Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field

In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial pot...

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Autores principales:	Mustaffa Waad Abbas, Mohamed Jasim Mohamed
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2013
Materias:	Mobile Robot Local Path Planning Obstacles Avoidance Potential Field. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/e1d20e303f9043a2ba32efaa8698fcdb
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spelling	oai:doaj.org-article:e1d20e303f9043a2ba32efaa8698fcdb2021-12-02T07:35:48ZObstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field1818-1171https://doaj.org/article/e1d20e303f9043a2ba32efaa8698fcdb2013-01-01T00:00:00Zhttp://www.iasj.net/iasj?func=fulltext&aId=69980https://doaj.org/toc/1818-1171In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint repulsive force and the off-sensors attractive force. These secondary forces and modified primary forces are merged to overcomethe drawbacks like dead ends and U shape traps. The proposed algorithm acquirs information of unknown environment by collecting the readings of five infrared sensors with detecting range of 0.8 m. The proposed algorithm is applied on two different environments also it is compared with another algorithm. The simulation and experimental results confirm that the proposed algorithm always converges to the desired target. In addition, the performance of algorithm is well and meets the requirements in terms of saved time and computational resources.Mustaffa Waad AbbasMohamed Jasim MohamedAl-Khwarizmi College of Engineering – University of BaghdadarticleMobile RobotLocal Path PlanningObstacles AvoidancePotential Field.Chemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 9, Iss 1, Pp 71-82 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mobile Robot Local Path Planning Obstacles Avoidance Potential Field. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Mobile Robot Local Path Planning Obstacles Avoidance Potential Field. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Mustaffa Waad Abbas Mohamed Jasim Mohamed Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
description	In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint repulsive force and the off-sensors attractive force. These secondary forces and modified primary forces are merged to overcomethe drawbacks like dead ends and U shape traps. The proposed algorithm acquirs information of unknown environment by collecting the readings of five infrared sensors with detecting range of 0.8 m. The proposed algorithm is applied on two different environments also it is compared with another algorithm. The simulation and experimental results confirm that the proposed algorithm always converges to the desired target. In addition, the performance of algorithm is well and meets the requirements in terms of saved time and computational resources.
format	article
author	Mustaffa Waad Abbas Mohamed Jasim Mohamed
author_facet	Mustaffa Waad Abbas Mohamed Jasim Mohamed
author_sort	Mustaffa Waad Abbas
title	Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
title_short	Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
title_full	Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
title_fullStr	Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
title_full_unstemmed	Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
title_sort	obstacles avoidance for mobile robot using enhanced artificial potential field
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2013
url	https://doaj.org/article/e1d20e303f9043a2ba32efaa8698fcdb
work_keys_str_mv	AT mustaffawaadabbas obstaclesavoidanceformobilerobotusingenhancedartificialpotentialfield AT mohamedjasimmohamed obstaclesavoidanceformobilerobotusingenhancedartificialpotentialfield
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Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field

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