Supported Teleoperation

This work focuses on predicting the motion of a human operator by using different sensing modalities. The lab has collaborated with Honda Motor Corporation, Japan, for this project. The work uses bioelectrical signals like EMG and other sensing modalities to predict human joint mechanics continuously. This information can then be relayed as a control signal for robot teleoperation.

This work is inspired by the idea of shared control, where the human operator controls a robot remotely through varying levels of autonomy. For instance, a robotic arm can track the trajectory of human limbs and detect the intent of an operator to act. However, low-level tasks like grasping can be achieved autonomously after intent detection by relying on the sensory feedback information received by the robot from the environment.

The high-level goal of the project is to reduce the latency in robot teleoperation to facilitate a better human-robot interaction experience.

Publications

Sitole, S.P. and Sup IV, F.C. (2023) Continuous Prediction of Human Joint Mechanics using EMG Signals: A Review of Model-based and Model-free Approaches. IEEE Transactions on Medical Robotics and Bionics,5(3), 528-546.

Contributing Researchers

Soumitra Sitole
Soumitra "Sam" Sitole
Postdoctoral Researcher, MIE
Frank Sup
Frank Sup
Professor, MIE