Optical flow aided motion estimation for legged locomotion

Singh, SPN; Csonka, PJ; Waldron, KJ

Optical flow aided motion estimation for legged locomotion

Singh, SPN Csonka, PJ Waldron, KJ

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2006, pp. 1738 - 1743
Issue Date:: 2006-12-01

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Field	Value	Language
dc.contributor.author	Singh, SPN	en_US
dc.contributor.author	Csonka, PJ	en_US
dc.contributor.author	Waldron, KJ https://orcid.org/0000-0002-7910-4907	en_US
dc.date.issued	2006-12-01	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2006, pp. 1738 - 1743	en_US
dc.identifier.isbn	142440259X	en_US
dc.identifier.isbn	9781424402595	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11948
dc.description.abstract	Dynamic legged locomotion entails navigating terrain at high speed. The impact shocks from rapid footfalls, pivotal for such mobility, introduce large impulses that saturate motion measurement. A biomimetic approach is presented in which visual information, in the form of optical flow, complements information from inertial sensors. The motion is then determined using a two-phase Hybrid Extended Kalman Filter. Experimentation in determining attitudes on a robotic leg platform shows a reduction in drift over inertial approaches and in delay over visual approaches. In tests with 6g impulses, pose was recovered within 5 deg rms with angular rate errors limited to 10 deg/sec at frequencies up to 250 Hz. © 2006 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2006.282134	en_US
dc.title	Optical flow aided motion estimation for legged locomotion	en_US
dc.type	Conference Proceeding
utslib.for	091399 Mechanical Engineering not elsewhere classified	en_US
utslib.for	091303 Autonomous Vehicles	en_US
utslib.for	091302 Automation and Control Engineering	en_US
dc.location.activity	Beijing, China	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
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Dynamic legged locomotion entails navigating terrain at high speed. The impact shocks from rapid footfalls, pivotal for such mobility, introduce large impulses that saturate motion measurement. A biomimetic approach is presented in which visual information, in the form of optical flow, complements information from inertial sensors. The motion is then determined using a two-phase Hybrid Extended Kalman Filter. Experimentation in determining attitudes on a robotic leg platform shows a reduction in drift over inertial approaches and in delay over visual approaches. In tests with 6g impulses, pose was recovered within 5 deg rms with angular rate errors limited to 10 deg/sec at frequencies up to 250 Hz. © 2006 IEEE.

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http://hdl.handle.net/10453/11948