The haptic-assisted user/robot-shared telemicromanipulation we propose uses learning different skill levels to improve operability. This research is expected to enhance teleoperation through haptic guidance based on a virtual fixture. Haptic guidance in the noncontact phase and novel feedback in the contact phase are integrated into a manipulation strategy to realize the haptic-assisted telemanipulation. We tested our proposed algorithms on a single-master multi-slave telemicromanipulation system using the task of improving user operability for user/robot-shared control. Pick-and-place experiments using salmon roe and styrene block model verify the feasibility of our haptic-assisted manipulation.
Modeling and analysis of driver behaviour under shared control through weighted visual and haptic guidance
