This work focuses on predicting the motion of a human operator by using different sensing modalities. For this project, the lab has been collaborating with Honda Motor Corporation, Japan. The work focuses on using bioelectrical signals like EMG and other sensing modalities to continuously predict human joint mechanics. 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 the human limbs and detect the intent of an operator to perform an action. 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.