our algorithm achieves 13.52% segmentation error and 0.81 area under the false-positive per image vs. recall curve on average over the challenging CMU Kitchen Occlusion Dataset. This is a 42.44% decrease in segmentation error and a 16.13% increase in localization performance compared to the state-of-the-art. Finally, we show that the visibility labelling produced by our algorithm can make full 3D pose estimation from a single image robust to occlusion. Samarth Brahmbhatt, Heni Ben Amor, Henrik I. Christensen	BMVC	3
2015	Information-based reduced landmark SLAM abstract In this paper, we present an information-based approach to select a reduced number of landmarks and poses for a robot to localize itself and simultaneously build an accurate map. We develop an information theoretic algorithm to efficiently reduce the number of landmarks and poses in a SLAM estimate without compromising the accuracy of the estimated trajectory. We also propose an incremental version of the reduction algorithm which can be used in SLAM framework resulting in information based reduced landmark SLAM. The results of reduced landmark based SLAM algorithm are shown on Victoria park dataset and a Synthetic dataset and are compared with standard graph SLAM (SAM [6]) algorithm. We demonstrate a reduction of 40-50% in the number of landmarks and around 55% in the number of poses with minimal estimation error as compared to standard SLAM algorithm. Siddharth Choudhary, Vadim Indelman, Henrik I. Christensen, Frank Dellaert	ICRA	3
2015	Exploiting symmetries and extrusions for grasping household objects abstract In this paper we present an approach for creating complete shape representations from a single depth image for robot grasping. We introduce algorithms for completing partial point clouds based on the analysis of symmetry and extrusion patterns in observed shapes. Identified patterns are used to generate a complete mesh of the object, which is, in turn, used for grasp planning. The approach allows robots to predict the shape of objects and include invisible regions into the grasp planning step. We show that the identification of shape patterns, such as extrusions, can be used for fast generation and optimization of grasps. Finally, we present experiments performed with our humanoid robot executing pick-up tasks based on single depth images and discuss the applications and shortcomings of our approach. Ana C. Huamán Quispe, Benoit Milville, Can Erdogan, Mike Stilman, Henrik I. Christensen, Heni Ben Amor	ICRA	6
2015	Learning non-holonomic object models for mobile manipulation abstract For a mobile manipulator to interact with large everyday objects, such as office tables, it is often important to have dynamic models of these objects. However, as it is infeasible to provide the robot with models for every possible object it may encounter, it is desirable that the robot can identify common object models autonomously. Existing methods for addressing this challenge are limited by being either purely kinematic, or inefficient due to a lack of physical structure. In this paper, we present a physics-based method for estimating the dynamics of common non-holonomic objects using a mobile manipulator, and demonstrate its efficiency compared to existing approaches. Jonathan Scholz, Martin Levihn, Charles L. Isbell Jr., Henrik I. Christensen, Mike Stilman	ICRA	4
2015	Exactly sparse memory efficient SLAM using the multi-block alternating direction method of multipliers abstract Large-scale SLAM demands for scalable techniques in which the computational burden and the memory consumption is shared among many processing units. While recent literature offers competitive approaches for scalable mapping, these usually involve approximations to preserve sparsity of the resulting subproblems. We present an approach to scalable SLAM that is exactly sparse. The main insight is that rather than eliminating variables (which induces dense cliques), we split the separators connecting subgraphs. Then, we enforce consistency of the separators in different subgraphs using hard constraints. The resulting constrained optimization problem can be solved in a decentralized manner using the multi-block Alternating Direction Method of Multipliers (ADMM). Our framework is appealing since (i) it preserves the sparsity structure of the original problem, (ii) it has a straightforward implementation, (iii) it allows to easily trade-off between computation time and accuracy. While our approach is currently slower than competitors, it is more accurate than other memory efficient alternatives. Moreover, we believe that the proposed framework can be of interest on its own as it draws connections with recent literature on decentralized optimization. Siddharth Choudhary, Luca Carlone, Henrik I. Christensen, Frank Dellaert	IROS	3
2015	A Taxonomy of Benchmark Tasks for Robot Manipulation Ana C. Huamán Quispe, Heni Ben Amor, Henrik I. Christensen	ISRR (1)	3
2015	Semantic Instance Labeling Leveraging Hierarchical Segmentation abstract Most of the approaches for indoor RGBD semantic labeling focus on using pixels or super pixels to train a classifier. In this paper, we implement a higher level segmentation using a hierarchy of super pixels to obtain a better segmentation for training our classifier. By focusing on meaningful segments that conform more directly to objects, regardless of size, we train a random forest of decision trees as a classifier using simple features such as the 3D size, LAB color histogram, width, height, and shape as specified by a histogram of surface normal's. We test our method on the NYU V2 depth dataset, a challenging dataset of cluttered indoor environments. Our experiments using the NYU V2 depth dataset show that our method achieves state of the art results on both a general semantic labeling introduced by the dataset (floor, structure, furniture, and objects) and a more object specific semantic labeling. We show that training a classifier on a segmentation from a hierarchy of super pixels yields better results than training directly on super pixels, patches, or pixels as in previous work. Steven Hickson, Irfan A. Essa, Henrik I. Christensen	WACV	3
2014	GASP: Geometric Association with Surface Patches abstract A fundamental challenge to sensory processing tasks in perception and robotics is the problem of obtaining data associations across views. We present a robust solution for ascertaining potentially dense surface patch (super pixel) associations, requiring just range information. Our approach involves decomposition of a view into regularized surface patches. We represent them as sequences expressing geometry invariantly over their super pixel neighborhoods. Uniquely consistent partial orderings are utilized for the same. We match these representations robustly through an optimal sequence comparison metric based on the Damerau-Levenshtein distance. The approach is able to perform under wide baselines, heavy rotations, significant occlusions and partially overlapping content. The technique does not require any priors -- motion or otherwise, and does not make restrictive assumptions on scene structure and sensor movement. It does not require appearance -- is hence more widely applicable than appearance reliant methods, and invulnerable to related ambiguities such as texture less or aliased content. We present promising qualitative and quantitative results under diverse settings, along with comparatives with popular approaches based on range as well as RGB-D data. Rahul Sawhney, Fuxin Li, Henrik I. Christensen	3DV	3
2014	Anisotropic Agglomerative Adaptive Mean-Shift Rahul Sawhney, Henrik I. Christensen, Gary R. Bradski	BMVC	2
2014	Efficient Hierarchical Graph-Based Segmentation of RGBD Videos abstract We present an efficient and scalable algorithm for segmenting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based approach. Our algorithm processes a moving window over several point clouds to group similar regions over a graph, resulting in an initial over-segmentation. These regions are then merged to yield a dendrogram using agglomerative clustering via a minimum spanning tree algorithm. Bipartite graph matching at a given level of the hierarchical tree yields the final segmentation of the point clouds by maintaining region identities over arbitrarily long periods of time. We show that a multistage segmentation with depth then color yields better results than a linear combination of depth and color. Due to its incremental processing, our algorithm can process videos of any length and in a streaming pipeline. The algorithm's ability to produce robust, efficient segmentation is demonstrated with numerous experimental results on challenging sequences from our own as well as public RGBD data sets. Steven Hickson, Stanley T. Birchfield, Irfan A. Essa, Henrik I. Christensen	CVPR	4
2014	Guidance for human navigation using a vibro-tactile belt interface and robot-like motion planning abstract Guidance for human navigation using a vibro-tactile belt interface and robot-like motion planning Akansel Cosgun, Akin Sisbot, Henrik I. Christensen	ICRA	3
2014	Trust modeling in multi-robot patrolling abstract On typical multi-robot teams, there is an implicit assumption that robots can be trusted to effectively perform assigned tasks. The multi-robot patrolling task is an example of a domain that is particularly sensitive to reliability and performance of robots. Yet reliable performance of team members may not always be a valid assumption even within homogeneous teams. For instance, a robot's performance may deteriorate over time or a robot may not estimate tasks correctly. Robots that can identify poorly performing team members as performance deteriorates, can dynamically adjust the task assignment strategy. This paper investigates the use of an observation based trust model for detecting unreliable robot team members. Robots can reason over this model to perform dynamic task reassignment to trusted team members. Experiments were performed in simulation and using a team of indoor robots in a patrolling task to demonstrate both centralized and decentralized approaches to task reassignment. The results clearly demonstrate that the use of a trust model can improve performance in the multi-robot patrolling task. Charles Pippin, Henrik I. Christensen	ICRA	2
2014	OmniMapper: A modular multimodal mapping framework abstract Simultaneous Localization and Mapping (SLAM) is not a problem with a one-size-fits-all solution. The literature includes a variety of SLAM approaches targeted at different environments, platforms, sensors, CPU budgets, and applications. We propose OmniMapper, a modular multimodal framework and toolbox for solving SLAM problems. The system can be used to generate pose graphs, do feature-based SLAM, and also includes tools for semantic mapping. Multiple measurement types from different sensors can be combined for multimodal mapping. It is open with standard interfaces to allow easy integration of new sensors and feature types. We present a detailed description of the mapping approach, as well as a software framework that implements this, and present detailed descriptions of its applications to several domains including mapping with a service robot in an indoor environment, large-scale mapping on a PackBot, and mapping with a handheld RGBD camera. Alexander J. B. Trevor, John G. Rogers III, Henrik I. Christensen	ICRA	3
2014	SLAM with object discovery, modeling and mapping abstract Object discovery and modeling have been widely studied in the computer vision and robotics communities. SLAM approaches that make use of objects and higher level features have also recently been proposed. Using higher level features provides several benefits: these can be more discriminative, which helps data association, and can serve to inform service robotic tasks that require higher level information, such as object models and poses. We propose an approach for online object discovery and object modeling, and extend a SLAM system to utilize these discovered and modeled objects as landmarks to help localize the robot in an online manner. Such landmarks are particularly useful for detecting loop closures in larger maps. In addition to the map, our system outputs a database of detected object models for use in future SLAM or service robotic tasks. Experimental results are presented to demonstrate the approach's ability to detect and model objects, as well as to improve SLAM results by detecting loop closures. Siddharth Choudhary, Alexander J. B. Trevor, Henrik I. Christensen, Frank Dellaert	IROS	3
2014	Finding optimal routes for multi-robot patrolling in generic graphs abstract Multi-robot patrolling is a problem that has important applications in security and surveillance. However, the optimal task assignment is known to be NP-hard. We consider evenly spacing the robots in a cyclic Traveling Salesman Problem (TSP) tour or partitioning the graph of the environment. The trade-off in performance, overall team travel cost and coordination is analyzed in this paper. We provide both a theoretical analysis and simulation results across multiple environments. The results demonstrate that generally cyclic-based strategies are superior, especially when small teams are used but at the expense of greater team cost, whereas partitioning strategies are especially suitable for larger teams and unbalanced graph topologies. The reported results show that graph topology and team size are fundamental to determine the best choice for a patrol strategy. David Portugal, Charles Pippin, Rui P. Rocha, Henrik I. Christensen	IROS	4
2013	Interactive object modeling & labeling for service robots Alexander J. B. Trevor, John G. Rogers III, Akansel Cosgun, Henrik I. Christensen	HRI	4
2013	Autonomous person following for telepresence robots abstract We present a method for a mobile robot to follow a person autonomously where there is an interaction between the robot and human during following. The planner takes into account the predicted trajectory of the human and searches future trajectories of the robot for the path with the highest utility. Contrary to traditional motion planning, instead of determining goal points close to the person, we introduce a task dependent goal function which provides a map of desirable areas for the robot to be at, with respect to the person. The planning framework is flexible and allows encoding of different social situations with the help of the goal function. We implemented our approach on a telepresence robot and conducted a controlled user study to evaluate the experiences of the users on the remote end of the telepresence robot. The user study compares manual teleoperation to our autonomous method for following a person while having a conversation. By designing a behavior specific to a flat screen telepresence robot, we show that the person following behavior is perceived as safe and socially acceptable by remote users. All 10 participants preferred our autonomous following method over manual teleoperation. Akansel Cosgun, Dinei A. F. Florêncio, Henrik I. Christensen	ICRA	3
2013	Robot planning with a semantic map abstract Context is an important factor for domestic service robots to consider when interpreting their environments to perform tasks. In people's homes, rooms are laid out in a specific arrangement to enable comfortable and efficient living; for example, the living room is central to the house, and the dining room is adjacent to the kitchen. The identity of the objects in a room are a strong cue for determining that room's purpose. This paper will present a planner for an autonomous mobile robot system which uses room connectivity topology and object understanding as context for an object search task in a domestic environment. John G. Rogers III, Henrik I. Christensen	ICRA	2
2013	RGB-D object tracking: A particle filter approach on GPU abstract This paper presents a particle filtering approach for 6-DOF object pose tracking using an RGB-D camera. Our particle filter is massively parallelized in a modern GPU so that it exhibits real-time performance even with several thousand particles. Given an a priori 3D mesh model, the proposed approach renders the object model onto texture buffers in the GPU, and the rendered results are directly used by our parallelized likelihood evaluation. Both photometric (colors) and geometric (3D points and surface normals) features are employed to determine the likelihood of each particle with respect to a given RGB-D scene. Our approach is compared with a tracker in the PCL both quantitatively and qualitatively in synthetic and real RGB-D sequences, respectively. Changhyun Choi, Henrik I. Christensen	IROS	2
2013	RGB-D edge detection and edge-based registration abstract We present a 3D edge detection approach for RGB-D point clouds and its application in point cloud registration. Our approach detects several types of edges, and makes use of both 3D shape information and photometric texture information. Edges are categorized as occluding edges, occluded edges, boundary edges, high-curvature edges, and RGB edges. We exploit the organized structure of the RGB-D image to efficiently detect edges, enabling near real-time performance. We present two applications of these edge features: edge-based pair-wise registration and a pose-graph SLAM approach based on this registration, which we compare to state-of-the-art methods. Experimental results demonstrate the performance of edge detection and edge-based registration both quantitatively and qualitatively. Changhyun Choi, Alexander J. B. Trevor, Henrik I. Christensen	IROS	3
2013	Planning with a task modeling framework in manufacturing robotics abstract In this paper we present the idea that by using AI planning in concert with formal task modeling, the overhead associated with plan creation for complex tasks can be reduced. The proposed approach uses a SysML taxonomy to model the system capabilities and the process specification, and the PDDL planning language to determine acceptable objective solutions. This idea is applied to the manufacturing domain, and examples are shown modeling a multi-robot system in an automobile manufacturing environment. A discussion is given regarding the merits of the demonstrated approach. Jacob Huckaby, Stavros Vassos, Henrik I. Christensen	IROS	3
2012	Performance based monitoring using statistical control charts on multi-robot teams Charles Pippin, Henrik I. Christensen	FUSION	2
2012	A conditional random field model for place and object classification abstract Place categorization and object recognition are competencies needed by robots to perform a variety of service tasks in the home, such as fetch-and-carry, retrieval, cleaning, meal preparation, and companionship. Context is a powerful cue for place categorization and object recognition; rooms are laid out in a specific fashion to enable comfortable and efficient living, and objects are used within rooms for tasks specific to that room. This paper will present a technique which leverages contextual cues for joint reasoning about object and room classification via a conditional random field model. John G. Rogers III, Henrik I. Christensen	ICRA	2
2012	Planar surface SLAM with 3D and 2D sensors abstract We present an extension to our feature based mapping technique that allows for the use of planar surfaces such as walls, tables, counters, or other planar surfaces as landmarks in our mapper. These planar surfaces are measured both in 3D point clouds, as well as 2D laser scans. These sensing modalities compliment each other well, as they differ significantly in their measurable fields of view and maximum ranges. We present experiments to evaluate the contributions of each type of sensor. Alexander J. B. Trevor, John G. Rogers III, Henrik I. Christensen	ICRA	3
2012	3D pose estimation of daily objects using an RGB-D camera abstract In this paper, we present an object pose estimation algorithm exploiting both depth and color information. While many approaches assume that a target region is cleanly segmented from background, our approach does not rely on that assumption, and thus it can estimate pose of a target object in heavy clutter. Recently, an oriented point pair feature was introduced as a low dimensional description of object surfaces. The feature has been employed in a voting scheme to find a set of possible 3D rigid transformations between object model and test scene features. While several approaches using the pair features require an accurate 3D CAD model as training data, our approach only relies on several scanned views of a target object, and hence it is straightforward to learn new objects. In addition, we argue that exploiting color information significantly enhances the performance of the voting process in terms of both time and accuracy. To exploit the color information, we define a color point pair feature, which is employed in a voting scheme for more effective pose estimation. We show extensive quantitative results of comparative experiments between our approach and a state-of-the-art. Changhyun Choi, Henrik I. Christensen	IROS	2
2012	3D textureless object detection and tracking: An edge-based approach abstract This paper presents an approach to textureless object detection and tracking of the 3D pose. Our detection and tracking schemes are coherently integrated in a particle filtering framework on the special Euclidean group, SE(3), in which the visual tracking problem is tackled by maintaining multiple hypotheses of the object pose. For textureless object detection, an efficient chamfer matching is employed so that a set of coarse pose hypotheses is estimated from the matching between 2D edge templates of an object and a query image. Particles are then initialized from the coarse pose hypotheses by randomly drawing based on costs of the matching. To ensure the initialized particles are at or close to the global optimum, an annealing process is performed after the initialization. While a standard edge-based tracking is employed after the annealed initialization, we employ a refinement process to establish improved correspondences between projected edge points from the object model and edge points from an input image. Comparative results for several image sequences with clutter are shown to validate the effectiveness of our approach. Changhyun Choi, Henrik I. Christensen	IROS	2
2012	Finding graph topologies for feasible multirobot motion planning abstract In this paper we present a design methodology for mapping the configuration space of multirobot systems in a warehouse. The method generates a tree topology with robot and terminal nodes. In the most general case multirobot motion planning problems are NP-complete. But, we show that pebble motion problems in the resultant tree topology are always feasible. Our method uses an integer programming formulation to find such a solution. Pushkar Kolhe, Henrik I. Christensen	IROS	2
2011	HRI: the real world abstract This year's conference focuses on human-robot interaction in the real world. The panel discussion presents the view from those who are "living it": industry leaders who are relying on current robotic technology to accomplish their work right now. Who better to provide the most compelling information on issues/challenges that are influencing their use? This panel gathers experts from business and industry to discuss their experiences in using robotic technology in their field. Topics include the financial, organizational, and practical challenges faced by professionals using robotic technology in the workplace, and factors influencing the acceptance of robots at work. The implications for design of robotic products and systems are also discussed. The session is a must for professionals and academic researchers interested in solving problems related to using robots in real world settings. Jennifer L. Burke, Henrik I. Christensen, Roland Menassa, Ralf Koeppe, Joe Dyer, Mario E. Munich	HRI	2
2011	Robust 3D visual tracking using particle filtering on the SE(3) group abstract In this paper, we present a 3D model-based object tracking approach using edge and keypoint features in a particle filtering framework. Edge points provide 1D information for pose estimation and it is natural to consider multiple hypotheses. Recently, particle filtering based approaches have been proposed to integrate multiple hypotheses and have shown good performance, but most of the work has made an assumption that an initial pose is given. To remove this assumption, we employ keypoint features for initialization of the filter. Given 2D-3D keypoint correspondences, we choose a set of minimum correspondences to calculate a set of possible pose hypotheses. Based on the inlier ratio of correspondences, the set of poses are drawn to initialize particles. For better performance, we employ an autoregressive state dynamics and apply it to a coordinate-invariant particle filter on the SE(3) group. Based on the number of effective particles calculated during tracking, the proposed system re-initializes particles when the tracked object goes out of sight or is occluded. The robustness and accuracy of our approach is demonstrated via comparative experiments. Changhyun Choi, Henrik I. Christensen	ICRA	2
2011	Simultaneous localization and mapping with learned object recognition and semantic data association abstract Complex and structured landmarks like objects have many advantages over low-level image features for semantic mapping. Low level features such as image corners suffer from occlusion boundaries, ambiguous data association, imaging artifacts, and viewpoint dependance. Artificial landmarks are an unsatisfactory alternative because they must be placed in the environment solely for the robot's benefit. Human environments contain many objects which can serve as suitable landmarks for robot navigation such as signs, objects, and furniture. Maps based on high level features which are identified by a learned classifier could better inform tasks such as semantic mapping and mobile manipulation. In this paper we present a technique for recognizing door signs using a learned classifier as one example of this approach, and demonstrate their use in a graphical SLAM framework with data association provided by reasoning about the semantic meaning of the sign. John G. Rogers III, Alexander J. B. Trevor, Carlos Nieto-Granda, Henrik I. Christensen	IROS	4
2011	Enhancing the robot service experience through social media abstract The development of effective robot servers has been an intensely studied research area for many years. Their operation in a dynamic environment presents multiple challenges in navigation, recognition, human-robot interaction, and manipulation. This paper addresses the challenges presented by recognition and human-robot interaction by utilizing Twitter and Facebook to potentially mitigate some of the long known issues in these areas. Specifically, we will address the problems of reliable human-robot communications and efficiency of service delivery. An online scenario study is administered to participants to evaluate the performance of a social media enabled robot as compared to a traditional speech synthesis and recognition enabled robot. The potential for the robot to learn and build long-term relationships through access to these social mediums is also discussed as a future work. Victor Emeli, Henrik I. Christensen	RO-MAN	2
2010	Real-time 3D model-based tracking using edge and keypoint features for robotic manipulation abstract We propose a combined approach for 3D real-time object recognition and tracking, which is directly applicable to robotic manipulation. We use keypoints features for the initial pose estimation. This pose estimate serves as an initial estimate for edge-based tracking. The combination of these two complementary methods provides an efficient and robust tracking solution. The main contributions of this paper includes: 1) While most of the RAPiD style tracking methods have used simplified CAD models or at least manually well designed models, our system can handle any form of polygon mesh model. To achieve the generality of object shapes, salient edges are automatically identified during an offline stage. Dull edges usually invisible in images are maintained as well for the cases when they constitute the object boundaries. 2) Our system provides a fully automatic recognition and tracking solution, unlike most of the previous edge-based tracking that require a manual pose initialization scheme. Since the edge-based tracking sometimes drift because of edge ambiguity, the proposed system monitors the tracking results and occasionally re-initialize when the tracking results are inconsistent. Experimental results demonstrate our system's efficiency as well as robustness. Changhyun Choi, Henrik I. Christensen	ICRA	2
2010	Applying domain knowledge to SLAM using virtual measurements abstract Simultaneous Localization and Mapping (SLAM) aims to estimate the maximum likelihood map and robot pose based on a robot's control and sensor measurements. In structured environments, such as human environments, we might have additional domain knowledge that could be applied to produce higher quality mapping results. We present a method for using virtual measurements, which are measurements between two features in our map. To demonstrate this, we present a system that uses such virtual measurements to relate visually detected points to walls detected with a laser scanner. Alexander J. B. Trevor, John G. Rogers III, Carlos Nieto-Granda, Henrik I. Christensen	ICRA	4
2010	Semantic map partitioning in indoor environments using regional analysis abstract Classification of spatial regions based on semantic information in an indoor environment enables robot tasks such as navigation or mobile manipulation to be spatially aware. The availability of contextual information can significantly simplify operation of a mobile platform. We present methods for automated recognition and classification of spaces into separate semantic regions and use of such information for generation of a topological map of an environment. The association of semantic labels with spatial regions is based on Human Augmented Mapping. The methods presented in this paper are evaluated both in simulation and on real data acquired from an office environment. Carlos Nieto-Granda, John G. Rogers III, Alexander J. B. Trevor, Henrik I. Christensen	IROS	4
2010	SLAM with Expectation Maximization for moveable object tracking abstract The goal of simultaneous localization and mapping (SLAM) is to compute the posterior distribution over landmark poses. Typically, this is made possible through the static world assumption - the landmarks remain in the same location throughout the mapping procedure. Some prior work has addressed this assumption by splitting maps into static and dynamic sets, or by recognizing moving landmarks and tracking them. In contrast to previous work, we apply an Expectation Maximization technique to a graph based SLAM approach and allow landmarks to be dynamic. The batch nature of this operation enables us to detect moveable landmarks and factor them out of the map. We demonstrate the performance of this algorithm with a series of experiments with moveable landmarks in a structured environment. John G. Rogers III, Alexander J. B. Trevor, Carlos Nieto-Granda, Henrik I. Christensen	IROS	4
2010	Computational visual attention systems and their cognitive foundations: A survey abstract Based on concepts of the human visual system, computational visual attention systems aim to detect regions of interest in images. Psychologists, neurobiologists, and computer scientists have investigated visual attention thoroughly during the last decades and profited considerably from each other. However, the interdisciplinarity of the topic holds not only benefits but also difficulties: Concepts of other fields are usually hard to access due to differences in vocabulary and lack of knowledge of the relevant literature. This article aims to bridge this gap and bring together concepts and ideas from the different research areas. It provides an extensive survey of the grounding psychological and biological research on visual attention as well as the current state of the art of computational systems. Furthermore, it presents a broad range of applications of computational attention systems in fields like computer vision, cognitive systems, and mobile robotics. We conclude with a discussion on the limitations and open questions in the field. Simone Frintrop, Erich Rome, Henrik I. Christensen	ACM Trans. Appl. Percept.	3
2010	Detecting Region Transitions for Human-Augmented Mapping abstract In this paper, we describe a concise method for the feature-based representation ofregionsin an indoor environment and show how it can also be applied for door-passage-independent detection of transitions betweenregionsto improve communication with a human user. Elin Anna Topp, Henrik I. Christensen	IEEE Trans. Robotics	2
2009	"Pimp My Roomba": designing for personalization abstract We present a study of how householders personalize their domestic vacuuming robot, iRobot's Roomba". In particular, we build on Blom and Monk's [3] theory of personalization that argues that personalization does not only occur naturally but can also be induced by design choices. In this study, we created a personalization toolkit, which allowed people to customize their Roomba's appearance and distributed it to 15 households. Our observations of these households provide empirical support that personalization can facilitate positive experiences with a Roomba, and having materials to hand can increase the odds of customization. We conclude by discussing design implications for personalization. Ja-Young Sung, Rebecca E. Grinter, Henrik I. Christensen	CHI	3
2009	Robots in the wild: understanding long-term use abstract It has long been recognized that novelty effects exist in the interaction with technologies. Despite this recognition, we still know little about the novelty effects associated with domestic robotic appliances and more importantly, what occurs after the novelty wears off. To address this gap, we undertook a longitudinal field study with 30 households to which we gave Roomba vacuuming robots and then observed use over six months. During this study, which spans over 149 home visits, we encountered methodological challenges in understanding households' usage patterns. In this paper we report on our longitudinal research, focusing particularly on the methods that we used 1) to understand human-robot interaction over time despite the constraints of privacy and temporality in the home, and 2) to uncover information when routines became less conscious to the participants themselves. Ja-Young Sung, Henrik I. Christensen, Rebecca E. Grinter	HRI	2
2009	Control of mobile manipulator using the dynamical systems approach abstract The combination of a mobile platform and a manipulator, known as a mobile manipulator, provides a highly flexible system, which can be used in a wide range of applications, especially within the field of service robotics. One of the challenges with mobile manipulators is the construction of control systems, enabling the robot to operate safely in potentially dynamic environments. In this paper we will present work in which a mobile manipulator is controlled using the dynamical systems approach. The method presented is a two level approach in which competitive dynamics are used both for the overall coordination of the mobile platform and the manipulator as well as the lower level fusion of obstacle avoidance and target acquisition behaviors. Lars-Peter Ellekilde, Henrik I. Christensen	ICRA	2
2009	Adaptive triangular mesh generation of self-configuring robot swarms abstract We address the problem of dispersing a large number of autonomous mobile robots toward building wireless ad hoc sensor networks performing environmental monitoring and control. For the purpose, we propose the adaptive triangular mesh generation algorithm that enables robots to generate triangular meshes of various sizes adapting to changing environmental conditions. A locally interacting, geometric technique allows robots to generate each triangular mesh with their two neighbor robots. Specifically, we have assumed that robots are not allowed to have the identifier, any pre-determined leaders or common coordinate systems, and any explicit communication. Under such minimal conditions, the positions of the robots were shown to converge to the desired distribution, which was mathematically proven and also verified through extensive simulations. Our preliminary results indicate that the proposed algorithm can be applied to the problem regarding the coverage of an area of interest by a swarm of mobile sensors. Geunho Lee 0001, Nak Young Chong, Henrik I. Christensen	ICRA	3
2009	Adding diagnostics to intelligent robot systems abstract Robot systems are increasing in complexity. Trying to diagnose a robot that is non-functional or exhibiting suboptimal performance can be a major challenge. A framework for plug-n-play addition of diagnostics to modules in an object oriented software framework is presented. The methods for modeling of system modules, their transition to a Bayesian model and final implementation are described. The methodology is exemplified for a mobile manipulation system and experimental results are presented. Sneha Chandrababu, Henrik I. Christensen	IROS	2
2009	Cognitive vision for efficient scene processing and object categorization in highly cluttered environments abstract One of the key competencies required in modern robots is finding objects in complex environments. For the last decade, significant progress in computer vision and machine learning literatures has increased the recognition performance of well localized objects. However, the performance of these techniques is still far from human performance, especially in cluttered environments. We believe that the performance gap between robots and humans is due in part to humans' use of an attention system. According to cognitive psychology, the human visual system uses two stages of visual processing to interpret visual input. The first stage is a pre-attentive process perceiving scenes fast and coarsely to select potentially interesting regions. The second stage is a more complex process analyzing the regions hypothesized in the previous stage. These two stages play an important role in enabling efficient use of the limited cognitive resources available. Inspired by this biological fact, we propose a visual attentional object categorization approach for robots that enables object recognition in real environments under a critical time limitation. We quantitatively evaluate the performance for recognition of objects in highly cluttered scenes without significant loss of detection rates across several experimental settings. Changhyun Choi, Henrik I. Christensen	IROS	2
2009	Self-configuring robot swarms with dual rotating infrared sensors abstract This paper presents practical design and hardware implementation issues of self-configuring swarms of autonomous mobile robots. For the purpose, we develop a new low-cost position detection system that we call dual rotating infrared (DRIr) sensor. The DRIr sensor can provide robots with advanced sensing capabilities that give reliable information about the position and surface geometry of neighboring robots and obstacles. Special focus is placed on how to realize the observation and object identification of mobile robots through the use of DRIr sensors. We verify the functionality and performance of the DRIr sensors mounted on a commercial mobile robot. Experimental results show that a swarm of mobile robots equipped with the DRIr sensors can autonomously configure themselves into an area. Geunho Lee 0001, Seokhoon Yoon, Nak Young Chong, Henrik I. Christensen	IROS	4
2009	Normalized graph cuts for visual SLAM abstract Simultaneous Localization and Mapping (SLAM) suffers from a quadratic space and time complexity per update step. Recent advancements have been made in approximating the posterior by forcing the information matrix to remain sparse as well as exact techniques for generating the posterior in the full SLAM solution to both the trajectory and the map. Current approximate techniques for maintaining an online estimate of the map for a robot to use while exploring make capacity-based decisions about when to split into sub-maps. This paper will describe an alternative partitioning strategy for online approximate real-time SLAM which makes use of normalized graph cuts to remove less information from the full map. John G. Rogers III, Henrik I. Christensen	IROS	2
2009	Wiimote robot control using human motion models abstract As mass-market video game controllers have become more advanced, there has been a recent increase in interest for using these as intuitive and inexpensive control devices. In this paper we examine position control for a robot using a wiimote game controller. We show that human motion models can be used to achieve better precision than traditional tracking approaches, sufficient for simpler tasks. We also present an experiment that shows that very intuitive control can be achieved, as novice subjects can control a robot arm through simple tasks after just a few minutes of practice and minimal instructions. Christian Smith, Henrik I. Christensen	IROS	2
2009	A minimum jerk predictor for teleoperation with variable time delay abstract In this paper we describe a method for bridging internet time delays in a teleoperation scenario. In the scenario, the sizes of the time delays is not only stochastic, but it is also large compared to the task execution time. The method proposed uses minimum jerk motion models to predict the input from the user a time into the future that is equivalent to the one-way communication delay. We present results from a teleoperated ball-catching experiment with real internet delays, where we show that the proposed method makes a significant improvement over traditional methods for teleoperation over intercontinental distances. Christian Smith, Henrik I. Christensen	IROS	2
2009	Visual Place Categorization: Problem, dataset, and algorithm abstract In this paper we describe the problem of visual place categorization (VPC) for mobile robotics, which involves predicting the semantic category of a place from image measurements acquired from an autonomous platform. For example, a robot in an unfamiliar home environment should be able to recognize the functionality of the rooms it visits, such as kitchen, living room, etc. We describe an approach to VPC based on sequential processing of images acquired with a conventional video camera. We identify two key challenges: Dealing with non-characteristic views and integrating restricted-FOV imagery into a holistic prediction. We present a solution to VPC based upon a recently-developed visual feature known as CENTRIST (census transform histogram). We describe a new dataset for VPC which we have recently collected and are making publicly available. We believe this is the first significant, realistic dataset for the VPC problem. It contains the interiors of six different homes with ground truth labels. We use this dataset to validate our solution approach, achieving promising results. Jianxin Wu 0001, Henrik I. Christensen, James M. Rehg	IROS	2
2009	Adaptive CPG based coordinated control of healthy and robotic lower limb movements abstract This paper proposes an adaptive CPG based controller for a lower limb prosthesis consisting of online trajectory generation and interlimb coordination. The adaptive CPG can produce multidimensional rhythmic patterns and modulate their frequency by tuning relevant parameters in an autonomously way adapting to a changing periodicity of external signals. Also, to increase the stability of the prosthesis, a spring-damper component is attached between the hip and ankle joints, allowing the absorption of impulsive ground reaction forces at landing. We verify the validity of the proposed controller with a simulated humanoid robot through the investigation of the self-coordination between the healthy and robotic legs. Jae-Kwan Ryu, Nak Young Chong, Bum-Jae You, Henrik I. Christensen	RO-MAN	4
2009	Sketching the future: Assessing user needs for domestic robots abstract In this paper, we discuss a user-centered vision of future domestic robots based on 48 householders' depiction of their ideal home robots. Through users' creative responses, we aim to identify domestic tasks desired for robotic assistance, and hence guide the design effort to better reflect user needs. Our study results show that householders want domestic robots for tasks including time-consuming drudgeries, house-sitting, and personal attendance. Further, we present three design lessons we learned to increase householders' acceptance of these robots. The design of domestic robots needs to provide a certain amount of human control, be compatible with the user's domestic environment, and take gender into consideration. Ja-Young Sung, Henrik I. Christensen, Rebecca E. Grinter	RO-MAN	2
2008	Housewives or technophiles?: understanding domestic robot owners abstract Despite the growing body of Human-Robot Interaction (HRI) research focused on domestic robots, surprisingly little is known about the demographic profile of robot owners and their influence on usage patterns. In this paper, we present the results of a survey of 379 iRobot's Roombao wners, that identified their demographic and usage trends. The outcome of the survey suggests that Roomba users are equally likely to be men or women, and they tend to be younger with high levels of education and technical backgrounds. Their adoption and use patterns illustrate the important role that gift exchange plays in adoption, and how the robot changes cleaning routines and creates non-cleaning activities. More generally, we argue that domestic robot adoption is growing, and suggest some of the factors that lead to a positive experience. Ja-Young Sung, Rebecca E. Grinter, Henrik I. Christensen, Lan Guo	HRI	3
2008	Detecting structural ambiguities and transitions during a guided tour abstract Service robots designed for domestic settings need to navigate in an environment that they have to share with their users. Thus, they have to be able to report their current state and whereabouts in a way that is comprehensible for the user. Pure metric maps do not usually correspond to the understanding of the environment a user would provide. Thus, the robotic map needs to be integrated with the human representation. With our framework for Human Augmented Mapping we aim to deal with this issue and assume a guided tour as basis for an initial mapping process. During such a tour the robotic system needs to be able to detect significant changes in its environment representation - structural ambiguities - to be able to invoke a clarification discourse with the user. In this paper we present our approach to the detection of such ambiguities, that is independent from prior specification and training of particular spatial categories. We evaluate our method on data sets obtained during several runs in indoor environments in the context of a guided tour scenario. Elin Anna Topp, Henrik I. Christensen	ICRA	2
2008	Towards robust place recognition for robot localization abstract Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place recognition algorithm should be robust to dynamic changes and it should perform consistently when recognizing a room (for instance a corridor) in different geographical locations. Also, it should be able to categorize places, a crucial capability for transfer of knowledge and continuous learning. In order to test the suitability of visual recognition algorithms for these tasks, this paper presents a new database, acquired in three different labs across Europe. It contains image sequences of several rooms under dynamic changes, acquired at the same time with a perspective and omnidirectional camera, mounted on a socket. We assess this new database with an appearance- based algorithm that combines local features with support vector machines through an ad-hoc kernel. Results show the effectiveness of the approach and the value of the database. Muhammad Muneeb Ullah, Andrzej Pronobis, Barbara Caputo, Jie Luo 0018, Patric Jensfelt, Henrik I. Christensen	ICRA	6
2008	Teleoperation for a ball-catching task with significant dynamics Christian Smith, Mattias Bratt, Henrik I. Christensen	Neural Networks	3
2008	From Sensors to Human Spatial Concepts: An Annotated Data Set abstract An annotated data set is presented meant to help researchers in developing, evaluating, and comparing various approaches in robotics for building space representations appropriate for communicating with humans. The data consist of omnidirectional images, laser range scans, sonar readings, and robot odometry. A set of base-level human spatial concepts is used to annotate the data. Zoran Zivkovic, Olaf Booij, Ben J. A. Kröse, Elin Anna Topp, Henrik I. Christensen	IEEE Trans. Robotics	5
2007	"My Roomba Is Rambo": Intimate Home Appliances Ja-Young Sung, Lan Guo, Rebecca E. Grinter, Henrik I. Christensen	UbiComp	4
2007	Using COTS to Construct a High Performance Robot Arm abstract In this paper we present a design study and technical specifications of a high performance robotic manipulator to be used for ball catching experiments using commercial off-the-shelf (COTS) components. Early evaluation shows that very good performance can be achieved using standardized PowerCube actuator modules from Amtec and a standard workstation using CAN bus communication. Implementation issues of low-level control and software platform are also described, as well as early experimental evaluation of the system. Christian Smith, Henrik I. Christensen	ICRA	2
2007	Minimum jerk based prediction of user actions for a ball catching task abstract The present paper examines minimum jerk models for human kinematics as a tool to predict user input in teleoperation with significant dynamics. Predictions of user input can be a powerful tool to bridge time-delays and to trigger autonomous sub-sequences. In this paper an example implementation is presented, along with the results of a pilot experiment in which a virtual reality simulation of a teleoperated ball-catching scenario is used to test the predictive power of the model. The results show that delays up to 100 ms can potentially be bridged with this approach. Mattias Bratt, Christian Smith, Henrik I. Christensen	IROS	3
2007	Reactive Tuning of Target Estimate Accuracy in Multisensor Data Fusion abstract Dealing with conflicting and target-specific requirements is an important issue in multisensor and multitarget tracking. This paper aims to allocate sensing resources among various targets in reaction to individual information requests. The proposed approach is to introduce agents for every relevant target responsible for its tracking. Such agents are expected to bargain with each other for a division of resources. A bilateral negotiation model is established for resource allocation in two-target tracking. The applications of agent negotiation to target covariance tuning are illustrated together with simulation results presented. Moreover, we suggest a way of organizing simultaneous one-to-one negotiations, making our negotiation model still applicable in scenarios of tracking more than two targets. Ning Xiong 0001, Henrik I. Christensen, Per Svensson 0001	Cybern. Syst.	2
2007	Agent negotiation of target distribution enhancing system survivability abstract This article proposes an agent negotiation model for target distribution across a set of geographically dispersed sensors. The key idea is to consider sensors as autonomous agents that negotiate over the division of tasks among them for obtaining better payoffs. The negotiation strategies for agents are established based upon the concept of subgame perfect equilibrium from game theory. Using such negotiation leads to not only superior measuring performance from a global perspective but also possibly balanced allocations of tasks to sensors, benefiting system robustness and survivability. A simulation test and results are given to demonstrate the ability of our approach in improving system security while keeping overall measuring performance near optimal. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 1251–1269, 2007. Ning Xiong 0001, Henrik I. Christensen, Per Svensson 0001	Int. J. Intell. Syst.	2
2007	Evolutionary Development of Hierarchical Learning Structures abstract Hierarchical reinforcement learning (RL) algorithms can learn a policy faster than standard RL algorithms. However, the applicability of hierarchical RL algorithms is limited by the fact that the task decomposition has to be performed in advance by the human designer. We propose a Lamarckian evolutionary approach for automatic development of the learning structure in hierarchical RL. The proposed method combines the MAXQ hierarchical RL method and genetic programming (GP). In the MAXQ framework, a subtask can optimize the policy independently of its parent task's policy, which makes it possible to reuse learned policies of the subtasks. In the proposed method, the MAXQ method learns the policy based on the task hierarchies obtained by GP, while the GP explores the appropriate hierarchies using the result of the MAXQ method. To show the validity of the proposed method, we have performed simulation experiments for a foraging task in three different environmental settings. The results show strong interconnection between the obtained learning structures and the given task environments. The main conclusion of the experiments is that the GP can find a minimal strategy, i.e., a hierarchy that minimizes the number of primitive subtasks that can be executed for each type of situation. The experimental results for the most challenging environment also show that the policies of the subtasks can continue to improve, even after the structure of the hierarchy has been evolutionary stabilized, as an effect of Lamarckian mechanisms Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen	IEEE Trans. Evol. Comput.	4
2007	Closing the Loop With Graphical SLAM abstract The problem of simultaneous localization and mapping (SLAM) is addressed using a graphical method. The main contributions are a computational complexity that scales well with the size of the environment, the elimination of most of the linearization inaccuracies, and a more flexible and robust data association. We also present a detection criteria for closing loops. We show how multiple topological constraints can be imposed on the graphical solution by a process of coarse fitting followed by fine tuning. The coarse fitting is performed using an approximate system. This approximate system can be shown to possess all the local symmetries. Observations made during the SLAM process often contain symmetries, that is to say, directions of change to the state space that do not affect the observed quantities. It is important that these directions do not shift as we approximate the system by, for example, linearization. The approximate system is both linear and block diagonal. This makes it a very simple system to work with especially when imposing global topological constraints on the solution. These global constraints are nonlinear. We show how these constraints can be discovered automatically. We develop a method of testing multiple hypotheses for data matching using the graph. This method is derived from statistical theory and only requires simple counting of observations. The central insight is to examine the probability of not observing the same features on a return to a region. We present results with data from an outdoor scenario using a SICK laser scanner. John Folkesson, Henrik I. Christensen	IEEE Trans. Robotics	2
2007	The M-Space Feature Representation for SLAM abstract In this paper, a new feature representation for simultaneous localization and mapping (SLAM) is discussed. The representation addresses feature symmetries and constraints explicitly to make the basic model numerically robust. In previous SLAM work, complete initialization of features is typically performed prior to introduction of a new feature into the map. This results in delayed use of new data. To allow early use of sensory data, the new feature representation addresses the use of features that initially have been partially observed. This is achieved by explicitly modelling the subspace of a feature that has been observed. In addition to accounting for the special properties of each feature type, the commonalities can be exploited in the new representation to create a feature framework that allows for interchanging of SLAM algorithms, sensor and features. Experimental results are presented using a low-cost Web-cam, a laser range scanner, and combinations thereof. John Folkesson, Patric Jensfelt, Henrik I. Christensen	IEEE Trans. Robotics	3
2006	Clarification dialogues in human-augmented mapping abstract An approach to dialogue based interaction for resolution of ambiguities encountered as part of Human-Augmented Mapping (HAM) is presented. The paper focuses on issues related to spatial organisation and localisation. The dialogue pattern naturally arises as robots are introduced to novel environments. The paper discusses an approach based on the notion of Questions under Discussion (QUD). The presented approach has been implemented on a mobile platform that has dialogue capabilities and methods for metric SLAM. Experimental results from a pilot study clearly demonstrate that the system can resolve problematic situations. Geert-Jan M. Kruijff, Hendrik Zender, Patric Jensfelt, Henrik I. Christensen	HRI	4
2006	Acquiring a shared environment representation abstract Interacting with a domestic service robot implies the existence for a joint environment model for a user and a robot. We present a pilot study that investigates, how humans present a familiar environment to a mobile robot. Results from this study are used to evaluate a generic environment model for a service robot that can be personalised by interaction. Elin Anna Topp, Henrik I. Christensen, Kerstin Severinson Eklundh	HRI	2
2006	SLAM using Visual Scan-Matching with Distinguishable 3D Points abstract Scan-matching based on data from a laser scanner is frequently used for mapping and localization. This paper presents an scan-matching approach based instead on visual information from a stereo system. The scale invariant feature transform (SIFT) is used together with epipolar constraints to get high matching precision between the stereo images. Calculating the 3D position of the corresponding points in the world results in a visual scan where each point has a descriptor attached to it. These descriptors can be used when matching scans acquired from different positions. Just like in the work with laser based scan matching a map can be defined as a set of reference scans and their corresponding acquisition point. In essence this reduces each visual scan that can consist of hundreds of points to a single entity for which only the corresponding robot pose has to be estimated in the map. This reduces the overall complexity of the map. The SIFT descriptor attached to each of the points in the reference allows for robust matching and detection of loop closing situations. The paper presents real-world experimental results from an indoor office environment Federico Bertolli, Patric Jensfelt, Henrik I. Christensen	IROS	3
2006	Design of a Control Strategy for Teleoperation of a Platform with Significant Dynamics abstract A teleoperation system for controlling a robot with fast dynamics over the Internet has been constructed. It employs a predictive control structure with an accurate dynamic model of the robot to overcome problems caused by varying delays. The operator interface uses a stereo virtual reality display of the robot cell, and a haptic device for force feed-back including virtual obstacle avoidance forces Mattias Bratt, Christian Smith, Henrik I. Christensen	IROS	3
2006	Attentional Landmark Selection for Visual SLAM abstract In this paper, we introduce a new method to automatically detect useful landmarks for visual SLAM. A biologically motivated attention system detects regions of interest which "pop-out" automatically due to strong contrasts and the uniqueness of features. This property makes the regions easily redetectable and thus they are useful candidates for visual landmarks. Matching based on scene prediction and feature similarity allows not only short-term tracking of the regions, but also redetection in loop closing situations. The paper demonstrates how regions are determined and how they are matched reliably. Various experimental results on real-world data show that the landmarks are useful with respect to be tracked in consecutive frames and to enable closing loops Simone Frintrop, Patric Jensfelt, Henrik I. Christensen	IROS	3
2006	Design of an Office-Guide Robot for Social Interaction Studies abstract In this paper, the design of an office-guide robot for social interaction studies is presented. We are interested in studying the impact of passage behaviours in casual encounters. While the system offers assistance in locating the appropriate office that a visitor wants to reach, it is expected to engage in a passing behaviour to allow free passage for other persons that it may encounter. Through use of such an approach it is possible to study the effect of social interaction in a situation that is much more natural than out-of-context user studies. The system has been tested in an early evaluation phase when it worked for almost 7 hours. A total of 64 interactions with people were registered and 13 passage behaviors were performed to conclude that this framework can be successfully used for the evaluation of passing behaviors in natural contexts of operation Elena Pacchierotti, Henrik I. Christensen, Patric Jensfelt	IROS	2
2006	A Discriminative Approach to Robust Visual Place Recognition abstract An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Usually localization is performed based on a purely geometric model. Through use of vision and place recognition a number of opportunities open up in terms of flexibility and association of semantics to the model. To achieve this we present an appearance based method for place recognition. The method is based on a large margin classifier in combination with a rich global image descriptor. The method is robust to variations in illumination and minor scene changes. The method is evaluated across several different cameras, changes in time-of-day and weather conditions. The results clearly demonstrate the value of the approach. Andrzej Pronobis, Barbara Caputo, Patric Jensfelt, Henrik I. Christensen	IROS	4
2006	A Discriminative Approach to Robust Visual Place Recognition abstract An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Usually localization is performed based on a purely geometric model. Through use of vision and place recognition a number of opportunities open up in terms of flexibility and association of semantics to the model. To achieve this, the present paper presents an appearance based method for place recognition. The method is based on a large margin classifier in combination with a rich global image descriptor. The method is robust to variations in illumination and minor scene changes. The method is evaluated across several different cameras, changes in time-of-day and weather conditions. The results clearly demonstrate the value of the approach Andrzej Pronobis, Barbara Caputo, Patric Jensfelt, Henrik I. Christensen	IROS	4
2006	Topological Modelling for Human Augmented Mapping abstract Service robots designed for domestic settings need to navigate in an environment that they have to share with their users. Thus, they have to be able to report their current state and whereabouts in a way that is comprehensible for the user. Pure metric maps do not usually correspond to the understanding of the environment a user would provide. Thus, the robotic map needs to be integrated with the human representation. This paper describes our framework of human augmented mapping that allows us to achieve this integration. We propose further a method to specify and represent regions that relate to a user's view on the environment. We assume an interactive setup for the specification of regions and show the applicability of our method in terms of distinctiveness for space segmentation and in terms of localisation purposes Elin Anna Topp, Henrik I. Christensen	IROS	2
2006	Bringing Together Human and Robotic Environment Representations A Pilot Study abstract Human interaction with a service robot requires a shared representation of the environment for spoken dialogue and task specification where names used for particular locations are depending on personal preferences. A question is how such human oriented models can be tied to the geometric robotic models needed for precise localisation and navigation. We assume that this integration can be based on the information potential users give to a service robot about its working environment. We further believe that this information is best given in an interactive setting (a "guided tour") in this particular environment. This paper presents a pilot study that investigates how humans present a familiar environment to a mobile robot. The study is set up within our concept of human augmented mapping, for which we assume an initial "guided tour" scenario to teach a robot its environment. Results from this pilot study are used to validate a proposed generic environment model for a service robot Elin Anna Topp, Helge Hüttenrauch, Henrik I. Christensen, Kerstin Severinson Eklundh	IROS	3
2006	What's in the gap? Interaction transitions that make HRI work abstract This paper presents an in-depth analysis from a human robot interaction (HRI) study on spatial positioning and interaction episode transitions. Subjects showed a living room to a robot to teach it new places and objects. This joint task was analyzed with respect to organizing strategies for interaction episodes. Noticing the importance of transitions between interaction episodes, small adaptive movements in posture were observed. This finding needs to be incorporated into HRI modules that plan and execute robots' spatial behavior in interaction, e.g., through dynamic adaptation of spatial formations and distances depending on interaction episode Helge Hüttenrauch, Kerstin Severinson Eklundh, Anders Green, Elin Anna Topp, Henrik I. Christensen	RO-MAN	5
2006	Situated dialogue and understanding spatial organization: Knowing what is where and what you can do there abstract The paper presents an HRI architecture for human-augmented mapping. Through interaction with a human, the robot can augment its autonomously learnt metric map with qualitative information about locations and objects in the environment. The system implements various interaction strategies observed in independent Wizard-of-Oz studies. The paper discusses an ontology-based approach to representing and inferring 2.5D spatial organization, and presents how knowledge of spatial organization can be acquired autonomously or through spoken dialogue interaction Geert-Jan M. Kruijff, Hendrik Zender, Patric Jensfelt, Henrik I. Christensen	RO-MAN	4
2006	Evaluation of Mapping with a Tele-operated Robot with Video Feedback abstract This research has examined robot operators' abilities to gain situational awareness while performing tele-operation with video feedback. The research included a user study in which 20 test persons explored and drew a map of a corridor and several rooms, which they had not visited before. Half of the participants did the exploration and mapping using a teleoperated robot (IRobot PackBot) with video feedback but without being able to see or enter the exploration area themselves. The other half fulfilled the task manually by walking through the premises. The two groups were evaluated regarding time consumption and the rendered maps were evaluated concerning error rate and dimensional and logical accuracy. Dimensional accuracy describes the test person's ability to estimate and reproduce dimensions in the map. Logical accuracy refers to missed, added, misinterpreted, reversed and inconsistent objects or shapes in the depiction. The evaluation showed that fulfilling the task with the robot on average took 96% longer time and rendered 44% more errors than doing it without the robot. Robot users overestimated dimensions with an average of 16% while non-robot users made an average overestimation of 1%. Further, the robot users had a 69% larger standard deviation in their dimensional estimations and on average made 23% more logical errors during the test Carl Lundberg, Henrik I. Christensen	RO-MAN	2
2006	Evaluation of Passing Distance for Social Robots abstract Casual encounters with mobile robots for nonexperts can be a challenge due to lack of an interaction model. The present work is based on the rules from proxemics which are used to design a passing strategy. In narrow corridors the lateral distance of passage is a key parameter to consider. An implemented system has been used in a small study to verify the basic parametric design for such a system. In total 10 subjects evaluated variations in proxemics for encounters with a robot in a corridor setting. The user feedback indicates that entering the intimate sphere of people is less comfortable, however a too significant avoidance is also considered unnecessary. Adequate signaling of avoidance is a behaviour that must be carefully tuned Elena Pacchierotti, Henrik I. Christensen, Patric Jensfelt	RO-MAN	2
2005	Biologically inspired embodied evolution of survival abstract Embodied evolution is a methodology for evolutionary robotics that mimics the distributed, asynchronous and autonomous properties of biological evolution. The evaluation, selection and reproduction are carried out by and between the robots, without any need for human intervention. In this paper, we propose a biologically inspired embodied evolution framework, which fully integrates self-preservation, recharging from external batteries in the environment, and self-reproduction, pair-wise exchange of genetic material, into a survival system. The individuals are explicitly evaluated for the performance of the battery capturing task, but also implicitly for the mating task by the fact that an individual that mates frequently has larger probability to spread its gene in the population. We have evaluated our method in simulation experiments and the simulation results show that the solutions obtained by our embodied evolution method were able to optimize the two survival tasks, battery capturing and mating, simultaneously. We have also performed preliminary experiments in hardware, with promising results. Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen	Congress on Evolutionary Computation	4
2005	Vision SLAM in the Measurement Subspace abstract In this paper we describe an approach to feature representation for simultaneous localization and mapping, SLAM. It is a general representation for features that addresses symmetries and constraints in the feature coordinates. Furthermore, the representation allows for the features to be added to the map with partial initialization. This is an important property when using oriented vision features where angle information can be used before their full pose is known. The number of the dimensions for a feature can grow with time as more information is acquired. At the same time as the special properties of each type of feature are accounted for, the commonalities of all map features are also exploited to allow SLAM algorithms to be interchanged as well as choice of sensors and features. In other words the SLAM implementation need not be changed at all when changing sensors and features and vice versa. Experimental results both with vision and range data and combinations thereof are presented. John Folkesson, Patric Jensfelt, Henrik I. Christensen	ICRA	3
2005	Graphical SLAM using vision and the measurement subspace abstract In this paper we combine a graphical approach for simultaneous localization and mapping, SLAM, with a feature representation that addresses symmetries and constraints in the feature coordinates, the measurement subspace, M-space. The graphical method has the advantages of delayed linearizations and soft commitment to feature measurement matching. It also allows large maps to be built up as a network of small local patches, star nodes. This local map net is then easier to work with. The formation of the star nodes is explicitly stable and invariant with all the symmetries of the original measurements. All linearization errors are kept small by using a local frame. The construction of this invariant star is made clearer by the M-space feature representation. The M-space allows the symmetries and constraints of the measurements to be explicitly represented. We present results using both vision and laser sensors. John Folkesson, Patric Jensfelt, Henrik I. Christensen	IROS	3
2005	Tracking for following and passing persons abstract This paper presents a multiple target tracking approach for following and passing persons in the context of human-robot interaction. The general purpose for the approach is the use in human augmented mapping. This concept is presented and it is described how navigation and person following are subsumed under it. Results from experiments under test conditions and from data collected during a user study are also provided. Elin Anna Topp, Henrik I. Christensen	IROS	2
2005	Session Overview Simultaneous Localisation and Mapping Paul Newman 0001, Henrik I. Christensen	ISRR	2
2004	Artificial Potential Biased Probabilistic Roadmap Method abstract Probabilistic roadmap methods (PRM) have been successfully used to solve difficult path planning problems but their efficiency is limited when the free space contains narrow passages through which the robot must pass. This paper presents a new sampling scheme that aims to increase the probability of finding paths through narrow passages. Here, a biased sampling scheme is used to increase the distribution of nodes in narrow regions of the free space. A partial computation of the artificial potential field is used to bias the distribution of nodes. Daniel Aarno, Danica Kragic, Henrik I. Christensen	ICRA	3
2004	Navigation for Human-Robot Interaction Tasks abstract One major design goal in human-robot interaction is that the robots behave in an intelligent manner, preferably in a similar way as humans. This constraint must also be taken into consideration when the navigation system for the platform is developed. However, research in human-robot interaction is often restricted to other components of the system including gestures, manipulation, and speech. On the other hand, research for mobile robot navigation focuses primarily on the task of reaching a certain goal point in an environment. We believe that these two problems can not be treated separately for a personal robot that coexists with humans in the same surrounding. Persons move constantly while they are interacting with each other. Hence, also a robot should do that, which poses constraints on the navigation system. This type of navigation is the focus of this paper. Methods have been developed for a robot to join a group of people engaged in a conversation. Preliminary results show that the platform's moving patterns are very similar to the ones of the persons. Moreover, this dynamic interaction has been judged naturally by the test subjects, which greatly increases the perceived intelligence of the robot. Philipp Althaus, Hiroshi Ishiguro, Takayuki Kanda 0001, Takahiro Miyashita, Henrik I. Christensen	ICRA	5
2004	Graphical SLAM - a Self-correcting Map abstract We describe an approach to simultaneous localization and mapping, SLAM. This approach has the highly desirable property of robustness to data association errors. Another important advantage of our algorithm is that non-linearities are computed exactly, so that global constraints can be imposed even if they result in large shifts to the map. We represent the map as a graph and use the graph to find an efficient map update algorithm. We also show how topological consistency can be imposed on the map, such as, closing a loop. The algorithm has been implemented on an outdoor robot and we have experimental validation of our ideas. We also explain how the graph can be simplified leading to linear approximations of sections of the map. This reduction gives us a natural way to connect local map patches into a much larger global map. John Folkesson, Henrik I. Christensen	ICRA	2
2004	Measurement Errors in Visual Servoing abstract In recent years, a number of hybrid visual servoing control algorithms have been proposed and evaluated. For some time now, it has been clear that classical control approaches-image and position based-have some inherent problems. Hybrid approaches try to combine them to overcome these problems. However, most of the proposed approaches concentrate on the design of the control law, neglecting the issue of errors resulting from the sensory system. This paper addresses the issue of measurement errors in visual servoing. The particular contribution is the analysis of the propagation of image error through pose estimation and visual servoing control law. We have chosen to investigate the properties of the vision system and their effect to the performance of the control system. Two approaches are evaluated: i) position, and ii) 2 1/2 D visual servoing. We believe that our evaluation offers a tool to build and analyze hybrid control systems based on, for example, switching or partitioning. Ville Kyrki, Danica Kragic, Henrik I. Christensen	ICRA	3
2004	An Architecture for Indoor Navigation abstract This paper is concerned with the design and implementation of a control architecture for a mobile robot that is to navigate in dynamic unknown indoor environments. It is based on the framework of Open Robot Control Software @ KTH, which is discussed and evaluated in this paper. As a hybrid architecture, it is decomposed into several basic components which can be classified as either deliberative or reactive. Each component can concurrently execute and communicate with another using unified communication interfaces. Scalability and portability and reusability are the goals of the design. Wenfeng Li 0001, Henrik I. Christensen, Anders Orebäck, Dingfang Chen	ICRA	2
2004	An Interactive Interface for Service Robots abstract In this paper, we present an initial design of an interactive interface for a service robot based on multisensor fusion. We show how the integration of speech, vision and laser range data can be performed using a high level of abstraction. Guided by a number of scenarios commonly used in a service robot framework, the experimental evaluation will show the benefit of sensory integration which allows the design of a robust and natural interaction system using a set of simple perceptual algorithms. Elin Anna Topp, Danica Kragic, Patric Jensfelt, Henrik I. Christensen	ICRA	4
2004	2D Mapping of Cluttered Indoor Environments by Means of 3D Perception abstract This paper presents a combination of a 3D laser sensor and a line-base SLAM algorithm which together produce 2D line maps of highly cluttered indoor environments. The key of the described method is the replacement of commonly used 2D laser range sensors by 3D perception. A straightforward algorithm extracts a virtual 2D scan that also contains partially occluded walls. These virtual scans are used as input for SLAM using line segments as features. The paper presents the used algorithms and experimental results that were made in a former industrial bakery. The focus lies on scenes that are known to be problematic for pure 2D systems. The results demonstrate that mapping indoor environments can be made robust with respect to both, poor odometry and clutter. Oliver Wulf, Kai Oliver Arras, Henrik I. Christensen, Bernardo Wagner	ICRA	3
2004	Multi-agent reinforcement learning: using macro actions to learn a mating task abstract Standard reinforcement learning methods are inefficient and often inadequate for learning cooperative multi-agent tasks. For these kinds of tasks the behavior of one agent strongly depends on dynamic interaction with other agents, not only with the interaction with a static environment as in standard reinforcement learning. The success of the learning is therefore coupled to the agents' ability to predict the other agents behaviors. In this study we try to overcome this problem by adding a few simple macro actions, actions that are extended in time for more than one time step. The macro actions improve the learning by making search of the state space more effective and thereby making the behavior more predictable for the other agent. In this study we have considered a cooperative mating task, which is the first step towards our aim to perform embodied evolution, where the evolutionary selection process is an integrated part of the task. We show, in simulation and hardware, that in the case of learning without macro actions, the agents fail to learn a meaningful behavior. In contrast, for the learning with macro action the agents learn a good mating behavior in reasonable time, in both simulation and hardware. Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen	IROS	4
2004	New shortest-path approaches to visual servoing abstract In recent years, a number of visual servo control algorithms have been proposed. Most approaches try to solve the inherent problems of image-based and position based servoing by partitioning the control between image and Cartesian spaces. However, partitioning of the control often causes the Cartesian path to become more complex, which might result in operation close to the joint limits. A solution to avoid the joint limits is to use a shortest-path approach, which avoids the limits in most cases. In this paper, two new shortest-path approaches to visual servoing are presented. First, a position-based approach is proposed that guarantees both shortest Cartesian trajectory and object visibility. Then, a variant is presented, which avoids the use of a 3D model of the target object by using homography based partial pose estimation. Ville Kyrki, Danica Kragic, Henrik I. Christensen	IROS	3
2003	Automatic map acquisition for navigation in domestic environment abstract An autonomous robot navigating in its environment needs a map representing the large-scale structure of the setting. There are a variety of different types of maps used in mobile robotics: for example, grid maps, maps containing geometrical beacons, or topological maps. Each of those poses its own constraints on the problem of acquiring the map, where its complexity is a major issue. We present a system that is able to build a topological map of large-scale indoor environments in a semi-autonomous way. This means that a person shows the robot around, interacts with it via a basic interface, the platform is following autonomously, and simultaneously creating the map. The acquisition mechanisms are rather simple and computationally inexpensive, due to the low complexity of the topological map. However, experiments show that this map is sufficient to navigate between arbitrary positions in the environment. Philipp Althaus, Henrik I. Christensen	ICRA	2
2003	Outdoor exploration and SLAM using a compressed filter abstract In this paper we describe the use of automatic explorationfor autonomous mapping of outdoor scenes. We describe areal-time SLAM implementation along with an autonomous explorationalgorithm. We have ... John Folkesson, Henrik I. Christensen	ICRA	2
2003	Confluence of parameters in model based tracking abstract During the last decade, model based tracking of objects and its necessity in visual servoing and manipulation has been advocated in a number of systems. Most of these systems demonstrate robust performance for cases where either the background or the object are relatively uniform in color. In terms of manipulation, our basic interest is handling of everyday objects in domestic environments such as a home or an office. In this paper, we consider a number of different parameters that effect the performance of a model-based tracking system. Parameters such as color channels, feature detection, validation gates, outliers rejection and feature selection are considered here and their affect to the overall system performance is discussed. Experimental evaluation shows how some of these parameters can successfully be evaluated (learned) on-line and consequently improve the performance of the system. Danica Kragic, Henrik I. Christensen	ICRA	2
2003	Vision and tactile sensing for real world tasks abstract Robotic fetch-and-carry tasks are commonly facilitated to demonstrate a number of research directions such as navigation, mobile manipulation, systems integration, etc. As a part of an integrated system in terms of a service robot framework, this paper describes a set of methods for real-world object manipulation tasks. We concentrate here on two particular parts of a manipulation sequence: i) robust visual servoing, and ii) grasping strategies. In terms of visual servoing we discuss the handling of singularities during a manipulation sequence. For grasping, we present a biologically motivated strategy using tactile feedback. Danica Kragic, S. Crinier, Dietrich Brunn, Henrik I. Christensen	ICRA	4
2003	Implementation of multi-rigid-body dynamics within a robotic grasping simulator abstract Robotic simulation systems allow researchers, engineers, and students to test control algorithms in a safe environment, but until recently these systems only simulated the dynamics of the mechanism itself and could not simulate (complex) contacts with other bodies in the environment. However, if the robot's task involves grasping an object, accurate simulation of contact and friction forces is a necessity. Recently developed methods formulate the constrains as a linear complementarity problem, allowing a solution to be computed using proven algorithms, but for anyone implementing such a system, several additional considerations must be taken into account. In this paper we present the implementation of the dynamics module of our freely available grasping simulator and present an example grasping task. Andrew T. Miller, Henrik I. Christensen	ICRA	2
2003	Automatic grasp planning using shape primitives abstract Automatic grasp planning for robotic hands is a difficult problem because of the huge number of possible hand configurations. However, humans simplify the problem by choosing an appropriate prehensile posture appropriate for the object and task to be performed. By modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, we can use a set of rules to generate a set of grasp starting positions and pregrasp shapes that can then be tested on the object model. Each grasp is tested and evaluated within our grasping simulator "GraspIt!", and the best grasps are presented to the user. The simulator can also plan grasps in a complex environment involving obstacles and the reachability constraints of a robot arm. Andrew T. Miller, Steffen Knoop, Henrik I. Christensen, Peter K. Allen	ICRA	3
2003	A Framework for Visual Servoing Danica Kragic, Henrik I. Christensen	ICVS	2
2003	Biologically motivated visual servoing and grasping for real world tasks abstract Hand-eye coordination involves four tasks: i) identification of the object to be manipulated, ii) ballistic arm motion to the vicinity of the object, iii) preshaping and alignment of the hand, and finally iv) manipulation or grasping of the object. Motivated by the operation of biological systems and utilizing some constraints for each of the above mentioned tasks, we are aiming at design of a robust, robotic hand-eye coordination system. Hand-eye coordination tasks we consider here are of the basic fetch-and-carry type useful for service robots operating in everyday environments. Objects to be manipulated are, for example, food items that are simple in shape (polyhedral, cylindrical) but with complex surface texture. To achieve the required robustness and flexibility, we integrate both geometric and appearance based information to solve the task at hand. We show how the research in human visuo-motor system can be facilitated to design a fully operational, visually guided object manipulation system. Danica Kragic, Henrik I. Christensen	IROS	2
2003	PDA interface for a field robot abstract Operating robots in an outdoor setting poses interesting problems in terms of interaction. To interact with the robot there is a need for a flexible computer interface. In this paper a PDA-based (personal digital assistant, i.e. a handheld computer) approach to robot interaction is presented. The system is designed to allow non-expert users to utilise the robot for operation in an urban exploration setup. The basic design is outlined and a first set of experiments are reported. Carl Lundberg, Carl Barck-Holst, John Folkesson, Henrik I. Christensen	IROS	4
2003	Session Summary Henrik I. Christensen	ISRR	1
2002	Multiple Plane Segmentation Using Optical Flow abstract In this paper we present a motion based segmentation algorithm to automatically detect multiple planes from sparse optical ¤ow information. An optimal estimate for planar motion in the presence of additive Gaussian noise is £rst proposed, in-cluding directional uncertainty of the measurements (thus coping with the aper-ture problem) and a multi-frame (n> 2) setting (adding overall robustness). In the presence of multiple planes in motion, the residuals of the motion estimation model are used in a clustering algorithm to segment the different planes. The image motion parameters are used to £nd an initial cluster of features be-longing to a surface, which is then grown towards the surface borders. Initialization is random and only robust statistics and continuity constraints are used. There is no need for using and tuning thresholds. Since the exact parametric planar ¤ow model is used, the algorithm is able to cope ef£ciently with projective distortions and 3D motion and structure can be directly estimated. 1 Marco Zucchelli, José Santos-Victor, Henrik I. Christensen	BMVC	3
2002	Weak Models and Cue Integration for Real-Time Tracking abstract Traditionally, fusion of visual information for tracking has been based on explicit models for uncertainty and integration. Most of the approaches use some form of Bayesian statistics where strong models are employed. We argue that for cases where a large number of visual features are available, weak models for integration may be employed. We analyze integration by voting where two methods are proposed and evaluated: (i) response and (ii) action fusion. The methods differ in the choice of voting space: the former integrates visual information in image space and latter in velocity space. We also evaluate four weighting techniques for integration. Danica Kragic, Henrik I. Christensen	ICRA	2
2002	Systems Integration for Real-World Manipulation Tasks abstract A system developed to demonstrate integration of a number of key research areas such as localization, recognition, visual tracking, visual servoing and grasping is presented together with the underlying methodology adopted to facilitate the integration. Through sequencing of basic skills, provided by the above mentioned competencies, the system has the potential to carry out flexible grasping for fetch and carry in realistic environments. Through careful fusion of reactive and deliberative control and use of multiple sensory modalities a significant flexibility is achieved. Experimental verification of the integrated system is presented. Lars Petersson, Patric Jensfelt, Dennis Tell, M. Strandberg, Danica Kragic, Henrik I. Christensen	ICRA	6
2002	Behaviour coordination for navigation in office environments abstract Behaviour coordination is a notorious problem in mobile robotics. Behaviours are either in competition or collaborating to achieve the goals of a system, which leads to requirements for arbitration and/or fusion of control signals. In most systems the arbitration is specified in terms of "events" that denote positions or sensory input. The detection of these events allows discrete switching between groups of behaviours. In contrast, the fusion of behaviours is often achieved using potential fields, fuzzy rules, or superposition. In most cases, the underlying theoretical foundation is rather weak and the behaviour switching results in discrete changes in the overall system dynamics. In this paper, we present a scheme for behaviour coordination that is grounded in the dynamical systems approach. The methodology provides a solid theoretical basis for analysis and design of a behaviour coordination framework. This framework is demonstrated in the context of a domestic robot for fetch-and-carry type tasks. It is here shown that behaviour coordination can be analyzed as an integral part of the design to facilitate smooth transition and fusion between behaviours. Philipp Althaus, Henrik I. Christensen	IROS	2
2002	Model based techniques for robotic servoing and grasping abstract A robotic manipulation of objects typically involves object detection/recognition, servoing to the object, alignment and grasping. To perform fine alignment and final grasping, it is usually necessary to estimate the position and orientation (pose) of the object. In this paper we present a model based tracking system used to estimate and continuously update the pose of the object to be manipulated. Here, a wire-frame model is used to find and track features in the consequent images. One of the important parts of the system is the ability to automatically initiate the tracking process. The strength of the system is the ability to operate in an domestic environment (living room) with changing lighting and background conditions. Danica Kragic, Henrik I. Christensen	IROS	2
2001	Recursive flow based structure from parallax with automatic rescaling abstract In this paper we propose a technique to recursively estimate structure and motion from a sequence of images acquired by an hand held camera. The algorithm is based on estimation of instantaneous optical flow for each frame of the sequence and on the use of the differential epipolar constraint to compute motion and structure. An alternative procedure to manage scale ambiguity across frames is also proposed. Neither user interaction nor any kind of scene knowledge is required and the algorithm, given its low complexity, is adaptable to real time applications. Marco Zucchelli, Henrik I. Christensen	BMVC	2
2001	Using the dynamical system approach to navigate in realistic real-world environments abstract The dynamical system approach to behaviour based robotics provides a sound mathematical framework to behaviour design and integration. So far this approach has been used in various simulation work and in simple real world settings. This paper is a first step towards application in a more realistic scenario such as a typical office environment. The robot perceives its environment via a set of sonar sensors. Simple geometric representations of the corridor and obstacles are extracted from the perceptual information. Obstacle avoidance and corridor following are implemented as the basic behaviours, which allow the robot to navigate safely through its environment. The robot can reliably distinguish between passages that are either wide enough to pass or too narrow to be traversed. Coordination among the primitive behaviours allows the robot to cope with more complex situations, such as a corridor that is blocked by obstacles, in a flexible manner. Philipp Althaus, Henrik I. Christensen, Frank Hoffmann 0001	IROS	2
2001	Intelligent Home Appliances Henrik I. Christensen	ISRR	1
2001	Pose tracking using laser scanning and minimalistic environmental models abstract Keeping track of the position and orientation over time using sensor data, i.e., pose tracking, is a central component in many mobile robot systems. In this paper, we present a Kalman filter-based approach utilizing a minimalistic environmental model. By continuously updating the pose, matching the sensor data to the model is straightforward and outliers can be filtered out effectively by validation gates. The minimalistic model paves the way for a low-complexity algorithm with a high degree of robustness and accuracy. Robustness here refers both to being able to track the pose for a long time, but also handling changes and clutter in the environment. This robustness is gained by the minimalistic model only capturing the stable and large scale features of the environment. The effectiveness of the pose tracking is demonstrated through a number of experiments, including a run of 90 min., which clearly establishes the robustness of the method. Patric Jensfelt, Henrik I. Christensen	IEEE Trans. Robotics Autom.	2
2001	Cue integration for visual servoing abstract The robustness and reliability of vision algorithms is, nowadays, the key issue in robotic research and industrial applications. To control a robot in a closed-loop fashion, different tracking systems have been reported in the literature. A common approach to increased robustness of a tracking system is the use of different models (CAD model of the object, motion model) known a priori. Our hypothesis is that fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. A particular application is the estimation of a robot's end-effector position in a sequence of images. The research investigates the following two different approaches to cue integration: 1) voting and 2) fuzzy logic-based fusion. The two approaches have been tested in association with scenes of varying complexity. Experimental results clearly demonstrate that fusion of cues results in a tracking system with a robust performance. The robustness is in particular evident for scenes with multiple moving objects and partial occlusion of the tracked object. Danica Kragic, Henrik I. Christensen	IEEE Trans. Robotics Autom.	2
2000	Tracking Techniques for Visual Servoing Tasks abstract Many of today's visual servoing systems rely on the use of markers on the object to provide features for control. There is thus a need for a visual system that provides control features regardless of the appearance of the object. Region based tracking is a natural approach since it does not require any special type of features. In this paper we present two different approaches to region based tracking: 1) a multi-resolution gradient based approach (using optical flow); and 2) a discrete feature based search approach. We present experiments conducted with both techniques for different types of image motions. Finally, the performance, drawbacks and limitations of used techniques are discussed. Danica Kragic, Henrik I. Christensen	ICRA	2
2000	BERRA: A Research Architecture for Service Robots abstract The architecture for a mobile service robot is discussed. The paper covers aspects related to overall design and implementation. The robot architecture is of the hybrid deliberative/reactive behavioral type. The strategy is selection where planning is viewed as configuration. The architecture can be divided into three layers, one for deliberation, one for task execution, and one reactive layer. Scalability and a high degree of flexibility have been primary design goals, making it easy to reconfigure the system. The system has been built in an object oriented fashion. An application of the architecture has been tested in a significant number of missions in our lab, where one room has been setup as an ordinary living room. Matthias Lindström, Anders Orebäck, Henrik I. Christensen	ICRA	3
2000	Vision-based door-traversal for autonomous mobile robots abstract Robust and safe traversal of doors is an important task for autonomous mobile robots. This paper presents a robust and inexpensive approach for recognizing and localizing doors based on monocular grey-level images and minimalistic models. The traversal is achieved by servoing the robot with respect to the door-hypothesis. Robustness against pose errors, scene complexity, and sensing conditions is obtained by combining indexing on significant aggregated features with a multi-view approach that employs consistency over time: pose-hypotheses are filtered via the motion of the robot to reject incorrect ones. The traversal is implemented as a behavior and was evaluated in 150 experiments at different doors under different conditions. Christof Eberst, Henrik I. Christensen	IROS	3
2000	Active exploration for feature based global localization abstract Presents an algorithm for active exploration of the environment by a mobile robot when performing global localization. During the localization process interesting regions for future exploration are selected based on already detected features and on the hypotheses generated by the localization algorithm. The localization process is improved by presenting it a richer set of features. The proposed algorithm provides highly robust global localization in real world environments with very low computational effort spent in finding exploration goal points. Experimental results are given, demonstrating the effectiveness of the algorithm in a number of different situations. Marco Seiz, Patric Jensfelt, Henrik I. Christensen	IROS	3
2000	Triangulation-based fusion of sonar data with application in robot pose tracking abstract In this paper a sensor fusion scheme, called triangulation-based fusion (TBF) of sonar data, is presented. This algorithm delivers stable natural point landmarks, which appear in practically all indoor environments, i.e., vertical edges like door posts, table legs, and so forth. The landmark precision is in most cases within centimeters. The TBF algorithm is implemented as a voting scheme, which groups sonar measurements that are likely to have hit the same object in the environment. The algorithm has low complexity and is sufficiently fast for most mobile robot applications. As a case study, we apply the TBF algorithm to robot pose tracking. The pose tracker is implemented as a classic extended Kalman filter, which use odometry readings for the prediction step and TBF data for measurement updates. The TBF data is matched to pre-recorded reference maps of landmarks in order to measure the robot pose. In corridors, complementary TBF data measurements from the walls are used to improve the orientation and position estimate. Experiments demonstrate that the pose tracker is robust enough for handling kilometer distances in a large scale indoor environment containing a sufficiently dense landmark set. Olle Wijk, Henrik I. Christensen	IEEE Trans. Robotics Autom.	2
1999	Laser Based Pose Tracking abstract The trend in localization is towards using more and more detailed models of the world. Our aim is to deal with the question of how simple a model can be used to provide and maintain pose information in an in-door setting. In this paper a Kalman filter based method for continuous position updating using a laser scanner is presented. By updating the position at a high frequency the matching problem becomes tractable and outliers can effectively be filtered out by means of validation gates. The experimental results presented show that the method performs very well in an in-door environment. Patric Jensfelt, Henrik I. Christensen	ICRA	2
1999	A Person Following Behaviour for a Mobile Robot abstract In this paper, a person following behaviour for a mobile robot is presented. The head of the person is located using skin colour detection. Then, a control loop is fed with the camera movements required to put the upper part of the person in the center of the image. The algorithm was tested in different rooms of a research lab. It performed well in all lighting conditions except in direct sunlight. Since the background and lighting cannot be controlled, the vision algorithm must be robust to such changes. However, since the computing power is quite limited, the algorithm must have as low complexity as possible. Hedvig Kjellström, Danica Kragic, Henrik I. Christensen	ICRA	3
1999	Robotics in the Home, Office, and Playing Field Minoru Asada, Henrik I. Christensen	IJCAI	2
1999	Integration of visual cues for active tracking of an end-effector abstract We describe and test how information from multiple sources can be combined into a robust visual servoing system. The main objective is integration of visual cues to provide smooth pursuit in a cluttered environment using a minimum or no calibration. For that purpose, voting schema and fuzzy logic command fusion are investigated. It is shown that the integration permits detection and rejection of measurement outliers. Danica Kragic, Henrik I. Christensen	IROS	2
1999	A hybrid control architecture for mobile manipulation abstract We present a scheme for mobile manipulation by introducing a mobile manipulation control architecture (MMCA). This architecture is motivated by a need for a systematic control structure for robotic manipulation within a behavior based framework. The control structure enables integration of the manipulator into a behavior based control structure for the platform. Furthermore, our suggested MMCA is designed in such a way that it supports design and performance analysis from both a manipulator dynamics and a hybrid automata perspective. Lars Petersson, Magnus Egerstedt, Henrik I. Christensen	IROS	3
1999	Exploiting process integration and composition in the context of active vision abstract The visual robustness of biological systems is in part due to their ability to actively integrate (fuse) information from a number of visual cues. In addition to active integration, the perception-action nature of biological vision demands event-driven behavioral composition. Providing mechanical vision systems with similar capabilities therefore requires tools and techniques for cue integration and behavioral composition. In this paper, we address two issues. First, we present a unified approach for handling both active integration and behavioral composition. The approach combines a theoretical framework that handles uncertainty using a voting scheme with a set of behaviors that are committed to achieving a specific goal through common effort and a well-known process composition model. Secondly, we address the issue of integration in the active vision activity of smooth pursuit. We have experimented with the fusion of four smooth pursuit techniques (blob tracking, edge tracking, template matching and image differencing). We discuss each technique, highlighting their strengths and weaknesses, and then show that fusing the techniques according to our formal framework improves system tracking behavior. Jeffrey A. Fayman, Paolo Pirjanian, Henrik I. Christensen, Ehud Rivlin	IEEE Trans. Syst. Man Cybern. Part C	3
1998	A Model-Free Voting Approach for Integrating Multiple Cues Carsten G. Bräutigam, Jan-Olof Eklundh, Henrik I. Christensen	ECCV (1)	3
1998	Triangulation based Fusion of Ultrasonic Sensor Data abstract Ultrasonic sensors are still one of the most widely used sensors in mobile robotics. A notorious problem in the use of sonar data is the lack of good spatial resolution, which typically results in a high uncertainty in the resulting map of the environment. In the paper a triangulation technique is used for filtering of data so as to obtain an improved grid map of the environment. The basic technique is described and it is outlined how it can be used for identification of natural landmarks. Olle Wijk, Patric Jensfelt, Henrik I. Christensen	ICRA	3
1997	Dynamic robot planning: cooperation through competition abstract We address scaling of the "dynamic systems" approach for robot planning to multi-agent cooperation. To accommodate this extension it is necessary to carefully consider how individual behaviors contribute to the vector field. To avoid spurious minima and related problems a competition dynamics is introduced and its stability is analyzed. A system of two cooperating agents is designed, and examples are presented to illustrate the utility of this approach. Edward W. Large, Henrik I. Christensen, Ruzena Bajcsy	ICRA	2
1997	Improving task reliability by fusion of redundant homogeneous modules using voting schemes abstract In this paper we present a technique that can help us design system components (behaviors) with reliability in mind. Our approach is similar to N-version programming. A team of functionally redundant behaviors vote for a set of possible actions. A voter then fuses the votes and selects the action which has received the maximum number of votes. We draw some design guidelines and show that with careful design, the selected action will have higher probability of success (reliability) than the reliability of each of the behaviors. A comprehensive set of experiments together with results are presented in which a team of tracking behaviors control a stereo camera head in the active vision task of smooth pursuit. The results show that the approach dramatically improves tracking performance. Paolo Pirjanian, Jeffrey A. Fayman, Henrik I. Christensen	ICRA	3
1997	Scaling the Dynamic Approach to Autonomous Path Planning: Planning Horizon Dynamics Edward W. Large, Henrik I. Christensen, Ruzena Bajcsy	IJCAI	2
1997	Theoretical methods for planning and control in mobile robotics abstract Through adaptation of theoretical techniques from control theory and computer science it becomes possible to provide well posed expert systems for the control of mobile robots. In contrast to other expert systems for mobile robotics the adapted framework enables structured design and verification of implemented systems. This in turn results in a modular system, and a system with a predictable performance. The authors describe how a behaviour based system can be controlled by a rule based expert system, where the interaction between behaviours is described in terms of a process algebra, where different processes are modelled as discrete event systems, and compositions are controlled by a supervisory control-structure. To verify the described framework experimental results obtained with a prototype system are also outlined. Henrik I. Christensen, Paolo Pirjanian	KES (1)	1
1997	Active Object Recognition Integrating Attention and Viewpoint Control Sven J. Dickinson, Henrik I. Christensen, John K. Tsotsos, Göran Olofsson	Comput. Vis. Image Underst.	2
1997	Editorial Performance characteristics of vision algorithms Henrik I. Christensen, Wolfgang Förstner	Mach. Vis. Appl.	1
1997	A Viewpoint Planning Strategy for Determining True Angles on Polyhedral Objects by Camera Alignment abstract The paper presents a viewpoint planning strategy which automatically guides a movable camera from an arbitrary position to a position where the optical axis is perpendicular to a plane spanned by any two intersecting edges on a polyhedral object, i.e., a junction. In related work it is common to use the changing length of edge segments to control such alignment, but we demonstrate the use of the apparent angle between the edge segments of the junction. Based on the control on the apparent angle we achieve robustness as well as independence of distance to the object and focal length. The strategy is able to determine the true angle of a junction with an accuracy of approximately 1/spl deg/, and align with an accuracy of approximately 6/spl deg/. Claus B. Madsen, Henrik I. Christensen	IEEE Trans. Pattern Anal. Mach. Intell.	2
1996	Using grammars for scene interpretation abstract A method that employs grammars to direct the inference process of a vision system that does interpretation of dynamic scenes is described. The system uses a set of qualitative image descriptors to drive the interpretation. The result is a 'natural language' description of scene activities. In addition the inference engine generates a set of predictions that can be used to control the interpretation strategy so as to make the processing of new images more efficient. The system has been implemented in an expert system shell to demonstrate the viability of the approach. Results on real images are reported. Henrik I. Christensen, Jiri Matas, Josef Kittler	ICIP (2)	1
1996	A system for active vision driven robotics abstract In this paper, we present an agent architecture/active vision research tool called the Active Vision Shell (AV-shell). The AV-shell can be viewed as a programming framework for expressing perception and action routines in the context of situated robotics. The AV-shelf is a powerful interactive C-shell style interface providing many capabilities important in an agent architecture such as the ability to combine perceptive capabilities of active vision with capabilities provided by other robotic devices, the ability to interact with a wide variety of active vision devices, a set of image routines and the ability to compose the routines into continuously running perception action processes. Finally, we present an application example of AV-shell. Jeffrey A. Fayman, Ehud Rivlin, Henrik I. Christensen	ICRA	3
1995	A Control Theoretical Approach to Active Vision Henrik I. Christensen, Jakob Horstmann, Torben Rasmussen	ACCV	1
1995	Discrete event modeling of visually guided behaviors Jana Kosecka, Henrik I. Christensen, Ruzena Bajcsy	Int. J. Comput. Vis.	2
1994	Qualitative tracking of 3-D objects using active contour networks abstract In this paper, we track changes in the appearance of the object as it moves from one frame to the next. At a symbolic level, an aspect graph clusters all the views of an object into a set of topologically distinct classes in terms of which surfaces of an object are visible from a given viewpoint (Koenderink and van Doom (1979). Two nodes (or aspects) in the aspect graph are connected by an arc if it is possible to directly move from a viewpoint in which the first aspect is visible to a viewpoint in which the second aspect is visible. Qualitatively, we can envision a tracking strategy which simply tracks an object as it moves from one node to another in the object's aspect graph. Although it does not provide us with accurate pose of the object, it does qualitatively describe the motion of the object without the need for a CAD representation of the object.> Sven J. Dickinson, Piotr Jasiobedzki, Göran Olofsson, Henrik I. Christensen	CVPR	4
1994	Reactive view planning for quantification of local geometry abstract We present a view point planning strategy for determining the true angle between legs of junctions in a polyhedral scene. The strategy results in a reactive visual behaviour guiding the camera towards a canonical view point producing a fronto-parallel projection of object faces. From these views the angle in the image is identical to the true angle, thus the method does not involve reconstruction. Qualitative visual events, e.g., zero-crossings in the rate-of-change of measured, apparent angle, are used to control the motion of the camera, resulting in independence of positional feedback.> Claus B. Madsen, Henrik I. Christensen	CVPR	2
1994	Active Vision: A Survey Henrik I. Christensen, Erik Granum	ECAI	1
1994	Active Object Recognition Integrating Attention and Viewpoint Control Sven J. Dickinson, Henrik I. Christensen, John K. Tsotsos, Göran Olofsson	ECCV (2)	2
1994	Determining angles with a movable observer abstract We present a view planning approach to determining angles between two-line junctions on an object. Using view planning we demonstrate an ability to determine such angles without reconstruction of 3D properties, and without using known camera displacement. The core in our approach is a two-step view planning strategy based on two simple motion patterns. The view planning is controlled using local extrema in the apparent (viewed) angle. We demonstrate the approach on real images and experiments show an accuracy in determined angle which is better than /spl plusmn/1 degrees. Claus B. Madsen, Henrik I. Christensen	ICPR (1)	2
1993	A Low-Cost Robot Camera Head abstract Active vision involving the exploitation of controllable cameras and camera heads is an area which has received increased attention over the last few years. At LIA/AUC a binocular robot camera head has been constructed for use in geometric modelling and interpretation. In this manuscript the basic design of the head is outlined and a first prototype is described in some detail. Detailed specifications for the components used are provided together with a section on lessons learned from construction and initial use of this prototype. Henrik I. Christensen	Int. J. Pattern Recognit. Artif. Intell.	1
1993	The Scale Space Aspect Graph abstract Currently the aspect graph is computed from the theoretical standpoint of perfect resolution in object shape, the viewpoint and the projected image. This means that the aspect graph may include details that an observer could never see in practice. Introducing the notion of scale into the aspect graph framework provides a mechanism for selecting a level of detail that is "large enough" to merit explicit representation. This effectively allows control over the number of nodes retained in the aspect graph. This paper introduces the concept of the scale space aspect graph, defines three different interpretations of the scale dimension, and presents a detailed example for a simple class of objects, with scale defined in terms of the spatial extent of features in the image.> David W. Eggert, Kevin W. Bowyer, Charles R. Dyer, Henrik I. Christensen, Dmitry B. Goldgof	IEEE Trans. Pattern Anal. Mach. Intell.	4
1992	The scale space aspect graph abstract Currently the aspect graph is computed under the assumption of perfect resolution in the viewpoint, the projected image, and the object shape. Visual detail is represented that an observer might never see in practice. By introducing scale into this framework, a mechanism is provided for selecting levels of detail that are large enough to merit explicit representation, effectively allowing control over the size of the aspect graph. To this end the scale space aspect graph is introduced, and an interpretation of the scale dimension in terms of the spatial extent of image features is considered. A brief example is given for polygons in a plane.> David W. Eggert, Kevin W. Bowyer, Charles R. Dyer, Henrik I. Christensen, Dmitry B. Goldgof	CVPR	4