Extending equilibria to periodic orbits for walkers using continuation methods

Nelson Rosa, Kevin M. Lynch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We present a strategy for generating period-one, open-loop walking gaits for multi-degree-of-freedom, planar biped walkers. Our approach uses equilibria of the dynamics as templates, which we connect to a family of period-one walking motions using numerical continuation methods. We define a gait as a fixed point of the walker's hybrid dynamics which resides in a state-time-control space consisting of the robot's post-impact state, switching time (the time at which the swing leg impacts the ground), and a finite set of design or control parameters. We demonstrate our approach on several physicallysymmetric biped walkers. In particular, we prove that our approach reduces the search space for an initial gait in the state-time-control space to a one-dimensional search in switching time. We show that we can generates periodic motion without resorting to splines or reference trajectories. Finally, we compare our method to generating gaits with virtual holonomic constraints.

Original languageEnglish (US)
Title of host publicationIROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3661-3667
Number of pages7
ISBN (Electronic)9781479969340
DOIs
StatePublished - Oct 31 2014
Event2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
Duration: Sep 14 2014Sep 18 2014

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
CountryUnited States
CityChicago
Period9/14/149/18/14

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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