Biomimetic adaptive impedance control in physical Human Robot Interaction

Human Robot Interaction has become a key point in the development of new robotic interfaces and controllers. In traditional control schemes for teleoperation, master devices are unaware of the user's arm dynamic characteristics, as well as of the complex motor control strategies adopted to perform the task. In this work, we propose a novel impedance controller to regulate the master device's dynamic properties based on the estimation of user's arm stiffness, with the aim of improving shared task performance. We developed a virtual planar reaching task, and we evaluated arm end-point stiffness's main axis changes in magnitude and direction using a non disruptive offline musculoskeletal model-based algorithm. Based on the stiffness modulation, the biomimetic variable impedance controller to adapt the master device's damping matrix. The direction of maximal damping was aligned with the estimated direction of maximal stiffness (Enhancing field), or to the perpendicular to the stiffness main axis (Isotropic field). The task performances under the biomimetic impedance controllers were tested and compared with the null damping condition. The results showed an increase in task performance, in terms of positional error and overshoots, with both biomimetic controllers. The analysis proved the potentiality of the biomimetic impedance modulation controller in terms of execution accuracy.