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...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Al-Khwarizmi College of Engineering – University of Baghdad
2013-01-01
|
| Series: | Al-Khawarizmi Engineering Journal |
| Subjects: | |
| Online Access: | http://www.iasj.net/iasj?func=fulltext&aId=69980 |
| _version_ | 1819015690052435968 |
|---|---|
| author | Mustaffa Waad Abbas Mohamed Jasim Mohamed |
| author_facet | Mustaffa Waad Abbas Mohamed Jasim Mohamed |
| author_sort | Mustaffa Waad Abbas |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-21T02:35:44Z |
| format | Article |
| id | doaj.art-e1d20e303f9043a2ba32efaa8698fcdb |
| institution | Directory Open Access Journal |
| issn | 1818-1171 |
| language | English |
| last_indexed | 2024-12-21T02:35:44Z |
| publishDate | 2013-01-01 |
| publisher | Al-Khwarizmi College of Engineering – University of Baghdad |
| record_format | Article |
| series | Al-Khawarizmi Engineering Journal |
| spelling | doaj.art-e1d20e303f9043a2ba32efaa8698fcdb2022-12-21T19:18:48ZengAl-Khwarizmi College of Engineering – University of BaghdadAl-Khawarizmi Engineering Journal1818-11712013-01-01917182Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential FieldMustaffa Waad AbbasMohamed Jasim MohamedIn 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.http://www.iasj.net/iasj?func=fulltext&aId=69980Mobile RobotLocal Path PlanningObstacles AvoidancePotential Field. |
| spellingShingle | Mustaffa Waad Abbas Mohamed Jasim Mohamed Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field Al-Khawarizmi Engineering Journal Mobile Robot Local Path Planning Obstacles Avoidance Potential Field. |
| title | 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_short | Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field |
| title_sort | obstacles avoidance for mobile robot using enhanced artificial potential field |
| topic | Mobile Robot Local Path Planning Obstacles Avoidance Potential Field. |
| url | http://www.iasj.net/iasj?func=fulltext&aId=69980 |
| work_keys_str_mv | AT mustaffawaadabbas obstaclesavoidanceformobilerobotusingenhancedartificialpotentialfield AT mohamedjasimmohamed obstaclesavoidanceformobilerobotusingenhancedartificialpotentialfield |