🤖 AI Summary
To address post-disturbance upper-body posture instability, large recovery displacement, and delayed gait response in humanoid robot manipulation tasks, this paper proposes a hierarchical model predictive control (MPC) framework. The method comprises three layers: a mid-level module that detects incipient instability and adaptively increases step frequency in real time; a high-level nonlinear MPC that optimizes whole-body dynamics; and a low-level convex optimization layer for stable gait generation. Crucially, the framework incorporates posture-aware step-frequency adaptation to enhance dynamic stability. Under constraints ensuring upright torso orientation and minimal displacement, the approach significantly improves disturbance rejection: simulation results show a 131% increase in average maximum recoverable impulse; hardware experiments demonstrate a 125 ms reduction in gait response latency; and under a 0.2 rad external perturbation, torso posture oscillations are substantially suppressed.
📝 Abstract
Current humanoid push-recovery strategies often use whole-body motion, yet they tend to overlook posture regulation. For instance, in manipulation tasks, the upper body may need to stay upright and have minimal recovery displacement. This paper introduces a novel approach to enhancing humanoid push-recovery performance under unknown disturbances and regulating body posture by tailoring the recovery stepping strategy. We propose a hierarchical-MPC-based scheme that analyzes and detects instability in the prediction window and quickly recovers through adapting gait frequency. Our approach integrates a high-level nonlinear MPC, a posture-aware gait frequency adaptation planner, and a low-level convex locomotion MPC. The planners predict the center of mass (CoM) state trajectories that can be assessed for precursors of potential instability and posture deviation. In simulation, we demonstrate improved maximum recoverable impulse by 131% on average compared with baseline approaches. In hardware experiments, a 125 ms advancement in recovery stepping timing/reflex has been observed with the proposed approach. We also demonstrate improved push-recovery performance and minimized body attitude change under 0.2 rad.