Parallel grid-based method and belief fusion Real-time cooperative non-Gaussian estimation

Furukawa, T; Tong, X; Dissanayake, G; Durrant-Whyte, HF

Parallel grid-based method and belief fusion Real-time cooperative non-Gaussian estimation

Furukawa, T Tong, X Dissanayake, G

Durrant-Whyte, HF

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Publication Type:: Conference Proceeding
Citation:: 2011 6th International Conference on Industrial and Information Systems, ICIIS 2011 - Conference Proceedings, 2011, pp. 370 - 375
Issue Date:: 2011-10-31

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Field	Value	Language
dc.contributor.author	Furukawa, T	en_US
dc.contributor.author	Tong, X	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.contributor.author	Durrant-Whyte, HF	en_US
dc.date.issued	2011-10-31	en_US
dc.identifier.citation	2011 6th International Conference on Industrial and Information Systems, ICIIS 2011 - Conference Proceedings, 2011, pp. 370 - 375	en_US
dc.identifier.isbn	9781457700354	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119700
dc.description.abstract	This paper presents a parallel grid-based method and belief fusion for real-time cooperative Bayesian estimation. The grid-based recursive Bayesian estimation (RBE) method effectively maintains the belief of objects even with no detection event but requires large computation for its prediction and correction processes as well as fusion process in cooperative estimation. In order for real-time estimation, the belief fusion proposed in the paper carries out the fusion of belief outside the RBE loop. The parallelization of the entire grid-based method and belief fusion further accelerates the RBE so that real-time estimation is possible even in highly dynamical environments. Numerical examples have first demonstrated the validity of the proposed approach through parametric studies. The proposed approach was then applied to the cooperative search by autonomous unmanned ground vehicles (UGVs), and its real-time capability has been demonstrated. © 2011 IEEE.	en_US
dc.relation.ispartof	2011 6th International Conference on Industrial and Information Systems, ICIIS 2011 - Conference Proceedings	en_US
dc.relation.isbasedon	10.1109/ICIINFS.2011.6038096	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Parallel grid-based method and belief fusion Real-time cooperative non-Gaussian estimation	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 Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

This paper presents a parallel grid-based method and belief fusion for real-time cooperative Bayesian estimation. The grid-based recursive Bayesian estimation (RBE) method effectively maintains the belief of objects even with no detection event but requires large computation for its prediction and correction processes as well as fusion process in cooperative estimation. In order for real-time estimation, the belief fusion proposed in the paper carries out the fusion of belief outside the RBE loop. The parallelization of the entire grid-based method and belief fusion further accelerates the RBE so that real-time estimation is possible even in highly dynamical environments. Numerical examples have first demonstrated the validity of the proposed approach through parametric studies. The proposed approach was then applied to the cooperative search by autonomous unmanned ground vehicles (UGVs), and its real-time capability has been demonstrated. © 2011 IEEE.

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http://hdl.handle.net/10453/119700