Published March 8, 2022 | Version Supplemental Material + Accepted Version
Journal Article Open

3-D Underactuated Bipedal Walking via H-LIP Based Gait Synthesis and Stepping Stabilization

  • 1. ROR icon California Institute of Technology

Abstract

In this article, we holistically present a hybrid-linear inverted pendulum (H-LIP) based approach for synthesizing and stabilizing 3-D foot-underactuated bipedal walking, with an emphasis on thorough hardware realization. The H-LIP is proposed to capture the essential components of the underactuated and actuated part of the robotic walking. The robot walking gait is then directly synthesized based on the H-LIP. We comprehensively characterize the periodic orbits of the H-LIP and provably derive the stepping stabilization via its step-to-step (S2S) dynamics, which is then utilized to approximate the S2S dynamics of the horizontal state of the center of mass of the robotic walking. The approximation facilities a H-LIP based stepping controller to provide desired step sizes to stabilize the robotic walking. By realizing the desired step sizes, the robot achieves dynamic and stable walking. The approach is fully evaluated in both simulation and experiment on the 3-D underactuated bipedal robot Cassie, which demonstrates dynamic walking behaviors with both high versatility and robustness.

Additional Information

© 2022 IEEE. Manuscript received October 29, 2021; accepted January 24, 2022. This article was recommended for publication by Associate Editor O. Stasse and Editor E. Yoshida upon evaluation of the reviewers' comments. This work was supported by Amazon Fellowship in AI and NSF under Grants 1924526 and 1923239.

Attached Files

Accepted Version - 3-D_Underactuated_Bipedal_Walking_via_H-LIP_Based_Gait_Synthesis_and_Stepping_Stabilization.pdf

Supplemental Material - supp1-3150219.mp4

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3-D_Underactuated_Bipedal_Walking_via_H-LIP_Based_Gait_Synthesis_and_Stepping_Stabilization.pdf

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Additional details

Identifiers

Eprint ID
113764
Resolver ID
CaltechAUTHORS:20220307-188394000

Funding

Amazon AI4Science Fellowship
NSF
ECCS-1924526
NSF
CMMI-1923239

Dates

Created
2022-03-08
Created from EPrint's datestamp field
Updated
2022-03-08
Created from EPrint's last_modified field