Assessment of an ant-inspired algorithm for path planning

Sangeetha, V; Krishankumar, R; Ravichandran, KS; Gandomi, AH

Assessment of an ant-inspired algorithm for path planning

Sangeetha, V Krishankumar, R Ravichandran, KS Gandomi, AH

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Publisher:: Elsevier
Publication Type:: Chapter
Citation:: Biomimicry for Materials, Design and Habitats: Innovations and Applications, 2022, pp. 247-265
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Sangeetha, V
dc.contributor.author	Krishankumar, R
dc.contributor.author	Ravichandran, KS
dc.contributor.author	Gandomi, AH
dc.date.accessioned	2023-03-27T21:42:07Z
dc.date.available	2023-03-27T21:42:07Z
dc.date.issued	2022-01-01
dc.identifier.citation	Biomimicry for Materials, Design and Habitats: Innovations and Applications, 2022, pp. 247-265
dc.identifier.isbn	9780128210543
dc.identifier.uri	http://hdl.handle.net/10453/168617
dc.description.abstract	The demand for path planners for a variety of applications has significantly increased over the past decade. The correct choice of a distance metric will be of utmost importance for an efficient path planner. The underlying connectivity of the roadmaps produced by the planner are determined by the metrics. A study was conducted in this chapter for the proper choice of planner metrics. Five metrics from the literature were chosen and implemented in a gain-based ant colony optimization (GACO) algorithm. Results are analyzed against parameters, such as time taken, length of the path, and turn characteristics. Finally, the GACO with the chosen metric was implemented using different satellite images from the International Society for Photogrammetry and Remote Sensing and compared against existing algorithms with respect to performance.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Biomimicry for Materials, Design and Habitats: Innovations and Applications
dc.relation.isbasedon	10.1016/B978-0-12-821053-6.00016-3
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	Assessment of an ant-inspired algorithm for path planning
dc.type	Chapter
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	in_progress	*
dc.date.updated	2023-03-27T21:42:04Z
pubs.publication-status	Published

Abstract:

The demand for path planners for a variety of applications has significantly increased over the past decade. The correct choice of a distance metric will be of utmost importance for an efficient path planner. The underlying connectivity of the roadmaps produced by the planner are determined by the metrics. A study was conducted in this chapter for the proper choice of planner metrics. Five metrics from the literature were chosen and implemented in a gain-based ant colony optimization (GACO) algorithm. Results are analyzed against parameters, such as time taken, length of the path, and turn characteristics. Finally, the GACO with the chosen metric was implemented using different satellite images from the International Society for Photogrammetry and Remote Sensing and compared against existing algorithms with respect to performance.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/168617