A computationally efficient low-bandwidth method for very-large-scale mapping of road signs with multiple vehicles

Amirsadri, A; Bishop, AN; Kim, J; Trumpf, J; Petersson, L

A computationally efficient low-bandwidth method for very-large-scale mapping of road signs with multiple vehicles

Amirsadri, A Bishop, AN

Kim, J

Trumpf, J Petersson, L

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Publication Type:: Conference Proceeding
Citation:: 15th International Conference on Information Fusion, FUSION 2012, 2012, pp. 1351 - 1358
Issue Date:: 2012-10-24

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Field	Value	Language
dc.contributor.author	Amirsadri, A	en_US
dc.contributor.author	Bishop, AN https://orcid.org/0000-0001-8581-8562	en_US
dc.contributor.author	Kim, J https://orcid.org/0000-0003-4505-1103	en_US
dc.contributor.author	Trumpf, J	en_US
dc.contributor.author	Petersson, L	en_US
dc.date.issued	2012-10-24	en_US
dc.identifier.citation	15th International Conference on Information Fusion, FUSION 2012, 2012, pp. 1351 - 1358	en_US
dc.identifier.isbn	9780982443859	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121165
dc.description.abstract	This paper provides a flexible solution to the problem of building and maintaining a very-large-scale map using multiple vehicles. In particular, we consider producing a map of landmarks on the scale of thousands of kilometres in an outdoor environment. The algorithm is distributed across multiple vehicles each given the task of producing and updating a local map. The vehicles are equipped with a range of sensors and selectively communicate maps to and from a central station in a bandwidth-constraint environment. The potentially overlapping local maps are asynchronously transmitted back to a central fusion centre where a global map repository is maintained. The work addresses two of the most common issues of mapping in large-scale environments, namely, computational complexity and limited communication bandwidth. The proposed communication architecture is scalable and is capable of dealing with time-varying overlapping map sizes. A general data fusion framework based on covariance intersection is proposed to tackle the problem of redundant information propagation that is caused by communicating sub-maps of arbitrary size in the network. We also provide an analysis on the applicability of covariance intersection, as compared to the optimal approach when no cross-correlation is known between estimates from different vehicles. We further analyse the solution using a number of illustrative examples. © 2012 ISIF (Intl Society of Information Fusi).	en_US
dc.relation.ispartof	15th International Conference on Information Fusion, FUSION 2012	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	A computationally efficient low-bandwidth method for very-large-scale mapping of road signs with multiple vehicles	en_US
dc.type	Conference Proceeding
utslib.for	0906 Electrical and Electronic 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 Biomedical Engineering
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
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

This paper provides a flexible solution to the problem of building and maintaining a very-large-scale map using multiple vehicles. In particular, we consider producing a map of landmarks on the scale of thousands of kilometres in an outdoor environment. The algorithm is distributed across multiple vehicles each given the task of producing and updating a local map. The vehicles are equipped with a range of sensors and selectively communicate maps to and from a central station in a bandwidth-constraint environment. The potentially overlapping local maps are asynchronously transmitted back to a central fusion centre where a global map repository is maintained. The work addresses two of the most common issues of mapping in large-scale environments, namely, computational complexity and limited communication bandwidth. The proposed communication architecture is scalable and is capable of dealing with time-varying overlapping map sizes. A general data fusion framework based on covariance intersection is proposed to tackle the problem of redundant information propagation that is caused by communicating sub-maps of arbitrary size in the network. We also provide an analysis on the applicability of covariance intersection, as compared to the optimal approach when no cross-correlation is known between estimates from different vehicles. We further analyse the solution using a number of illustrative examples. © 2012 ISIF (Intl Society of Information Fusi).

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http://hdl.handle.net/10453/121165