Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 10, 2020 | Submitted
Report Open

Dynamic Walking: Toward Agile and Efficient Bipedal Robots

Abstract

Dynamic walking on bipedal robots has evolved from an idea in science fiction to a practical reality. This is due to continued progress in three key areas: a mathematical understanding of locomotion, the computational ability to encode this mathematics through optimization, and the hardware capable of realizing this understanding in practice. In this context, this review article outlines the end-to-end process of methods which have proven effective in the literature for achieving dynamic walking on bipedal robots. We begin by introducing mathematical models of locomotion, from reduced order models that capture essential walking behaviors to hybrid dynamical systems that encode the full order continuous dynamics along with discrete footstrike dynamics. These models form the basis for gait generation via (nonlinear) optimization problems. Finally, models and their generated gaits merge in the context of real-time control, wherein walking behaviors are translated to hardware. The concepts presented are illustrated throughout in simulation, and experimental instantiation on multiple walking platforms are highlighted to demonstrate the ability to realize dynamic walking on bipedal robots that is agile and efficient.

Additional Information

The authors would like to thank the members of AMBER Lab whom have contributed to the understanding of robotic walking summarized in this paper. Of special note are Shishir Kolathaya, Wenlong Ma, Ayonga Heried, Eric Ambrose and Matthew Powell for their work on AMBER 1, 2 and 3M and DURUS, from developing the theory, to computational methods, to experimental realization. Outside of AMBER Lab, the authors would like to thank their many collaborators. Of particular note is Jessy Grizzle and the joint efforts on HZD and CLFs. This work was supported over the years by the National Science Foundation, including awards: CPS-1239055, CNS-0953823, NRI-1526519, CNS-1136104, CPS-1544857. Other support includes projects from NASA, DARPA, SRI, and Disney. The authors are not aware of any afilliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

Attached Files

Submitted - 2010.07451.pdf

Files

2010.07451.pdf
Files (18.4 MB)
Name Size Download all
md5:2740228d362f7245e158771b6c9f8e96
18.4 MB Preview Download

Additional details

Created:
August 19, 2023
Modified:
October 20, 2023