Grid-based GA path planning with improved cost function for an over-actuated hover-capable AUV
Grid-based GA path planning with improved cost function for an over-actuated hover-capable AUV
For an AUV to perform a long-range mission with its maximum endurance, its energy consumption during transit must be kept to a minimum. This paper presents an improved cost function for a grid-based genetic algorithm (GA) path planning in 2D static environments. The proposed function consists of energy consumption terms that are estimated according to dynamics of a hover-capable AUV - notably Delphin2 AUV. It seeks for a path that requires least effort for the vehicle to move along. A simulation was written in Matlab and the outcomes of the GA with the improved cost function are compared with the ones of a GA with an optimal distance approach as well as an A approach. It is found that outcomes of an improved cost function require less energy compared with the other techniques.
Autonomous Underwater Vehicle, AUV, Delphin2, Genetic Algorithm, Path Planning
Tanakitkorn, Kantapon
d5301173-f805-4c0e-9610-48b4996a4508
Wilson, Philip A.
8307fa11-5d5e-47f6-9961-9d43767afa00
Turnock, Stephen R.
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Phillips, Alexander B.
f565b1da-6881-4e2a-8729-c082b869028f
3 March 2015
Tanakitkorn, Kantapon
d5301173-f805-4c0e-9610-48b4996a4508
Wilson, Philip A.
8307fa11-5d5e-47f6-9961-9d43767afa00
Turnock, Stephen R.
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Phillips, Alexander B.
f565b1da-6881-4e2a-8729-c082b869028f
Tanakitkorn, Kantapon, Wilson, Philip A., Turnock, Stephen R. and Phillips, Alexander B.
(2015)
Grid-based GA path planning with improved cost function for an over-actuated hover-capable AUV.
In 2014 IEEE/OES Autonomous Underwater Vehicles, AUV 2014.
IEEE..
(doi:10.1109/AUV.2014.7054426).
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Conference or Workshop Item
(Paper)
Abstract
For an AUV to perform a long-range mission with its maximum endurance, its energy consumption during transit must be kept to a minimum. This paper presents an improved cost function for a grid-based genetic algorithm (GA) path planning in 2D static environments. The proposed function consists of energy consumption terms that are estimated according to dynamics of a hover-capable AUV - notably Delphin2 AUV. It seeks for a path that requires least effort for the vehicle to move along. A simulation was written in Matlab and the outcomes of the GA with the improved cost function are compared with the ones of a GA with an optimal distance approach as well as an A approach. It is found that outcomes of an improved cost function require less energy compared with the other techniques.
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Published date: 3 March 2015
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Publisher Copyright:
© 2014 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
Venue - Dates:
2014 IEEE/OES Autonomous Underwater Vehicles, AUV 2014, , Oxford, United States, 2014-10-06 - 2014-10-09
Keywords:
Autonomous Underwater Vehicle, AUV, Delphin2, Genetic Algorithm, Path Planning
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Local EPrints ID: 449213
URI: http://eprints.soton.ac.uk/id/eprint/449213
PURE UUID: 72a591d8-6dae-4dea-9b63-181fa1ef45b0
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Date deposited: 19 May 2021 18:19
Last modified: 17 Mar 2024 03:00
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Author:
Kantapon Tanakitkorn
Author:
Alexander B. Phillips
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