EDBT 2026 Demo / reviewers in the wild / expert
Kevin Murphy 0006
dblp:83/86-6
· DBLP profile ↗
4ranked-venue papers
1as first author
4since 2021 · last 2024
0000-0001-6396-7989ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 1 first-author · 4 since 2021Systems, architecture and hardware · 4 · 1 first-author · 4 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Cooperative Modular Manipulation with Numerous Cable-Driven Robots for Assistive Construction and Gap CrossingabstractSoldiers in the field often need to cross negative obstacles, such as rivers or canyons, to reach goals or safety. Military gap crossing involves on-site temporary bridges construction. However, this procedure is conducted with dangerous, time and labor intensive operations, and specialized machinery. We envision a scalable robotic solution inspired by advancements in force-controlled and Cable-Driven Parallel Robots (CDPRs); this solution can address the challenges inherent in this transportation problem, achieving fast, efficient, and safe deployment and field operations. We introduce the embodied vision in Co3MaNDR, a solution to the military gap crossing problem, a distributed robot consisting of several modules simultaneously pulling on a central payload, controlling the cables’ tensions to achieve complex objectives, such as precise trajectory tracking or force amplification. Hardware experiments demonstrate teleoperation of a payload, trajectory following, and the sensing and amplification of operators’ applied physical forces during slow operations. An operator was shown to manipulate a 27.2 kg (60 lb) payload with an average force utilization of 14.5% of its weight. Results indicate that the system can be scaled up to heavier payloads without compromising performance or introducing superfluous complexity. This research lays a foundation to expand CDPR technology to uncoordinated and unstable mobile platforms in unknown environments. Kevin Murphy 0006, Joao C. V. Soares, Justin K. Yim, Dustin Nottage, Ahmet Soylemezoglu, João Ramos 0004 |
IROS | 1 |
| 2022 | Hands-free Telelocomotion of a Wheeled HumanoidabstractRobotic systems capable of Dynamic Mobile Manipulation (DMM) tasks combine dynamic manipulation and locomotion and could facilitate dangerous or physically demanding labor. For instance, firefighter humanoid robots could leverage their body by leaning against collapsed building rubble to push it aside. Here we introduce a teleoperation system that targets the realization of these tasks using human's whole-body motor skills. We describe a new wheeled humanoid platform, SATYRR, and a novel hands-free teleoperation architecture using a whole-body Human Machine Interface (HMI). This system enables telelocomotion of the humanoid robot using the operator's body motion, freeing their arms for manipulation tasks. In this study we evaluate the efficacy of the proposed system on hardware, and explore the control of SATYRR using two teleoperation mappings that map the operators body pitch and yaw to the robot's velocity or acceleration. Through experiments and user feedback we showcase our preliminary findings of the pilot-system response. Results suggest that the HMI is capable of effectively telelocomoting SATYRR, that pilot preferences should dictate the appropriate motion mapping and gains, and finally that the pilot can better learn to control the system over time. This study represents a fundamental step towards the realization of combined manipulation and locomotion via teleoperation. Amartya Purushottam, Yeongtae Jung, Kevin Murphy 0006, Donghoon Baek, João Ramos 0004 |
IROS | 3 |
| 2021 | A Comparison Between Joint Space and Task Space Mappings for Dynamic Teleoperation of an Anthropomorphic Robotic Arm in Reaction TestsabstractTeleoperation—i.e., controlling a robot with human motion—proves promising in enabling a humanoid robot to move as dynamically as a human. But how to map human motion to a humanoid robot matters because a human and a humanoid robot rarely have identical topologies and dimensions. This work presents an experimental study that utilizes reaction tests to compare joint space and task space mappings for dynamic teleoperation of an anthropomorphic robotic arm that possesses human-level dynamic motion capabilities. The experimental results suggest that the robot achieved similar and, in some cases, human-level dynamic performances with both mappings for the six participating human subjects. All subjects became proficient at teleoperating the robot with both mappings after practice, despite that the subjects and the robot differed in size and link length ratio and that the teleoperation required the subjects to move unintuitively. Yet, most subjects developed their teleoperation proficiencies more quickly with task space mapping than with joint space mapping after similar amounts of practice. This study also indicates the potential values of three-dimensional task space mapping, a teleoperation training simulator, and force feedback to the human pilot for intuitive and dynamic teleoperation of a humanoid robot’s arms. Sunyu Wang 0001, Kevin Murphy 0006, Dillan Kenney, João Ramos 0004 |
ICRA | 2 |
| 2021 | HOPPY: An Open-source Kit for Education with Dynamic Legged RobotsabstractThis paper introduces HOPPY, an open-source, low-cost, robust, and modular kit for robotics education. The robot dynamically hops around a rotating gantry with a fixed base. The kit is intended to lower the entry barrier for studying dynamic robots and legged locomotion with real systems. It bridges the theoretical content of fundamental robotic courses with real dynamic robots by facilitating and guiding the software and hardware integration. This paper describes the topics which can be studied using the kit, lists its components, discusses preferred practices for implementation, presents results from experiments with the simulator and the real system, and suggests further improvements. A simple heuristic-based controller is described to achieve velocities up to 1.7m/s, navigate small objects, and mitigate external disturbances when the robot is aided by a counterweight. HOPPY was utilized as the subject of a semester-long project for the Robot Dynamics and Control course at the University of Illinois at Urbana-Champaign. The positive feedback from the students and instructors about the hands-on activities during the course motivates us to share this kit and continue improving it in the future. João Ramos 0004, Yanran Ding, Youngwoo Sim 0001, Kevin Murphy 0006, Daniel Block |
IROS | 4 |