A robust humanoid robot navigation algorithm with ZUPT

Li, Y; Luo, X; Ren, XT; Wang, JJ

A robust humanoid robot navigation algorithm with ZUPT

Li, Y Luo, X Ren, XT Wang, JJ

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Publication Type:: Conference Proceeding
Citation:: 2012 IEEE International Conference on Mechatronics and Automation, ICMA 2012, 2012, pp. 505 - 510
Issue Date:: 2012-10-23

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Field	Value	Language
dc.contributor.author	Li, Y	en_US
dc.contributor.author	Luo, X	en_US
dc.contributor.author	Ren, XT	en_US
dc.contributor.author	Wang, JJ https://orcid.org/0000-0002-6282-0456	en_US
dc.date.issued	2012-10-23	en_US
dc.identifier.citation	2012 IEEE International Conference on Mechatronics and Automation, ICMA 2012, 2012, pp. 505 - 510	en_US
dc.identifier.isbn	9781467312776	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32304
dc.description.abstract	This paper discusses algorithmic concepts, design and testing of a pedestrian dead reckoning (PDR) navigation system based on a low-cost inertial measurement unit (IMU) attached to a user's shoe. The algorithm uses the technique known as "Zero Velocity Update" (ZUPT) and Kalman Filter consists of 24 error states to reduce IMU errors. We propose a novel dynamic and more robust algorithm to detect the stance phases during walking. The system works well in both 2D (2-dimensional) and 3D environments. Test results show that its horizontal positioning errors are always below 0.3% of the total travelled distance, and the vertical errors are below 0.7%, even on 3D terrain. These results reach the highest position accuracy in available literature. © 2012 IEEE.	en_US
dc.relation.ispartof	2012 IEEE International Conference on Mechatronics and Automation, ICMA 2012	en_US
dc.relation.isbasedon	10.1109/ICMA.2012.6283159	en_US
dc.title	A robust humanoid robot navigation algorithm with ZUPT	en_US
dc.type	Conference Proceeding
utslib.for	0913 Mechanical Engineering	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 Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper discusses algorithmic concepts, design and testing of a pedestrian dead reckoning (PDR) navigation system based on a low-cost inertial measurement unit (IMU) attached to a user's shoe. The algorithm uses the technique known as "Zero Velocity Update" (ZUPT) and Kalman Filter consists of 24 error states to reduce IMU errors. We propose a novel dynamic and more robust algorithm to detect the stance phases during walking. The system works well in both 2D (2-dimensional) and 3D environments. Test results show that its horizontal positioning errors are always below 0.3% of the total travelled distance, and the vertical errors are below 0.7%, even on 3D terrain. These results reach the highest position accuracy in available literature. © 2012 IEEE.

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http://hdl.handle.net/10453/32304