Feedback Whole-Body Control of Wheeled Inverted Pendulum Humanoids Using Operational Space

Abstract

We present a hierarchical framework for trajectory optimization and optimal feedback whole-body control of wheeled inverted pendulum (WIP) humanoid robot. The framework extends rapidly exponentially stabilizing control Lyapunov functions (RES-CLF) to operational space for controlling WIP humanoid robots while utilizing a hierarchical framework to compute an optimal policy. The upper level of the hierarchy encodes locomotion tasks, while the lower level incorporates the full system dynamics, including manipulation tasks to be performed. The framework computes an optimal policy directly in the operational space. Thus it avoids computing inverse kinematics or inverse dynamics explicitly. The framework can handle torque and task constraints while guaranteeing exponential convergence and min-norm control from RES-CLF. The efficacy of the framework is demonstrated on 18 degrees of freedom (DoF) WIP humanoid robot, Golem Krang, and 7 DoF planar WIP humanoid robot.