Expertise Anywhere: Navigating High Latency in Haptic Teleoperation

Abstract

This thesis explores the challenge of achieving haptic bilateral teleoperation across long distances, focusing on enhancing Model Mediated Teleoperation (MMT) to support dynamic environments under high network latency. Instead of striving for perfect model alignment, we acknowledge the inevitable mismatch between the remote environment and its model at the operator. We suggest a set of design considerations and a complementary framework to make operator intent a key factor in MMT solution development. By developing a system where a user can control a remote robot arm to draw on a moving whiteboard using a novel position-altering scheme that attempts to prioritize operator intent, we apply the framework to minimize the impact of network latency on user experience. Our findings reveal that the implemented position-altering scheme significantly reduces the effects of network delays on drawing accuracy, and a user study confirms that force feedback delays are more critical to user satisfaction than visual feedback delays. The results suggest that satisfactory teleopera-tion performance can be achieved with network latency up to 50 ms, challenging the conventional 10 ms requirement. This research provides design considerations, a comprehensive framework with a position-altering policy, and an open-source software package for advancing haptic teleop-eration technologies.