Whole-Body Balance Control of Wheeled-Bipedal Robots for Perception-Less Terrain Adaptation

Abstract

In this paper, we present a whole-body control framework that allows a wheeled-bipedal robot to achieve robust locomotion across diverse environments without relying on terrain perception. The proposed approach consists of a whole-body motion planner and an optimization-based torque computation module. By considering the floating-base dynamics of the robot, the motion planner produces terrain-adaptive behaviors using the zero moment point (ZMP) to preserve balance without prior knowledge of the terrain. In addition, the torque computation module combines a linear quadratic regulator (LQR) with a quadratic programming (QP)-based controller. The LQR computes wheel torques to regulate the body angle while addressing the inherent non-minimum phase characteristics. Using these wheel torques, the QP-based controller allocates optimal joint torques to achieve the desired motion and maintain stable balance. The proposed framework is validated on a wheeled-bipedal robot, demonstrating locomotion over various terrains, including slopes and stairs, as well as robustness against external disturbances.