Adaptive Ankle Torque Control for Bipedal Humanoid Walking on Surfaces with Unknown Horizontal and Vertical Motion

TL;DR

This paper presents an adaptive ankle torque control method for stable bipedal walking on unknown, moving surfaces, addressing hybrid dynamics and estimation challenges with a novel step-length planner and simulation validation.

Contribution

It introduces an adaptive ankle torque controller combined with a step-length planner to handle uncertainties in surface motion and robot dynamics during walking.

Findings

Effective stability and tracking demonstrated in simulations.

Outperforms baseline controllers under unknown disturbances.

Ensures continuous error system for hybrid dynamics.

Abstract

Achieving stable bipedal walking on surfaces with unknown motion remains a challenging control problem due to the hybrid, time-varying, partially unknown dynamics of the robot and the difficulty of accurate state and surface motion estimation. Surface motion imposes uncertainty on both system parameters and non-homogeneous disturbance in the walking robot dynamics. In this paper, we design an adaptive ankle torque controller to simultaneously address these two uncertainties and propose a step-length planner to minimize the required control torque. Typically, an adaptive controller is used for a continuous system. To apply adaptive control on a hybrid system such as a walking robot, an intermediate command profile is introduced to ensure a continuous error system. Simulations on a planar bipedal robot, along with comparisons against a baseline controller, demonstrate that the proposed approach effectively ensures stable walking and accurate tracking under unknown, time-varying disturbances.