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Hybrid System Identification via Switched System Optimal Control for Bipedal Robotic Walking

  • Ram VasudevanEmail author
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 100)

Abstract

While the goal of robotic bipedal walking to date has been the development of anthropomorphic gait, the community as a whole has been unable to agree upon an appropriate model to generate such gait. In this paper, we describe a method to segment human walking data in order to generate a robotic model capable of human-like walking. Generating the model requires the determination of the sequence of contact point enforcements which requires solving a combinatorial scheduling problem. We resolve this problem by transforming the detection of contact point enforcements into a constrained switched system optimal control problem for which we develop a provably convergent algorithm. We conclude the paper by illustrating the performance of the algorithm on identifying a model for robotic bipedal walking.

Keywords

Contact Point Optimal Control Problem Bipedal Robot Optimal Control Scheme Unilateral Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

I would like to thank Sam Burden for the many conversations on system identification, Humberto Gonzalez and Maryam Kamgarpour for their help with the development of the switched system optimal control algorithm, Ryan Sinnet for his help with robotic model considered in the Application Section. I am also grateful to Aaron Ames for the many insightful discussions on bipedal walking and system identification and Ruzena Bajcsy for her willingness to try to solve hard problems. This research is supported in part by NSF Awards CCR-0325274, CNS-0953823, ECCS-0931437, IIS-0703787, IIS-0724681, IIS-0840399 and NHARP Award 000512-0184-2009.

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of MichiganAnn ArborUSA

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