Optimal search for multiple targets in a built environment

Lau, H; Huang, S; Dissanayake, G

Optimal search for multiple targets in a built environment

Lau, H Huang, S

Dissanayake, G

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Publication Type:: Conference Proceeding
Citation:: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, 2005, pp. 228 - 233
Issue Date:: 2005-12-01

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Field	Value	Language
dc.contributor.author	Lau, H	en_US
dc.contributor.author	Huang, S https://orcid.org/0000-0002-6124-4178	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2005-12-01	en_US
dc.identifier.citation	2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, 2005, pp. 228 - 233	en_US
dc.identifier.isbn	0780389123	en_US
dc.identifier.isbn	9780780389120	en_US
dc.identifier.uri	http://hdl.handle.net/10453/3023
dc.description.abstract	The main contribution of this paper is an algorithm for autonomous search that minimizes the expected time for detecting multiple targets present in a known built environment. The proposed technique makes use of the probability distribution of the target(s) in the environment, thereby making it feasible to incorporate any additional information, known a-priori or acquired while the search is taking place, into the search strategy. The environment is divided into a set of distinct regions and an adjacency matrix is used to describe the connections between them. The costs of searching any of the regions as well as the cost of travel between them can be arbitrarily specified. The search strategy is derived using a dynamic programming algorithm. The effectiveness of the algorithm is illustrated using an example based on the search of an office environment. An analysis of the computational complexity is also presented. © 2005 IEEE.	en_US
dc.relation.ispartof	2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS	en_US
dc.relation.isbasedon	10.1109/IROS.2005.1544986	en_US
dc.title	Optimal search for multiple targets in a built environment	en_US
dc.type	Conference Proceeding
utslib.for	091007 Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)	en_US
utslib.for	091303 Autonomous Vehicles	en_US
dc.location.activity	Edmonton, Canada	en_US
dc.location.activity	Edmonton, CANADA
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	open_access
pubs.publication-status	Published	en_US

Abstract:

The main contribution of this paper is an algorithm for autonomous search that minimizes the expected time for detecting multiple targets present in a known built environment. The proposed technique makes use of the probability distribution of the target(s) in the environment, thereby making it feasible to incorporate any additional information, known a-priori or acquired while the search is taking place, into the search strategy. The environment is divided into a set of distinct regions and an adjacency matrix is used to describe the connections between them. The costs of searching any of the regions as well as the cost of travel between them can be arbitrarily specified. The search strategy is derived using a dynamic programming algorithm. The effectiveness of the algorithm is illustrated using an example based on the search of an office environment. An analysis of the computational complexity is also presented. © 2005 IEEE.

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http://hdl.handle.net/10453/3023