Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems

This paper proposes a path planning algorithm using the hybridization of the rapidly-exploring random tree (RRT) and ant colony system (ACS) algorithms. The RRT algorithm can quickly generate paths. However, the resulting path is suboptimal. Meanwhile, the ACS algorithm can generate the optimal path...

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Autores principales:	Muhammad Aria Rajasa Pohan, Bambang Riyanto Trilaksono, Sigit Puji Santosa, Arief Syaichu Rohman
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Path planning rapidly-exploring random tree ant colony system convergence speed Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/21c2470324104cb3a25a235b2477c705
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spelling	oai:doaj.org-article:21c2470324104cb3a25a235b2477c7052021-11-24T00:01:30ZPath Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems2169-353610.1109/ACCESS.2021.3127635https://doaj.org/article/21c2470324104cb3a25a235b2477c7052021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9612162/https://doaj.org/toc/2169-3536This paper proposes a path planning algorithm using the hybridization of the rapidly-exploring random tree (RRT) and ant colony system (ACS) algorithms. The RRT algorithm can quickly generate paths. However, the resulting path is suboptimal. Meanwhile, the ACS algorithm can generate the optimal path from the suboptimal previous path information. Then, the proposed algorithm will combine the advantages of RRT with the ACS algorithm. Therefore, it can reach the optimal value with a good convergence speed. We call this proposed algorithm the RRT-ACS algorithm. This study developed a new method for hybridizing the RRT and ACS algorithms for path planning problems. This hybridization process is carried out using one of the ACS principles: the pseudorandom proportional rule. The performance of the proposed algorithm with the RRT, informed RRT, RRT-connect, and informed RRT-connect algorithms is tested with several benchmark cases. The test results from benchmark case tests with known optimal values indicate that the proposed algorithm has succeeded in achieving those optimal values. Furthermore, statistical tests have also been carried out to verify whether there is a significant difference in performance between the RRT-ACS algorithm and the existing algorithms. The test and statistical analysis results show that the RRT-ACS algorithm has good performance and convergence speed. We also discuss the stability, robustness, convergence, and rapidity of the RRT-ACS algorithm. The results indicates that the RRT-ACS algorithm may be used in applications that require fast and optimal path planning algorithms such as robots and autonomous vehicles.Muhammad Aria Rajasa PohanBambang Riyanto TrilaksonoSigit Puji SantosaArief Syaichu RohmanIEEEarticlePath planningrapidly-exploring random treeant colony systemconvergence speedElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 153599-153615 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Path planning rapidly-exploring random tree ant colony system convergence speed Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Path planning rapidly-exploring random tree ant colony system convergence speed Electrical engineering. Electronics. Nuclear engineering TK1-9971 Muhammad Aria Rajasa Pohan Bambang Riyanto Trilaksono Sigit Puji Santosa Arief Syaichu Rohman Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems
description	This paper proposes a path planning algorithm using the hybridization of the rapidly-exploring random tree (RRT) and ant colony system (ACS) algorithms. The RRT algorithm can quickly generate paths. However, the resulting path is suboptimal. Meanwhile, the ACS algorithm can generate the optimal path from the suboptimal previous path information. Then, the proposed algorithm will combine the advantages of RRT with the ACS algorithm. Therefore, it can reach the optimal value with a good convergence speed. We call this proposed algorithm the RRT-ACS algorithm. This study developed a new method for hybridizing the RRT and ACS algorithms for path planning problems. This hybridization process is carried out using one of the ACS principles: the pseudorandom proportional rule. The performance of the proposed algorithm with the RRT, informed RRT, RRT-connect, and informed RRT-connect algorithms is tested with several benchmark cases. The test results from benchmark case tests with known optimal values indicate that the proposed algorithm has succeeded in achieving those optimal values. Furthermore, statistical tests have also been carried out to verify whether there is a significant difference in performance between the RRT-ACS algorithm and the existing algorithms. The test and statistical analysis results show that the RRT-ACS algorithm has good performance and convergence speed. We also discuss the stability, robustness, convergence, and rapidity of the RRT-ACS algorithm. The results indicates that the RRT-ACS algorithm may be used in applications that require fast and optimal path planning algorithms such as robots and autonomous vehicles.
format	article
author	Muhammad Aria Rajasa Pohan Bambang Riyanto Trilaksono Sigit Puji Santosa Arief Syaichu Rohman
author_facet	Muhammad Aria Rajasa Pohan Bambang Riyanto Trilaksono Sigit Puji Santosa Arief Syaichu Rohman
author_sort	Muhammad Aria Rajasa Pohan
title	Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems
title_short	Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems
title_full	Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems
title_fullStr	Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems
title_full_unstemmed	Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems
title_sort	path planning algorithm using the hybridization of the rapidly-exploring random tree and ant colony systems
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/21c2470324104cb3a25a235b2477c705
work_keys_str_mv	AT muhammadariarajasapohan pathplanningalgorithmusingthehybridizationoftherapidlyexploringrandomtreeandantcolonysystems AT bambangriyantotrilaksono pathplanningalgorithmusingthehybridizationoftherapidlyexploringrandomtreeandantcolonysystems AT sigitpujisantosa pathplanningalgorithmusingthehybridizationoftherapidlyexploringrandomtreeandantcolonysystems AT ariefsyaichurohman pathplanningalgorithmusingthehybridizationoftherapidlyexploringrandomtreeandantcolonysystems
_version_	1718416081628954624

Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems

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