By Topic

A minimum model adaptive control approach for a planar biped

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chee-Meng Chew ; MIT, Cambridge, MA, USA ; G. A. Pratt

Virtual model control (VMC) has previously been successfully applied to steady dynamic walking of a planar biped. This control methodology requires very low computation because it does not calculate the inverse dynamics of the biped. An adaptive control approach based on radial basis function neural networks (RBFNNs) has also been previously proposed to enhance VMC. However, such implementation is computationally intensive. We propose a simpler adaptive VMC that allows the biped to adapt to mass variations without using RBFNNs. We implement the resulting system and demonstrate the robustness of the implementation by simulating the biped walking over rolling terrain

Published in:

Intelligent Robots and Systems, 1999. IROS '99. Proceedings. 1999 IEEE/RSJ International Conference on  (Volume:3 )

Date of Conference: