Boundedness approach to gait planning for the flexible linear inverted pendulum model

Leonardo Lanari, Oliver Urbann, Seth Hutchinson, Ingmar Schwarz

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

Abstract

In this paper, we solve the gait planning problem by using the Flexible LIP model, which has been shown to be more realistic w.r.t. the LIP for cost-effective or compliant biped robots for gait generation. We extend a stable inversion approach to obtain bounded Center of Mass (CoM) reference trajectories and show several advantages compared to preview control: avoidance of numerical integration, lower computation time, exact tracking of reference Zero Moment Point (ZMP) trajectories, and the ability to come to an immediate stop.

Original languageEnglish (US)
Title of host publicationRoboCup 2016
Subtitle of host publicationRobot World Cup XX
EditorsRaymond Sheh, Daniel D. Lee, Sven Behnke, Sanem Sariel
PublisherSpringer-Verlag Berlin Heidelberg
Pages58-70
Number of pages13
ISBN (Print)9783319687919
DOIs
StatePublished - Jan 1 2017
Event20th Annual RoboCup International Symposium, 2016 - Leipzig, Germany
Duration: Jun 30 2016Jul 4 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9776 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other20th Annual RoboCup International Symposium, 2016
CountryGermany
CityLeipzig
Period6/30/167/4/16

Keywords

  • Boundedness
  • LIPM
  • Preview control
  • Stable inversion

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lanari, L., Urbann, O., Hutchinson, S., & Schwarz, I. (2017). Boundedness approach to gait planning for the flexible linear inverted pendulum model. In R. Sheh, D. D. Lee, S. Behnke, & S. Sariel (Eds.), RoboCup 2016: Robot World Cup XX (pp. 58-70). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9776 LNAI). Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-319-68792-6_5