Sep 17, 2026 · cs.ROJ/K move · Enter open · S save
Lewei Feng, Qi Chen, Wenshuo Wang, Xianghao Meng+5
School of Mechanical Engineering, Beijing Institute of Technology, China · Faculty of Marine Science and Technology, Beijing Institute of Technology, China · Department of Civil and Environmental Engineering, University of Auckland, New Zealand · School of Artificial Intelligence, University of Science and Technology Beijing, China · Department of Computer Science, Tsinghua University, China
Teleoperation, a human-in-the-loop control scheme, allows a human operator to remotely command and guide a mobile robot to navigate in off-road environments, yet fluent and user-friendly tele-navigation requires an alignment of traversability evaluation between human and robot. In the teleoperation system, the human operator typically utilizes off-site incomplete and delayed feedback via a human-machine interface to make a judgment of traversability, while the robot makes such an evaluation based on in situ onboard sensory information, which could cause divergent traversability estimation and thus generate mismatched decisions and actions. Existing approaches for traversability modeling, estimation, and prediction are mainly derived from the view of robots, i.e., robot-centric, and are practically suitable for fully autonomous mobile robots, but neglect the influence of human operators. To address this problem, this paper extends the concept of traversability from robot-centric to human-centric by accounting for the operator's cognitive states, such as attention, workload, and risk tolerance or awareness, termed tele-traversability. We first revisit the definitions and roles of traversability in robotics and then extend them to teleoperation settings. Finally, we highlight future trends and open challenges of tele-traversability toward human-centric teleoperation systems.