Bimanual Telemanipulation with Force and Haptic Feedback and Predictive Limit Avoidance
This work addresses the problem of enhancing situation awareness and efficiency in teleoperation for applications like remote or hazardous environments, though it appears incremental as it builds on existing telemanipulation concepts with specific improvements.
The authors tackled the challenge of providing sufficient feedback and control interfaces in robotic teleoperation by developing a bimanual telemanipulation system with force and haptic feedback and a predictive limit avoidance model, which was evaluated in lab experiments and a user study with untrained operators.
Robotic teleoperation is a key technology for a wide variety of applications. It allows sending robots instead of humans in remote, possibly dangerous locations while still using the human brain with its enormous knowledge and creativity, especially for solving unexpected problems. A main challenge in teleoperation consists of providing enough feedback to the human operator for situation awareness and thus create full immersion, as well as offering the operator suitable control interfaces to achieve efficient and robust task fulfillment. We present a bimanual telemanipulation system consisting of an anthropomorphic avatar robot and an operator station providing force and haptic feedback to the human operator. The avatar arms are controlled in Cartesian space with a 1:1 mapping of the operator movements. The measured forces and torques on the avatar side are haptically displayed directly to the operator. We developed a predictive avatar model for limit avoidance which runs on the operator side, ensuring low latency. Only off-the-shelf components were used to build the system. It is evaluated in lab experiments and by untrained operators in a small user study.