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
Institute of Electrical and Electronics Engineers Inc.
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.
Institute of Electrical and Electronics Engineers Inc..
(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: 08 Sep 2022 01:44
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Author:
Kantapon Tanakitkorn
Author:
Alexander B. Phillips
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