Legged robot gait locus generation based on genetic algorithms

Xu, K; Chen, XP; Liu, W; Williams, MA

Legged robot gait locus generation based on genetic algorithms

Xu, K Chen, XP Liu, W Williams, MA

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Publication Type:: Conference Proceeding
Citation:: ACM International Conference Proceeding Series, 2006, 213 pp. 51 - 62
Issue Date:: 2006-12-01

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Field	Value	Language
dc.contributor.author	Xu, K	en_US
dc.contributor.author	Chen, XP	en_US
dc.contributor.author	Liu, W	en_US
dc.contributor.author	Williams, MA https://orcid.org/0000-0002-1047-0503	en_US
dc.date.issued	2006-12-01	en_US
dc.identifier.citation	ACM International Conference Proceeding Series, 2006, 213 pp. 51 - 62	en_US
dc.identifier.isbn	1740521307	en_US
dc.identifier.isbn	9781740521307	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17575
dc.description.abstract	Achieving an effective gait locus for legged robots is a challenging task. It is often done manually in a laborious way due to the lack of research in automatic gait locus planning. Bearing this problem in mind, this article presents a gait locus planning method using inverse kinematics while incorporating genetic algorithms. Using quadruped robots as a platform for evaluation, this method is shown to generate a good gait locus for legged robots. Copyright © held by author.	en_US
dc.relation.ispartof	ACM International Conference Proceeding Series	en_US
dc.relation.isbasedon	10.1145/1232425.1232435	en_US
dc.title	Legged robot gait locus generation based on genetic algorithms	en_US
dc.type	Conference Proceeding
utslib.citation.volume	213	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Perth, Australia	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	213	en_US

Abstract:

Achieving an effective gait locus for legged robots is a challenging task. It is often done manually in a laborious way due to the lack of research in automatic gait locus planning. Bearing this problem in mind, this article presents a gait locus planning method using inverse kinematics while incorporating genetic algorithms. Using quadruped robots as a platform for evaluation, this method is shown to generate a good gait locus for legged robots. Copyright © held by author.

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http://hdl.handle.net/10453/17575