Distributed MPC-based posture control for knee-wheeled wheel-legged robots with multi-actuation

Abstract

Wheel-legged robots (WLRs) with knee-wheel placement can switch motion mode into wheeled motion and legged motion depending on the road condition. However, in wheeled motion mode, robots are energy-efficiency and high maneuverability but struggle to handle rough terrain. To address this challenge, we propose a quarter-car model predictive controller (MPC) that utilizes both thigh and calf leg actuation to track sprung mass displacement and regulate tire force during unknown road disturbances. To overcome the high computational demands of whole-body MPC-based posture control for the entire robot, we propose a distributed MPC-based framework with inverse kinematics. Simulations, including quarter-car wheel-legged system simulation, posture tracking, braking, and steering with load transfer, were conducted to evaluate the effectiveness of our proposed control framework and the promising performance of multi-actuation involving the calf leg. The results of this paper demonstrate that our proposed approach is effective in improving the posture control and stability of knee-wheeled WLRs, particularly in rough terrain conditions.