On evolving a dynamic bipedal walk using Partial Fourier Series

Haider, S; Abidi, SS; Williams, M

On evolving a dynamic bipedal walk using Partial Fourier Series

Haider, S Abidi, SS Williams, M

Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest, 2012, pp. 8 - 13
Issue Date:: 2012-01

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Field	Value	Language
dc.contributor.author	Haider, S	en_US
dc.contributor.author	Abidi, SS	en_US
dc.contributor.author	Williams, M	en_US
dc.contributor.editor	NA	en_US
dc.date	2012-12-11	en_US
dc.date.issued	2012-01	en_US
dc.identifier.citation	2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest, 2012, pp. 8 - 13	en_US
dc.identifier.isbn	978-1-4673-2125-9	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22938
dc.description.abstract	The paper presents a Partial Fourier Series (PFS) based bipedal gait in sagittal and transverse planes. The parameters of the Fourier series are optimized through Evolutionary Algorithms (EA). In addition to evolving the two walks (forward and turn) separately, the paper demonstrates how the combination of the two enables a dynamic and adjustable walk. The stability of the walk is ensured through an effective use of the built-in gyroscope sensor. The evolved walk has been tested on the simulated version of the humanoid Nao robot and is being used within the RoboCup Soccer 3D Simulation competition	en_US
dc.format	Scott McWhirter	en_US
dc.publisher	IEEE	en_US
dc.relation.ispartof	2012 IEEE International Conference on Robotics and Biomimetics, ROBIO 2012 - Conference Digest	en_US
dc.relation.ispartof	IEEE International Conference on Robotics and Biomimetics	en_US
dc.relation.isbasedon	10.1109/ROBIO.2012.6490935	en_US
dc.title	On evolving a dynamic bipedal walk using Partial Fourier Series	en_US
dc.type	Conference Proceeding
utslib.location	Piscataway, USA	en_US
utslib.location.activity	Guangzhou, China	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Guangzhou, China	en_US
dc.location.activity	Guangzhou, China
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 Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.notes	OK-SAM	en_US
pubs.place-of-publication	Piscataway, USA	en_US
pubs.start-date	2012-12-11	en_US

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Abstract:

The paper presents a Partial Fourier Series (PFS) based bipedal gait in sagittal and transverse planes. The parameters of the Fourier series are optimized through Evolutionary Algorithms (EA). In addition to evolving the two walks (forward and turn) separately, the paper demonstrates how the combination of the two enables a dynamic and adjustable walk. The stability of the walk is ensured through an effective use of the built-in gyroscope sensor. The evolved walk has been tested on the simulated version of the humanoid Nao robot and is being used within the RoboCup Soccer 3D Simulation competition

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http://hdl.handle.net/10453/22938