Achieving human-level performance on real world tasks is a north star for the robotics community. We present the first learned robot agent that reaches amateur humanlevel performance in competitive table tennis. Table tennis is a physically demanding sport that takes humans years to master. We contribute (1) a hierarchical and modular policy architecture consisting of (i) low level controllers with their skill descriptors that model their capabilities and (ii) a high level controller that chooses the low level skills, (2) techniques for enabling zero-shot sim-to-real and curriculum building, including an iterative approach (train in sim, deploy in real), and (3) real time adaptation to unseen opponents. Policy performance was assessed through 29 robot vs. human matches of which the robot won 45 % (13/29). All humans were unseen players and their skill level varied from beginner to tournament level. Whilst the robot lost all matches vs. the most advanced players it won 100 % matches vs. beginners and 55 % matches vs. intermediate players, demonstrating solidly amateur humanlevel performance. Videos of the matches can be viewed here1.See sites https://google.com/view/competitive-robot-table-tennis.

People employ expressive behaviors to effectively communicate and coordinate their actions with others, such as nodding to acknowledge a person glancing at them or saying "excuse me" to pass people in a busy corridor. We would like robots to also demonstrate expressive behaviors in human-robot interaction. Prior work proposes rule-based methods that struggle to scale to new communication modalities or social situations, while data-driven methods require specialized datasets for each social situation the robot is used in. We propose to leverage the rich social context available from large language models (LLMs) and their ability to generate motion based on instructions or user preferences, to generate expressive robot motion that is adaptable and composable, building upon each other. Our approach utilizes few-shot chain-of-thought prompting to translate human language instructions into parametrized control code using the robot's available and learned skills. Through user studies and simulation experiments, we demonstrate that our approach produces behaviors that users found to be competent and easy to understand. Supplementary material can be found at https://generative-expressive-motion.github.io/.

Curiosity is increasingly being looked at to develop interactive non-human agents capable of lifelong learning, particularly in the space of Ai driven agents. However, the way a non-human agent’s mental state is described could prime expectations in human counterparts as well as alter perceptions of an agent’s behavior. We conducted an online experiment examining people’s perceptions of four levels of curious behavior portrayed by a robot agent and whether this behavior matched people’s expectations when primed to anticipate a “curious” vs. “learning” vs. “autonomous” robot agent. As curiosity increased, the ratings of the robot agent’s thinking ability also increased. This was juxtaposed by a decrease in the robot’s ratings as an effective worker and social agent. Further, we captured a unique trajectory of expectation matching showing that agents’ internal mental states should be matched with analogous external behaviors. Our findings have implications for the design and development of non-human agents that engage in learning modeled on forms of human cognition.

Abstract In a controlled lab experiment, we compared how in-person and robot-mediated communicative settings affected attitudes towards communicators and discourse phenomena related to conversational negotiation. We used a mock interview within-participants experiment design where each participant (mock interviewee) experienced both types of communication with the same experimenter (mock interviewer). Despite communicating with the same person, participants found the in-person interviewer to be more likable, more capable, more intelligent, more polite, more in control, and less awkward than the same person using a telepresence robot. Behaviorally, we did not detect differences in participants’ productions of discourse phenomena (likes, you knows, ums, uhs), laughter, or gaze. We also tested the role of communicative expectations on attitudes towards communications. We primed participants to expect that they would be talking to a person via telepresence, a “disabled” robot-person combination using telepresence, or a person in person (between-participants). We did not find differences arising from people’s expectations of the communication.

It is difficult to run long-term in-the-wild studies with mobile robots. This is partly because the robots we, as human-robot interaction (HRI) researchers, are interested in deploying prioritize expressivity over navigational capabilities, and making those robots autonomous is often not the focus of our research. One way to address these difficulties is with the Wizard of Oz (WoZ) methodology, where a researcher teleop-erates the robot during its deployment. However, the constant attention required for teleoperation limits the duration of WoZ deployments, which in-turn reduces the amount of in-the-wild data we are able to collect. Our key insight is that several types of in-the-wild mobile robot studies can be run without autonomous navigation, using wandering instead. In this paper we present and share code for our wandering robot system, which enabled Kuri, an expressive robot with limited sensor and computational capabilities, to traverse the hallways of a$28,000 \text{ ft}^{2}$floor for four days. Our system relies on informed direction selection to avoid obstacles and traverse the space, and periodic human help to charge. After presenting the outcomes from the four-day deployment, we then discuss the benefits of deploying a wandering robot, explore the types of in-the-wild studies that can be run with wandering robots, and share pointers for enabling other robots to wander. Our goal is to add wandering to the toolbox of navigation approaches HRI researchers use, particularly to run in-the-wild deployments with mobile robots.

As the Human-Robot Interaction (HRI) research field is relatively young and interdisciplinary, we spend a good deal of time and effort on communicating with each other, sharing ideas and empirical findings across disciplinary boundaries. While this practice is important and needs to continue, there is an increasingly pressing need for us to also communicate outside of this research community. I have met way too many designers, engineers, product managers, and roboticists, who tell me that they were either unaware that there was an HRI research community or that they have found our research community and have been disappointed by our work. That is unfortunate and it is fixable. Like the Human-Computer Interaction research community, we need to tackle this research-practice gap [1]. In this talk, I will make the case for why and how we might get started. There is so much to be gained by taking a Translational Science approach to HRI research. There are opportunities to do work that is grounded in real world problems, real people, and real robots. Furthermore, there are opportunities to make a difference in the design and deployment of robotic products and services right now. As just one example, in spending time studying robot deployments in service industries, at sea, and in the sky, we kept meeting professional Robot Wranglers. In many of our research projects, graduate students take on the Robot Wrangler role, which we claim will eventually disappear when the robots become “fully” autonomous. Looking across many industries, I believe that Robot Wranglers are here to stay. We could and should study them as real stakeholders and people. As HRI researchers, we have an opportunity to use our work to more directly inform the design of technologies. We can also find inspiration from the study of empirical [2]. I think it is time to roll up our sleeves and get better at communicating and working with the people who are building the future of robotics now. Publishing and presenting peer-reviewed papers is not where our work ends. We have much more work to do in translating our work in ways that will help others outside of our research community actually make use of our insights, engaging in collaborations with them, and coming back here to share and learn from stories about those experiences.

We present an accessible robot interface for telemanipulation (A-RIFT), which preserves the haptic channel partially in a zero-additional-cost interface by visual substitution of force feedback (VSFF). This work explores a gap in the literature, resulting from the focus on performance improvements in telerobotics at increasing interface costs. Unlike most telemanipulation interfaces for high-degree-of-freedom robotic systems, this one requires minimal training and can be run in a web browser under high latency conditions, using an Internet connected computer with the user's own mouse and keyboard. To evaluate the performance of the system, we ran a controlled user study (N=12) to test how different distances (local vs. remote) and VSFF (on vs. off) affect the system's usability. As expected, participants in remote conditions performed worse than those in closer proximity. Despite several participants claiming that the visual display of force feedback did not help them, our analysis of their task performance showed that operators in remote condition actually performed statistically significantly better with the visual force feedback display than without it. These results indicate a promising new interface design direction for low-cost telemanipulation.

Robots are being taught by increasingly broader populations of people who provide training data for machine learning algorithms. Many studies over the past decade have begun demonstrating reproducible robot teaching methodologies and have highlighted benefits in human-robot interaction (HRI). However, there have been few investigations about what it is like for the people teaching these robots. In this study, we consider how teaching a skill to a robot arm, performing a reaching task (as opposed to observing the robot self-learning), influences a user's emotional experience and perceptions of the robot. In a$\boldsymbol{2\mathrm{x}2}$experiment$\boldsymbol{(N=160)}$, we varied the agent's learning technique (user reinforcement feedback or robot self-learning) and expressiveness (static agent face or performance-based valence expression with head following), using an online WebGL virtual environment to enable remote HRI. Our results demonstrate that users experience significantly more trust, believability, and emotional response when teaching the robot than when observing it learning, which can be amplified with agent expressiveness.

With their ability to embody users in physically distant spaces, telepresence robots have gained popularity in environments including hospitals, schools, and offices. However, with platforms lacking in individuation and social presence, users often personalize telepresence robots with clothing and accessories to increase their recognizability and sense of embodiment. Toward understanding personalization preferences, as well as perceptions of personalized platforms, we conducted a series of five studies that investigate patterns in personalization of a telepresence robot and evaluate the impacts of common personalizations along five dimensions (robot uniqueness, humanness, pleasantness/unpleasantness, and people's willingness to interact with it). Finding a strong preference for the use of clothing and headwear in Studies 1-2 (N=52), we systematically manipulated a robot's appearance using these items and evaluated the qualitative and quantitative impacts on observer perceptions in Studies 3-4 (N=160). Observing that personalization increased perceptions of uniqueness and humanness, but also decreased positive responding, we then investigated the associations between personalization preferences and perceptions via a fifth study (N=100). Across the five studies, tensions emerged between operators' interest in using wigs and interlocutors' dislike of wigs. This result highlights a need to consider both operator and interlocutor perspectives when personalizing telepresence robots.

Remotely Operated Vehicles (ROVs) are essential to human-operated underwater expeditions in the deep sea. However, piloting an ROV to safely interact with live ecosystems is an expensive and cognitively demanding task, requiring extensive maneuvering and situational awareness. Immersive Virtual Reality (VR) Head-Mounted Displays (HMDs) could address some of these challenges. This paper investigates how VR HMDs influence operator performance through a novel telepresence system for piloting ROVs in real-time. We present an empirical user study [N=12] that examines common midwater creature capture tasks, comparing Stereoscopic-VR, Monoscopic-VR, and Desktop teleoperation conditions. Our findings indicate that Stereoscopic-VR can outperform Monoscopic-VR and Desktop ROV capture tasks, effectively doubling the efficacy of operators. We also found significant differences in presence, task load, usability, intrinsic motivation, and cybersickness. Our research points to new opportunities towards VR with ROVs.

Researchers have proposed models of curiosity as a means to drive robots to learn and adapt to their environments. While these models balance goal- and exploration-oriented actions in a mathematically principled manor, it is not understood how users perceive a robot that pursues off-task actions. Motivated by a model of curiosity based on intrinsic rewards, we conducted three online video-surveys with a total of 264 participants, evaluating a variety of curious behaviors. Our results indicate that a robot's off-task actions are perceived as expressions of curiosity, but that these actions lead to a negative impact on perceptions of the robot's competence. When the robot explains or acknowledges its deviation from the primary task, this can partially mitigate the negative effects of off-task actions.

Telepresence robots act as the remote embodiments of human operators, enabling people to stay connected to friends, family, and coworkers over lengthy physical separations. However, the factors affecting how humans can best make use of such systems are not yet well understood. This paper explores the effects of personalization and relationship closeness on telepresence via two studies. Study 1 was a between-participants experiment that investigated telepresence robot personalization. 32 pairs of friends (N = 64) participated in the study's team-building-style activities and answered questions about robot operator presence. The results unexpectedly indicated that relationship closeness influenced the interaction experience more than any other considered predictor variable. To study closeness more rigorously as the central manipulation, we conducted Study 2, a between-participants experiment with 24 pairs (N = 48) and a similar procedure. Robot operators who reported a closer relationship with their teammate felt more present in this investigation. These findings can inform the design and application of telepresence robot systems to increase a remote operator's feelings of presence via robot.

In face-to-face interaction, moving with and mimicking the body movements of communication partners has been widely demonstrated to affect interpersonal processes, including feel- ings of affiliation and closeness. In this paper, we examine effects of movement and mimicry in robot-mediated communication. Participants were instructed to get to know their partner, a confederate, who interacted with them via a telepresence robot. The robot either (a) mimicked the participant's body orientation (mimicry condition), (b) mimicked pre-recorded movements of another participant (random movement condition), or (c) did not move during the interaction (static condition). Results showed that mimicry and random movement had similar effects on participants' perceptions of similarity and closeness to their partners and that these effects depend on the participant's gender and level of self-monitoring. The findings suggest that the social movements of a telepresence robot affect interpersonal processes and that these effects are shaped by individual differences.

Robots that can leverage help from people could accomplish much more than robots that cannot. We present the results of two experiments that examine how robots can more effectively request help from people. Study 1 is a video prototype experiment (N=354), investigating the effectiveness of four linguistic politeness strategies as well as the effects of social status (equal, low), size of request (large, small), and robot familiarity (high, low) on people's willingness to help a robot. The results of this study largely support Politeness Theory and the Computers as Social Actors paradigm. Study 2 is a physical human-robot interaction experiment (N=48), examining the impact of source orientation (autonomous, single operator, multiple operators) on people's behavioral willingness to help the robot. People were nearly 50% faster to help the robot if they perceived it to be autonomous rather than being teleoperated. Implications for research design, theory, and methods are discussed.

Robots are no longer only in outer space, in factory cages, or in our imaginations. We interact with robotic agents when withdrawing cash from ATMs, driving cars with anti-lock brakes, and tuning our thermostats. In the moment of those interactions with robotic agents, we behave in ways that do not necessarily align with the rational belief that robots are just plain machines. Through a combination of controlled experiments and field studies, we will examine the ways that people make sense of robotic agents, including (1) how people interact with personal robots and (2) how people interact through telepresence robots. These observations and experiments raise questions about the psychology of human-agent interaction, particularly about issues of perceived agency and the incorporation of technologies into one's sense of self.

This tutorial is a hands-on introduction to human-centered design topics and practices for human-robot interaction. It is intended for researchers with a variety of backgrounds, particularly those with little or no prior experience in design. In the morning, participants will learn about user needs and needfinding, as ways to understand the stakeholders in research outcomes, guide the selection of participants, and as possible measures of success. We then focus on design sketching, including ways to represent objects, people and their interactions through storyboards. Design sketching is not intended to be art, rather a way to develop and build upon ideas with oneself, and quickly communicate with colleagues. In the afternoon, participants will use the tools and materials, and learn techniques for lightweight physical prototyping and improvisation. Participants will build a small paper robot (not actuated) of their own design, to practice puppeteering, explore bodily movement and prototype interactions.

Robotic telepresence systems-videoconferencing systems that allow a remote user to drive around in another location-are an emerging technology for supporting geographically-distributed teams. Thus far, many of these systems rely on affordances designed for stationary systems, such as a single, narrow-view camera to provide vision for the remote user. Teleoperation has offered some solutions to this via an augmented field-of-view, but how these solutions support task outcomes in collaborative mobile telepresence tasks has yet to be understood. To investigate this, we conducted a three condition (field-of-view: narrow (45°) vs. wide-angle (180°) vs. panoramic (360°)) between-participants controlled laboratory experiment. We asked participants (N=24) to collaborate with a confederate via a robotic telepresence system while using one of these views in a redecoration task. Our results showed that wider views supported task efficiency and fewer collisions, but were perceived as more difficult to use.

Robotic telepresence systems - videoconferencing systems that allow a remote user to drive around in another location - provide an alternative to video-mediated communications as a way of interacting over distances. These systems, which are seeing increasing use in business and medical settings, are unique in their ability to grant the remote user the ability to maneuver in a distant location. While this mobility promises increased feelings of "being there" for remote users and thus greater support for task collaboration, whether these promises are borne out, providing benefits in task performance, is unknown. To better understand the role that mobility plays in shaping the remote user's sense of presence and its potential benefits, we conducted a two-by-two (system mobility: stationary vs. mobile; task demands for mobility: low vs. high) controlled laboratory experiment. We asked participants (N=40) to collaborate in a construction task with a confederate via a robotic telepresence system. Our results showed that mobility significantly increased the remote user's feelings of presence, particularly in tasks with high mobility requirements, but decreased task performance. Our findings highlight the positive effects of mobility on feelings of "being there," while illustrating the need to design support for effective use of mobility in high-mobility tasks.

Allowing end-users to harness the full capability of general purpose robots, requires giving them powerful tools. As the functionality of these tools increase, learning how to use them becomes more challenging. In this paper we investigate the use of instructional materials to support the learnability of a Programming by Demonstration tool. We develop a system that allows users to program complex manipulation skills on a two-armed robot through a spoken dialog interface and by physically moving the robot's arms. We present a user study (N=30) in which participants are left alone with the robot and a user manual, without any prior instructions on how to program the robot. Instead, they are asked to figure it out on their own. We investigate the effect of providing users with an additional written tutorial or an instructional video. We find that videos are most effective in training the user; however, this effect might be superficial and ultimately trial-and-error plays an important role in learning to program the robot. We also find that tutorials can be problematic when the interaction has uncertainty due to speech recognition errors. Overall, the user study demonstrates the effectiveness and learnability of the our system, while providing useful feedback about the dialog design.

Robots often need to ask humans for help, for instance to complete a human component in a larger task or to recover from an unforeseen error. In this paper, we explore how robots can initiate interactions with people in order to ask for help. We discuss a study in which a robot initiated interaction with a participant by producing either an acoustic signal or a verbal greeting. Thereafter, the robot produced a gesture in order to request help in performing a task. We investigate the effect that social framing by means of a verbal greeting may have on people's attention to the robot, on their recognition of the robot's actions and intention, and on their willingness to help. The results show that social framing, in contrast to other methods for getting a person's continued attention, is effective and increases how friendly the robot appears. However, it has little influence on people's willingness to assist the robot, which rather depends on the activities people are engaged in, and on the readability of the robot's request.

Communication technologies are becoming increasingly diverse in form and functionality, making it important to identify which aspects of these technologies actually improve geographically distributed communication. Our study examines two potentially important aspects of communication technologies which appear in robot-mediated communication - physical embodiment and control of this embodiment. We studied the impact of physical embodiment and control upon interpersonal trust in a controlled laboratory experiment using three different videoconferencing settings: (1) a handheld tablet controlled by a local user, (2) an embodied system controlled by a local user, and (3) an embodied system controlled by a remote user (n = 29 dyads). We found that physical embodiment and control by the local user increased the amount of trust built between partners. These results suggest that both physical embodiment and control of the system influence interpersonal trust in mediated communication and have implications for future system designs.

As an emerging technology that enables geographically distributed work teams, mobile remote presence (MRP) systems present new opportunities for supporting effective team building and collaboration. MRP systems are physically embodied mobile videoconferencing systems that remote co-workers control. These systems allow remote users, pilots, to actively initiate conversations and to navigate throughout the local environment. To investigate ways of encouraging team-like behavior among local and remote co-workers, we conducted a 2 (visual framing: decoration vs. no decoration) x 2 (verbal framing: interdependent vs. independent performance scoring) between-participants study (n=40). We hypothesized that verbally framing the situation as interdependent and visually framing the MRP system to create a sense of self-extension would enhance group cohesion between the local and the pilot. We found that the interdependent framing was successful in producing more in-group oriented behaviors and, contrary to our predictions, visual framing of the MRP system weakened team cohesion.

Metaphors for making sense of new communication technologies are important for setting user expectations about appropriate use of the technologies. When users do not share a common metaphorical model for using these technologies, interpersonal communication breakdowns can occur. Through a set of three 8-week-long field deployments and one ongoing observation in-house, we conducted contextual inquiries around the uses of a relatively new communication technology, a mobile remote presence (MRP) system. We observed many nonhuman-like metaphors (e.g., orienting toward the system as a robot, an object) and human-like metaphors (e.g., a person, or a person with disabilities). These metaphors influence people's expectations about social norms in using the systems. We found that there is a serious risk of creating interpersonal conflict when the metaphors are mismatched between people (e.g., locals use nonhuman-like metaphors when remote pilots use human-like metaphors). We explore the implications for understanding remote pilots' rights and responsibilities and present design guidelines for MRP systems that support geographically distributed groups.

Human-in-the loop robotic systems have the potential to handle complex tasks in unstructured environments, by combining the cognitive skills of a human operator with autonomous tools and behaviors. Along these lines, we present a system for remote human-in-the-loop grasp execution. An operator uses a computer interface to visualize a physical robot and its surroundings, and a point-and-click mouse interface to command the robot. We implemented and analyzed four different strategies for performing grasping tasks, ranging from direct, real-time operator control of the end-effector pose, to autonomous motion and grasp planning that is simply adjusted or confirmed by the operator. Our controlled experiment (N=48) results indicate that people were able to successfully grasp more objects and caused fewer unwanted collisions when using the strategies with more autonomous assistance. We used an untethered robot over wireless communications, making our strategies applicable for remote, human-in-the-loop robotic applications.

Technologists have long wanted to put robots in the home, making robots truly personal and present in every aspect of our lives. It has not been clear, however, exactly what these robots should do in the home. The difficulty of tasking robots with home chores comes not only from the significant technical challenges, but also from the strong emotions and expectations people have about their home lives. In this paper, we explore one possible set of tasks a robot could perform, home organization and storage tasks. Using the technique of need finding, we interviewed a group of people regarding the reality of organization in their home; the successes, failures, family dynamics and practicalities surrounding organization. These interviews are abstracted into a set of frameworks and design implications for home robotics, which we contribute to the community as inspiration and hypotheses for future robot prototypes to test.

This year's human-robot interaction (HRI) conference focuses on "robots in the loop" and how robots are capable of enhancing the experiences of human users in everyday life and work. Telepresence robots allow operators the ability to participate in remote locations through their mobility and live bidirectional audio and video feeds. Using robotic telepresence, students with chronic illnesses are attending their regular classes, physicians are conducting virtual "home visits" for recovering patients, and remote teammates are having conversations beyond the office conference room.

Home and automation are not natural partners--one homey and the other cold. Most current automation in the home is packaged in the form of appliances. To better understand the current reality and possible future of living with other types of domestic technology, we went out into the field to conduct need finding interviews among people who have already introduced automation into their homes and kept it there--home automators. We present the lessons learned from these home automators as frameworks and implications for the values that domestic technology should support. In particular, we focus on the satisfaction and meaning that the home automators derived from their projects, especially in connecting to their homes (rather than simply controlling their homes). These results point the way toward other technologies designed for our everyday lives at home.

The Robots for Humanity project aims to enable people with severe motor impairments to interact with their own bodies and their environment through the use of an assistive mobile manipulator, thereby improving their quality of life. Assistive mobile manipulators (AMMs) are mobile robots that physically manipulate the world in order to provide assistance to people with disabilities. They present an exciting frontier for assistive technology, as they can operate away from the user, have a large dexterous workspace (due to their mobility), and not directly encumber their users. The cornerstone of this project is an ongoing, interactive design process with a quadriplegic user, Henry Evans, and his wife and primary caregiver, Jane Evans. Henry has been enabled, through the use of a PR2 robot, to scratch his own face, shave, fetch a towel from his kitchen, and hand out Halloween candy to trick-ortreating children at a local mall.

The intertwining of people and robots is at the very heart of human-robot interaction. The design of effective human-robot interactions depends not only upon an elegant and thorough engineering design for the robot's behavior, but also a clear and insightful understanding of how the human user is likely to behave toward the robot. This presents a challenge and an opportunity for engaging robotics systems research with the cognitive, behavioral, and social sciences. Without a deeper understanding of human user contexts, real user needs, and an ability to evaluate a robotic system's performance in terms of user needs, robotics runs the risk of inventing technologies for the sake of the technologies themselves. Without a thorough understanding of the state-of-the-art in robotics, user research runs the risk of generating superficial or irrelevant recommendations for robotic system design.

As geographically distributed teams become increasingly common, there are more pressing demands for communication work practices and technologies that support distributed collaboration. One set of technologies that are emerging on the commercial market is mobile remote presence (MRP) systems, physically embodied videoconferencing systems that remote workers use to drive through a workplace, communicating with locals there. Our interviews, observations, and survey results from people, who had 2-18 months of MRP use, showed how remotely-controlled mobility enabled remote workers to live and work with local coworkers almost as if they were physically there. The MRP supported informal communications and connections between distributed coworkers. We also found that the mobile embodiment of the remote worker evoked orientations toward the MRP both as a person and as a machine, leading to formation of new usage norms among remote and local coworkers.

While much of human-robot interaction research focuses upon people interacting with autonomous robots, there is also much to be gained from exploring human interpersonal interaction through robots. The current study focuses on mobile remote presence (MRP) systems as used by a population who could potentially benefit from more social connectivity and communication with remote people - older adults. Communication technologies are important for ensuring safety, independence, and social support for older adults, thereby potentially improving their quality of life and maintaining their independence [24]. However, before such technologies would be accepted and used by older adults, it is critical to understand their perceptions of the benefits, concerns, and adoption criteria for MRP systems. As such, we conducted a needs assessment with twelve volunteer participants (ages 63-88), who were given first-hand experience with both meeting a visitor via the MRP system and driving the MRP system to visit that person. The older adult participants identified benefits such as being able to see and be seen via the MRP system, reducing travel costs and hassles, and reducing social isolation. Among the concerns identified were etiquette of using the MRP, personal privacy, and overuse of the system. Some new use-cases were identified that have not yet been explored in prior work, for example, going to museums, attending live performances, and visiting friends who are hospitalized. The older adults in the current study preferred to operate the MRP themselves, rather than to be visited by others operating the MRP system. More findings are discussed in terms of their implications for design.

The animation techniques of anticipation and reaction can help create robot behaviors that are human readable such that people can figure out what the robot is doing, reasonably predict what the robot will do next, and ultimately interact with the robot in an effective way. By showing forethought before action and expressing a reaction to the task outcome (success or failure), we prototyped a set of human-robot interaction behaviors. In a 2 (forethought vs. none: between) x 2 (reaction to outcome vs. none: between) x 2 (success vs. failure task outcome: within) experiment, we tested the influences of forethought and reaction upon people's perceptions of the robot and the robot's readability. In this online video prototype experiment (N=273), we have found support for the hypothesis that perceptions of robots are influenced by robots showing forethought, the task outcome (success or failure), and showing goal-oriented reactions to those task outcomes. Implications for theory and design are discussed.

As mobile remote presence (MRP) systems become more pervasive in everyday environments such as office spaces, it is important for operators to navigate through remote locations without running into obstacles. Human-populated environments frequently change (e.g., doors open and close, furniture is moved around) and mobile remote presence systems must be able to adapt to such changes and to avoid running into obstacles. As such, we implemented an assisted teleoperation feature for a MRP system and evaluated its effectiveness with a controlled user study, focusing on both the system-oriented dimensions (e.g., autonomous assistance vs. no assistance) and human-oriented dimensions (e.g., gaming experience, locus of control, and spatial cognitive abilities) (N=24). In a systems-only analysis, we found that the assisted teleoperation helped people avoid obstacles. However, assisted teleoperation also increased time to complete an obstacle course. When human-oriented dimensions were evaluated, gaming experience and locus of control affected speed of completing the course. Implications for future research and design are discussed.

This study builds upon previous work regarding people's attitudes toward robot workers, identifying the characteristics of occupations for which people believe robots are qualified and desired. This research updates prior research and adds a new dimension of respondent expertise in the domain of robotics (N=392, which includes 134 robotics experts and 258 non-experts). We deployed a web-based survey that asked respondents about their attitudes toward robots' suitability for a variety of jobs (n=812) from the U.S. Department of Labor's O*NET occupational information database. There were different responses from experts and non-experts about what types of jobs robots: (a) could, but should not do and (b) should, but could not do. Implications for the robotics community are discussed.

In our field deployments of mobile remote presence (MRP) systems in offices, we observed that remote operators of MRPs often unintentionally spoke too loudly. This disrupted their local co-workers, who happened to be within earshot of the MRP system. To address this issue, we prototyped and empirically evaluated the effect of sidetone to help operators self regulate their speaking loudness. Sidetone is the intentional, attenuated feedback of speakers' voices to their ears while they are using a telecommunication device. In a 3-level (no sidetone vs. low sidetone vs. high sidetone) within- participants pair of experiments, people interacted with a confederate through an MRP system. The first experiment involved MRP operators using headsets with boom microphones (N=20). The second experiment involved MRP operators using loudspeakers and desktop microphones (N=14). While we detected the effects of the sidetone manipulation in our audio-visual context, the effect was attenuated in comparison to earlier audio-only studies. We hypothesize that the strong visual component of our MRP system interferes with the sidetone effect. We also found that engaging in more social tasks (e.g., a getting-to-know-you activity) and more intellectually demanding tasks (e.g., a creativity exercise) influenced how loudly people spoke. This suggests that testing such sidetone effects in the typical read-aloud setting is insufficient for generalizing to more interactive, communication tasks. We conclude that MRP application support must reach beyond the time honored audio-only technologies to solve the problem of excessive speaker loudness.

Communication mediating technologies are throwing our voices away from our bodies in situations ranging from voice conference meetings to mass presentations. Physical height is known to influence dominance in interactions between people. This study explores how audio projection technologies also influence dominance behaviors between people. In an exploratory 2 (between-participants: own voice location set spatially high vs. low) x 2 (within-participants: voice agent set spatially high vs. low) mixed-design experiment (N=64), we investigated the psychological effects of voice location upon collaborative decision-making interactions between people and voice agents. We found evidence that suggests the dominating effects of project voices' coming from above can be mitigated by hearing one's own voice projected from above.

No abstract available.

The aim of the company talks is (1)to provide a good picture about forefront technologies about robots related to human-robot interaction,and (2)to provide a opportunity to connect researchers and people from industries.Seven companies gives 8 minutes talk to present their cutting-edge technologies.Instead of having Q&A time after each presentation researchers and company presenters are Q&A time after each presentation,researchers and company presenters are encouraged to communicate with each other during reception just after company talks,where research posters will be presented.

Managing user expectations of personal robots becomes particularly challenging when the end-user just wants to know what the robot can do, and neither understands nor cares about its technical specifications. In describing what a robot can do to such an end-user, we explored the questions of (a) whether or not such users would respond to expectation setting about personal robots and, if so, (b) how such expectation setting would influence human-robot interactions and people's perceptions of the robots. Using a 2 (expectation setting: high vs. low) x 2 (robot type: Pleo vs. AIBO) between-participants experiment (N=24), we examined these questions. We found that people's initial beliefs about the robot's capabilities are indeed influenced by expectation setting tactics. Contrary to the hypotheses predicted by the Self-Fulfilling Prophecy and Confirmation Bias, we found that erring on the side of setting expectations lower rather than higher led to less disappointment and more positive appraisals of the robot's competence.

Human-Robot Interaction researchers are beginning to reach out to fields not traditionally associated with interaction research, such as the performing arts, cartooning, and animation. These collaborations offer the potential for novel insights about how to get robots and people to interact more effectively, but they also involve a number of unique challenges. This full-day workshop will offer a venue for HRI researchers and their collaborators from these diverse fields to report on their work, share insights about the collaboration process, and to help begin to define an exciting new area in HRI.

As computational agents become more sophisticated, it will frequently be necessary for the agents to disagree with users. In these cases, it might be useful for the agent to use politeness strategies that defuse the person's frustrations and preserve the human-computer relationship. One such strategy is distancing, which we implemented by spatially distancing an agent's voice from its body. In a 2 (agent disagreement: none vs. some) x 2 (agent voice location: on robotic body vs. in control box) between-participants experiment, we studied the effects of agent disagreement and agent voice location in a collaborative human-agent desert survival task (N=40). People changed their answers more often when agents disagreed with them and felt more similar to agents that always agreed with them, even when substantive content was identical. Strikingly, people felt more positively toward the disagreeing agent whose voice came from a separate control box rather than from its body; for agreement, the body-attached voice was preferred.

Though legislation is increasingly discouraging drivers from holding on to their mobile phones while talking, hands-free devices do not improve driver safety. We offer two design alternatives to improve driver safety in the contexts of voice-based user interfaces and mobile phone conversations in cars' side tones (auditory feedback used in landline phones) and location of speakers. In a 2 (side tone: present vs. not) x 2 (location of speakers: headphones vs. dashboard) between-participants experiment (N=48), we investigated the impact of these features upon driver experience and performance on a simulated mobile phone conversation while driving. Participants became more verbally engaged in the conversation when side tones were present, but also experienced more cognitive load. Participants drove more safely when voices were projected from the dashboard rather than from headphones. Implications for driver user interface design are discussed.

As robots become more pervasive, operators will develop richer relationships with them. In a 2 (robot form: humanoid vs. car) x 2 (assembler: self vs. other) between-participants experiment (N=56), participants assembled either a humanoid or car robot. Participants then used, in the context of a game, either the robot they built or a different robot. Participants showed greater extension of their self-concept into the car robot and preferred the personality of the car robot over the humanoid robot. People showed greater self extension into a robot and preferred the personality of the robot they assembled over a robot they believed to be assembled by another. Implications for the theory and design of robots and human-robot interaction are discussed.

Agentic objects are those entities that are perceived and responded to in-the-moment as if they were agentic despite the likely reflective perception that they are not agentic at all. They include autonomous robots, but also simpler systems like automatic doors, trashcans, and staplers--anything that seems to possess agency. It is well known that low-level spatiotemporal information elicits in-the-moment responses that are interpreted as perceiving mentalism [8, 17], but people reflectively believe that there is a distinction between human and non-human agents. How are we to make sense of these agentic objects?

As robots enter the everyday physical world of people, it is important that they abide by society's unspoken social rules such as respecting people's personal spaces. In this paper, we explore issues related to human personal space around robots, beginning with a review of the existing literature in human-robot interaction regarding the dimensions of people, robots, and contexts that influence human-robot interactions. We then present several research hypotheses which we tested in a controlled experiment (N = 30). Using a 2 (robotics experience vs. none: between-participants) × 2 (robot head oriented toward a participant's face vs. legs: within-participants) mixed design experiment, we explored the factors that influence proxemic behavior around robots in several situations: (1) people approaching a robot, (2) people being approached by an autonomously moving robot, and (3) people being approached by a teleoperated robot. We found that personal experience with pets and robots decreases a person's personal space around robots. In addition, when the robot's head is oriented toward the person's face, it increases the minimum comfortable distance for women, but decreases the minimum comfortable distance for men. We also found that the personality trait of agreeableness decreases personal spaces when people approach robots, while the personality trait of neuroticism and having negative attitudes toward robots increase personal spaces when robots approach people. These results have implications for both human-robot interaction theory and design.

We present a study of people's attitudes toward robot workers, identifying the characteristics of occupations for which people believe robots are qualified and desired. We deployed a web-based public-opinion survey that asked respondents (n=250) about their attitudes regarding robots' suitability for a variety of jobs (n=812) from the U.S. Department of Labor's O*NET occupational information database. We found that public opinion favors robots for jobs that require memorization, keen perceptual abilities, and service-orientation. People are preferred for occupations that require artistry, evaluation, judgment and diplomacy. In addition, we found that people will feel more positively toward robots doing jobs with people rather than in place of people.

Advances in mobile communication technologies have allowed people in more places to reach each other more conveniently than ever before. However, many mobile phone communications occur in inappropriate contexts, disturbing others in close proximity, invading personal and corporate privacy, and more broadly breaking social norms. This paper presents a telephony system that allows users to answer calls quietly and privately without speaking. The paper discusses the iterative process of design, implementation and system evaluation. The resulting system is a VoIP-based telephony system that can be immediately deployed from any phone capable of sending DTMF signals. Observations and results from inserting and evaluating this technology in real-world business contexts through two design cycles of the Touch-Talk feature are reported.

Our physical bodies play a central role in shaping human experience in the world, understandingof the world, and interactions in the world. This paper draws on theories of embodiment - from psychology, sociology, and philosophy - synthesizing five themes we believe are particularly salient for interaction design: thinking through doing, performance, visibility, risk, and thick practice. We intro-duce aspects of human embodied engagement in the world with the goal of inspiring new interaction design ap-proaches and evaluations that better integrate the physical and computational worlds.

In this paper, we demonstrate how field studies, interviews, and low-fidelity prototypes can be used to inform the design of ubiquitous computing systems for firefighters. We describe the artifacts and processes used by firefighters to assess, plan, and communicate during emergency situations, showing how accountability affects these decisions, how their current Incident Command System supports these tasks, and some drawbacks of existing solutions. These factors informed the design of a large electronic display for supporting the incident commander, the person who coordinates the overall response strategy in an emergency. Although our focus was on firefighters, our results are applicable for other aspects of emergency response as well, due to common procedures and training.

Computer system administrators are the unsung heroes of the information age, working behind the scenes to configure, maintain, and troubleshoot the computer infrastructure that underlies much of modern life. However, little can be found in the literature about the practices and problems of these highly specialized computer users. We conducted a series of field studies in large corporate data centers, observing organizations, work practices, tools, and problem-solving strategies of system administrators. We found system administrators operate within large-scale, complex environments that present significant technical, social, cognitive, and business challenges. In this paper, we describe system administrator tool use in critical, high-cost, labor-intensive work through observational, survey, and interview data. We discuss our findings concerning administrator needs for coordinating work, maintaining situation awareness, planning and rehearsing complex procedures, building tools, and supporting complicated interleaved workflows.