The University of Southampton
University of Southampton Institutional Repository

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
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
Tanakitkorn, Kantapon
d5301173-f805-4c0e-9610-48b4996a4508
Wilson, P.A.
8307fa11-5d5e-47f6-9961-9d43767afa00
Turnock, S.R.
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Phillips, A.B.
f565b1da-6881-4e2a-8729-c082b869028f
Tanakitkorn, Kantapon
d5301173-f805-4c0e-9610-48b4996a4508
Wilson, P.A.
8307fa11-5d5e-47f6-9961-9d43767afa00
Turnock, S.R.
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Phillips, A.B.
f565b1da-6881-4e2a-8729-c082b869028f

Tanakitkorn, Kantapon, Wilson, P.A., Turnock, S.R. and Phillips, A.B. (2014) Grid-based GA path planning with improved cost function for an over-actuated hover-capable AUV. AUV 2014, Mississippi, United States. 05 - 08 Oct 2014.

Record type: 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

Text
AUV2014_GA.pdf - Other
Download (1MB)

More information

Published date: 19 August 2014
Venue - Dates: AUV 2014, Mississippi, United States, 2014-10-05 - 2014-10-08
Organisations: National Oceanography Centre, Fluid Structure Interactions Group

Identifiers

Local EPrints ID: 368403
URI: http://eprints.soton.ac.uk/id/eprint/368403
PURE UUID: 9bf1cd34-1e77-4ffa-a762-ad7b928cc0c3
ORCID for P.A. Wilson: ORCID iD orcid.org/0000-0002-6939-682X
ORCID for S.R. Turnock: ORCID iD orcid.org/0000-0001-6288-0400
ORCID for A.B. Phillips: ORCID iD orcid.org/0000-0003-3234-8506

Catalogue record

Date deposited: 18 Sep 2014 10:59
Last modified: 12 Dec 2021 03:29

Export record

Contributors

Author: Kantapon Tanakitkorn
Author: P.A. Wilson ORCID iD
Author: S.R. Turnock ORCID iD
Author: A.B. Phillips ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×