Robust Bipedal Locomotion: Leveraging Saltation Matrices for Gait Optimization

TL;DR

This paper introduces a novel gait optimization method for bipedal robots that incorporates saltation matrices into Hybrid Zero Dynamics, resulting in more robust walking gaits validated through simulation and hardware experiments.

Contribution

It extends Hybrid Zero Dynamics by including saltation matrices and jointly optimizing for robustness and torque, improving gait stability in bipedal robots.

Findings

Gaits generated with saltation matrices are more robust than traditional methods.

Experimental validation on hardware confirms improved robustness.

Method applied successfully on AMBER-3M and Atalante robots.

Abstract

The ability to generate robust walking gaits on bipedal robots is key to their successful realization on hardware. To this end, this work extends the method of Hybrid Zero Dynamics (HZD) -- which traditionally only accounts for locomotive stability via periodicity constraints under perfect impact events -- through the inclusion of the saltation matrix with a view toward synthesizing robust walking gaits. By jointly minimizing the norm of the extended saltation matrix and the torque of the robot directly in the gait generation process, we demonstrate that the synthesized gaits are more robust than gaits generated with either term alone; these results are shown in simulation and on hardware for the AMBER-3M planar biped and the Atalante lower-body exoskeleton (both with and without a human subject). The end result is experimental validation that combining saltation matrices with HZD methods produces more robust bipedal walking in practice.