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:	Mohamed Jasim Mohamed, Mustaffa Waad Abbas
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2017
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/e499fd3342b340da9049311d9361df64
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spelling	oai:doaj.org-article:e499fd3342b340da9049311d9361df642021-12-02T06:16:27ZObstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field1818-11712312-0789https://doaj.org/article/e499fd3342b340da9049311d9361df642017-12-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/160https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789In 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. Mohamed Jasim MohamedMustaffa Waad AbbasAl-Khwarizmi College of Engineering – University of BaghdadarticleMobile RobotLocal Path PlanningObstacles AvoidancePotential FieldChemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 9, Iss 1 (2017)
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 Mohamed Jasim Mohamed Mustaffa Waad Abbas 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	Mohamed Jasim Mohamed Mustaffa Waad Abbas
author_facet	Mohamed Jasim Mohamed Mustaffa Waad Abbas
author_sort	Mohamed Jasim Mohamed
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	2017
url	https://doaj.org/article/e499fd3342b340da9049311d9361df64
work_keys_str_mv	AT mohamedjasimmohamed obstaclesavoidanceformobilerobotusingenhancedartificialpotentialfield AT mustaffawaadabbas obstaclesavoidanceformobilerobotusingenhancedartificialpotentialfield
_version_	1718400024358944768

Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field

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