Hostname: page-component-cb9f654ff-plnhv Total loading time: 0.001 Render date: 2025-08-20T04:04:26.362Z Has data issue: false hasContentIssue false
  • English
  • Français

Frontal plane algorithms for dynamic bipedal walking

Published online by Cambridge University Press:  05 January 2004

Chee-Meng Chew  and
Gill A. Pratt
Chee-Meng Chew
Affiliation:
Department of Mechanical Engineering, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260.
Gill A. Pratt
Affiliation:
F.W. Olin College of Engineering, 1735 Great Plain Ave., Needham, MA 02492–1245 (USA)
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper presents two frontal plane algorithms for 3D dynamic bipedal walking. One of which is based on the notion of symmetry and the other uses reinforcement learning algorithm to learn the lateral foot placement. The algorithms are combined with a sagittal plane algorithm and successfully applied to a simulated 3D bipedal robot to achieve level ground walking. The simulation results showed that the choice of the local control law for the stance-ankle roll joint could significantly affect the performance of the frontal plane algorithms.

Keywords

Bipedal walkingFrontal plane algorithmsControl lawStance-ankle joint roll

Information

Type
Research Article
Information
Robotica , Volume 22 , Issue 1 , January 2004 , pp. 29 - 39
Copyright
© 2004 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable