Adaptive Passivity-based Hybrid Pose/Force Control for Uncertain Robots

In this work, we consider a novel adaptive hybrid pose/force control strategy for uncertain robot manipulators capable of performing interaction tasks on poorly structured environments. A unique hybrid control law, based on an orientation-dependent term, is proposed to overcome the performance degradation of the feedback system due to the presence of uncertainties in the geometric parameters of the contact surfaces. A gradient-based adaptive law, which depends on the tracking error, is designed to deal with parametric uncertainties in the robot kinematics and the stiffness of the environment. In our solution, the effect of the uncertain robot dynamics is addressed by using an adaptive dynamic control based on a cascade control strategy. The Lyapunov stability theory and the passivity paradigm are employed to carry out the stability analysis of the overall closed-loop control system. Numerical simulations are included to illustrate the performance and feasibility of the proposed methodology. Copyright (C) 2020 The Authors.