A strategy for efficient observation pruning in multi-objective 3D SLAM

Miro, JV; Zhou, W; Dissanayake, G

A strategy for efficient observation pruning in multi-objective 3D SLAM

Miro, JV

Zhou, W Dissanayake, G

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2011, pp. 1640 - 1646
Issue Date:: 2011-12-29

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Field	Value	Language
dc.contributor.author	Miro, JV https://orcid.org/0000-0002-0083-7797	en_US
dc.contributor.author	Zhou, W	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2011-12-29	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2011, pp. 1640 - 1646	en_US
dc.identifier.isbn	9781612844541	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32343
dc.description.abstract	An efficient automatic solution to the feature-based simultaneous localisation and mapping (SLAM) of mobile robots operating in conditions where a number of competing objectives operate simultaneously is proposed. The formulation quantitatively measures the merit of incoming data with respect to multiple priorities, automatically adjusting the amount of observations to be used in the estimation process for the best possible combined outcome. The methodology enables a selection mechanism which can efficiently exploit the observations available to the robot to best fulfil the objectives of differing tasks throughout the course of a mission, e.g. localisation, mapping, exploration, feature distribution, searching for specific objects or victims, etc. The work is particularly motivated by navigation in three-dimensional terrains, and an example considering the objectives of robot localisation and map expansion in a search and rescue environment using an RGB-D camera is utilised for discussion and results. © 2011 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2011.6048755	en_US
dc.title	A strategy for efficient observation pruning in multi-objective 3D SLAM	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	San Francisco, CA
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:

An efficient automatic solution to the feature-based simultaneous localisation and mapping (SLAM) of mobile robots operating in conditions where a number of competing objectives operate simultaneously is proposed. The formulation quantitatively measures the merit of incoming data with respect to multiple priorities, automatically adjusting the amount of observations to be used in the estimation process for the best possible combined outcome. The methodology enables a selection mechanism which can efficiently exploit the observations available to the robot to best fulfil the objectives of differing tasks throughout the course of a mission, e.g. localisation, mapping, exploration, feature distribution, searching for specific objects or victims, etc. The work is particularly motivated by navigation in three-dimensional terrains, and an example considering the objectives of robot localisation and map expansion in a search and rescue environment using an RGB-D camera is utilised for discussion and results. © 2011 IEEE.

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http://hdl.handle.net/10453/32343