Balance Performance Tuning of Rider-Bikebot Interactions

Abstract

Human balance skills serve as a central role in many human-machine or human-robot interactions. In this paper, we present a human balance tuning scheme in the rider-bikebot interactions. The rider-bikebot model is first presented to capture the dynamic interactions among the rider movements, steering control, and bikebot balancing. We then present a control design to tune the stiffness and damping effects of the rider-bikebot interactions. The control is designed to guarantee the stability of the rider-bikebot interactions. Experimental results are presented to compare the control performance with that under only human control and the autonomous steering control to illustrate the balancing skill improvements.