Bracing for Impact: Robust Humanoid Push Recovery and Locomotion with Reduced Order Models
For humanoid robotics researchers, this work provides a practical method to improve push recovery by using environmental contact, though it is an incremental extension of existing control techniques.
The paper presents a unified framework for humanoid walking control and push recovery that uses arms to brace against walls, combining SRB-MPC with HLIP dynamics. In simulation, the robot recovers from pushes up to 100N for 0.2s while walking at 0.5m/s, outperforming HLIP alone.
Push recovery during locomotion will facilitate the deployment of humanoid robots in human-centered environments. In this paper, we present a unified framework for walking control and push recovery for humanoid robots, leveraging the arms for push recovery while dynamically walking. The key innovation is to use the environment, such as walls, to facilitate push recovery by combining Single Rigid Body model predictive control (SRB-MPC) with Hybrid Linear Inverted Pendulum (HLIP) dynamics to enable robust locomotion, push detection, and recovery by utilizing the robot's arms to brace against such walls and dynamically adjusting the desired contact forces and stepping patterns. Extensive simulation results on a humanoid robot demonstrate improved perturbation rejection and tracking performance compared to HLIP alone, with the robot able to recover from pushes up to 100N for 0.2s while walking at commanded speeds up to 0.5m/s. Robustness is further validated in scenarios with angled walls and multi-directional pushes.