Enhanced Robust Locomotion of Wheeled-Bipedal Robot via Hierarchical Optimization and Online Wheel Position Planning

In this paper, we present a novel control framework for wheeled-bipedal robots to address the challenges posed by underactuation characteristics and complex dynamics coupling. An integrated dynamic model is constructed by combining wheel dynamics and centroidal dynamics of the bipedal body based on rolling constraints and interaction force transmission, facilitating dynamic coordination between wheels and the base. Considering the non-minimum phase behavior, the online dynamic planner captures the fundamental dynamics of wheeled-bipedal robots to generate wheel position constraints, ensuring adaptation to the current center of mass (CoM) height and dynamic balance requirements. A hierarchical optimization control framework integrating model predictive control (MPC) and weighted multi-task whole-body control (WM-WBC) is proposed, taking into account the full-body dynamics, nonholonomic constraints, optimal interaction forces, and multi-task coordination. Experimental results demonstrate that the proposed method achieves precise trajectory tracking, compliant adaptation to various terrains, and exhibits superior robustness against disturbances.