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Operators working with robots in safety-critical domains have to make decisions under uncertainty, which remains a challenging problem for a single human operator. An open question is whether two human operators can make better decisions…

Human-Computer Interaction · Computer Science 2025-03-21 Duc-An Nguyen , Raunak Bhattacharyya , Clara Colombatto , Steve Fleming , Ingmar Posner , Nick Hawes

Remote robot manipulation with human control enables applications where safety and environmental constraints are adverse to humans (e.g. underwater, space robotics and disaster response) or the complexity of the task demands human-level…

Robotics · Computer Science 2020-11-24 Claudia Pérez-D'Arpino , Rebecca P. Khurshid , Julie A. Shah

Semi-autonomous telerobotic systems allow both humans and robots to exploit their strengths, while enabling personalized execution of a task. However, for new soft robots with degrees of freedom dissimilar to those of human operators, it is…

Teleoperation is increasingly recognized as a viable solution for deploying robots in hazardous environments. Controlling a robot to perform a complex or demanding task may overload operators resulting in poor performance. To design a robot…

Robotics · Computer Science 2024-12-10 Jiahe Pan , Jonathan Eden , Denny Oetomo , Wafa Johal

Assessing human performance in robotic scenarios such as those seen in telepresence and teleoperation has always been a challenging task. With the recent spike in mixed reality technologies and the subsequent focus by researchers, new…

Human-Computer Interaction · Computer Science 2021-03-26 Eleftherios Triantafyllidis , Zhibin Li

Employing a teleoperation system for gathering demonstrations offers the potential for more efficient learning of robot manipulation. However, teleoperating a robot arm equipped with a dexterous hand or gripper, via a teleoperation system…

Autonomous robots often encounter challenging situations where their control policies fail and an expert human operator must briefly intervene, e.g., through teleoperation. In settings where multiple robots act in separate environments, a…

Robotics · Computer Science 2020-03-10 Gokul Swamy , Siddharth Reddy , Sergey Levine , Anca D. Dragan

Teleoperation (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…

Robotics · Computer Science 2020-11-06 Sunyu Wang , Kevin Murphy , Dillan Kenney , Joao Ramos

Teleoperation of humanoid robots enables the integration of the cognitive skills and domain expertise of humans with the physical capabilities of humanoid robots. The operational versatility of humanoid robots makes them the ideal platform…

Recent advancements in robotics have increased the possibilities for integrating robotic systems into human-involved workplaces, highlighting the need to examine and optimize human-robot coordination in collaborative settings. This study…

Robotics · Computer Science 2025-11-26 Róisín Keenan , Joost C. Dessing

Due to the potentially large number of units involved, the interaction with a multi-robot system is likely to exceed the limits of the span of apprehension of any individual human operator. In previous work, we studied how this issue can be…

Robotics · Computer Science 2020-07-27 Jayam Patel , Carlo Pinciroli

In this paper, we aim to achieve a human-robot work balance by implementing shared autonomy through a web interface. Shared autonomy integrates user input with the autonomous capabilities of the robot and therefore increases the overall…

Robotics · Computer Science 2020-02-21 Yug Ajmera , Arshad Javed

Teleoperation interfaces are essential tools for enabling human control of robotic systems. Although a wide range of interfaces has been developed, a persistent gap remains between the level of performance humans can achieve through these…

Robotics · Computer Science 2026-01-21 Aliyah Smith , Monroe Kennedy

With increasing numbers of mobile robots arriving in real-world applications, more robots coexist in the same space, interact, and possibly collaborate. Methods to provide such systems with system size scalability are known, for example,…

Robotics · Computer Science 2024-05-15 Jonas Kuckling , Robin Luckey , Viktor Avrutin , Andrew Vardy , Andreagiovanni Reina , Heiko Hamann

Teleoperation of heavy machinery in industry often requires operators to be in close proximity to the plant and issue commands on a per-actuator level using joystick input devices. However, this is non-intuitive and makes achieving desired…

Robotics · Computer Science 2019-05-14 Christopher E. Mower , Wolfgang Merkt , Aled Davies , Sethu Vijayakumar

Relational networks within a team play a critical role in the performance of many real-world multi-robot systems. To successfully accomplish tasks that require cooperation and coordination, different agents (e.g., robots) necessitate…

Robotics · Computer Science 2023-10-20 Yasin Findik , Hamid Osooli , Paul Robinette , Kshitij Jerath , S. Reza Ahmadzadeh

In the field of robotics, robot teleoperation for remote or hazardous environments has become increasingly vital. A major challenge is the lag between command and action, negatively affecting operator awareness, performance, and mental…

Robotics · Computer Science 2023-10-16 Jing Du , William Vann , Tianyu Zhou , Yang Ye , Qi Zhu

Robot learning empowers the robot system with human brain-like intelligence to autonomously acquire and adapt skills through experience, enhancing flexibility and adaptability in various environments. Aimed at achieving a similar level of…

Robotics · Computer Science 2026-05-18 Yuxuan Zhao , Yuanchen Tang , Jindi Zhang , Hongyu Yu

Shared control in teleoperation leverages both human and robot's strengths and has demonstrated great advantages of reducing the difficulties in teleoperating a robot and increasing the task performance. One fundamental question in shared…

Robotics · Computer Science 2020-03-12 Songpo Li , Michael Bowman , Xiaoli Zhang

Learning collaborative behaviors is essential for multi-agent systems. Traditionally, multi-agent reinforcement learning solves this implicitly through a joint reward and centralized observations, assuming collaborative behavior will…

Robotics · Computer Science 2025-02-27 Zhengran Ji , Lingyu Zhang , Paul Sajda , Boyuan Chen
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