Control design and experiments for enhanced detection of stiffness variation in soft-tissue telemanipulation

Abstract

The performance index in teleoperation, transparency, is often defined as linear scaling of force and position between the master/operator and slave/environment. Motivated by applications involving soft tissue manipulation such as robotic surgery, the transparency objective is generalized to include monotonic nonlinear mappings between the master/slave position and force signals. To demonstrate the utility of such performance index, an enhanced sensitivity non-linear force mapping design is proposed that can improve stiffness discrimination in telemanipulation tasks. The mapping design is validated using adaptive psychophysics perception experiments. Lyapunov-based adaptive motion/force controllers are presented that can guarantee the convergence of position and force tracking errors in the presence of dynamic uncertainty. Given a priori known bounds on the unknown operator/environment parameters, the robust stability of the proposed teleoperation system is analyzed using an off-axis circle criterion and the Nyquist envelope of interval plant systems. Experimental results with a two-axis teleoperation setup are provided.