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Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination

This paper focuses on improving an optimization process for swarm robots using Particle Swarm Optimization (PSO) by altering the acceleration coefficient from static to dynamic. In swarm robotic, motion coordination addresses the issue of avoiding a group of robots interfere with each other in a lim...

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Main Authors: Nyiak, Tien Tang, Lim, Kit Guan, Tan, Min Keng, Yang, Soo Siang, Teo, Kenneth Tze Kin
Format: Article
Language:English
English
Published: International Journal of Simulation: Systems, Science & Technology 2020
Subjects:
TA Engineering (General). Civil engineering (General)
TL Motor vehicles. Aeronautics. Astronautics
Online Access:https://eprints.ums.edu.my/id/eprint/27579/1/Dynamic%20acceleration%20coefficient%20of%20particle%20swarm%20optimization%20in%20robotics%20motion%20coordination%20.pdf
https://eprints.ums.edu.my/id/eprint/27579/2/Dynamic%20acceleration%20coefficient%20of%20particle%20swarm%20optimization%20in%20robotics%20motion%20coordination%201.pdf
https://eprints.ums.edu.my/id/eprint/27579/
https://ijssst.info/Vol-21/No-3/paper6.pdf
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spelling my.ums.eprints.275792021-07-01T14:19:40Z https://eprints.ums.edu.my/id/eprint/27579/ Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination Nyiak, Tien Tang Lim, Kit Guan Tan, Min Keng Yang, Soo Siang Teo, Kenneth Tze Kin TA Engineering (General). Civil engineering (General) TL Motor vehicles. Aeronautics. Astronautics This paper focuses on improving an optimization process for swarm robots using Particle Swarm Optimization (PSO) by altering the acceleration coefficient from static to dynamic. In swarm robotic, motion coordination addresses the issue of avoiding a group of robots interfere with each other in a limited workspace, while achieving the global motion objective. PSO is commonly suggested in the literature to optimize path trajectory in robotic field. However, the typical PSO tends to be trapped in local optima. Therefore, a dynamic acceleration coefficient is proposed to optimize the cognitive and social coefficients of PSO in order to improve its exploration ability in seeking the global optimum solution. With this novel feature, PSO becomes less dependent on the chain of its past experience that it had explored in a certain region within the solution space. The effectiveness of the proposed method is tested on a simulated swarm robotic platform. Results show the proposed PSO with Dynamic Coefficient (DCPSO) is 1.09 seconds and 3.58 seconds faster than the typical PSO under dynamic and extreme conditions respectively. International Journal of Simulation: Systems, Science & Technology 2020 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/27579/1/Dynamic%20acceleration%20coefficient%20of%20particle%20swarm%20optimization%20in%20robotics%20motion%20coordination%20.pdf text en https://eprints.ums.edu.my/id/eprint/27579/2/Dynamic%20acceleration%20coefficient%20of%20particle%20swarm%20optimization%20in%20robotics%20motion%20coordination%201.pdf Nyiak, Tien Tang and Lim, Kit Guan and Tan, Min Keng and Yang, Soo Siang and Teo, Kenneth Tze Kin (2020) Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination. International Journal of Simulation: Systems, Science & Technology. pp. 1-10. ISSN 1473-804x https://ijssst.info/Vol-21/No-3/paper6.pdf
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic TA Engineering (General). Civil engineering (General)
TL Motor vehicles. Aeronautics. Astronautics
spellingShingle TA Engineering (General). Civil engineering (General)
TL Motor vehicles. Aeronautics. Astronautics
Nyiak, Tien Tang
Lim, Kit Guan
Tan, Min Keng
Yang, Soo Siang
Teo, Kenneth Tze Kin
Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination
description This paper focuses on improving an optimization process for swarm robots using Particle Swarm Optimization (PSO) by altering the acceleration coefficient from static to dynamic. In swarm robotic, motion coordination addresses the issue of avoiding a group of robots interfere with each other in a limited workspace, while achieving the global motion objective. PSO is commonly suggested in the literature to optimize path trajectory in robotic field. However, the typical PSO tends to be trapped in local optima. Therefore, a dynamic acceleration coefficient is proposed to optimize the cognitive and social coefficients of PSO in order to improve its exploration ability in seeking the global optimum solution. With this novel feature, PSO becomes less dependent on the chain of its past experience that it had explored in a certain region within the solution space. The effectiveness of the proposed method is tested on a simulated swarm robotic platform. Results show the proposed PSO with Dynamic Coefficient (DCPSO) is 1.09 seconds and 3.58 seconds faster than the typical PSO under dynamic and extreme conditions respectively.
format Article
author Nyiak, Tien Tang
Lim, Kit Guan
Tan, Min Keng
Yang, Soo Siang
Teo, Kenneth Tze Kin
author_facet Nyiak, Tien Tang
Lim, Kit Guan
Tan, Min Keng
Yang, Soo Siang
Teo, Kenneth Tze Kin
author_sort Nyiak, Tien Tang
title Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination
title_short Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination
title_full Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination
title_fullStr Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination
title_full_unstemmed Dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination
title_sort dynamic acceleration coefficient of particle swarm optimization in robotics motion coordination
publisher International Journal of Simulation: Systems, Science & Technology
publishDate 2020
url https://eprints.ums.edu.my/id/eprint/27579/1/Dynamic%20acceleration%20coefficient%20of%20particle%20swarm%20optimization%20in%20robotics%20motion%20coordination%20.pdf
https://eprints.ums.edu.my/id/eprint/27579/2/Dynamic%20acceleration%20coefficient%20of%20particle%20swarm%20optimization%20in%20robotics%20motion%20coordination%201.pdf
https://eprints.ums.edu.my/id/eprint/27579/
https://ijssst.info/Vol-21/No-3/paper6.pdf
_version_ 1760230640097165312
score 13.211869

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