A dual-user teleoperated system with Virtual Fixtures for robotic surgical training

This paper proposes a teleoperated dual-user system incorporating Virtual Fixtures (VFs) that allows concurrent performance of a robotic surgical task by an expert and a trainee. In order to guide the trainee through the procedure, an adaptive VF is created in the trainee's workspace according to the motion generated by the expert who is performing the surgery at the same time. The VF gets adaptively adjusted based on the level of expertise the trainee shows during the surgery. In addition, the trainee's level of expertise is used to adaptively adjust the dual-user dominance factor in an online fashion, which gives the trainee some authority over the task based on his/her skill level. To quantify the trainee's expertise level, a performance measure is proposed, based on the force generated by the VF. Three performance measures from the literature are also used. To satisfy the desired objectives of the proposed system, an impedance-based control methodology is adopted. Stability of the closed-loop system is investigated using the small-gain theorem. A sufficient stability condition is derived that guarantees stability in the presence of time-varying communication delay. Experimental results are given to validate the performance of the system.