Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm
This paper proposes a new algorithm for multiple robots that can navigate from source to goal position in a coordinated and formative manner in an optimum path and time, efficiently avoiding static and dynamic obstacles. The proposed algorithm is applied here to track surveillance for two and four r...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-09-01
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| Series: | Ain Shams Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447921004536 |
| _version_ | 1811250556659826688 |
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| author | Madhu Sudan Das Sourish Sanyal Sanjoy Mandal |
| author_facet | Madhu Sudan Das Sourish Sanyal Sanjoy Mandal |
| author_sort | Madhu Sudan Das |
| collection | DOAJ |
| description | This paper proposes a new algorithm for multiple robots that can navigate from source to goal position in a coordinated and formative manner in an optimum path and time, efficiently avoiding static and dynamic obstacles. The proposed algorithm is applied here to track surveillance for two and four robots from starting point to the goal point in an obstacle environment without collision. This algorithm is inspired by the concept of the Artificial Potential Field (APF) method and behavior-based approximate reasoning. An exhaustive search approach is used to avoid the randomly appeared obstacles, approximately estimate positions of obstacles, thus reaching the surveillance point and then tracking the allotted path for the robots. The robots are governed to move in real-time, maintaining a formation between them to track the assigned path cooperatively. The performance of this algorithm is validated in a real-time and simulation environment using MATLAB/Simulink. It is observed from the results of performance measuring parameters path length and travel time that the proposed algorithm outperforms than existing A*, RRT, and GA algorithm. |
| first_indexed | 2024-04-12T16:06:10Z |
| format | Article |
| id | doaj.art-52b1b24fbac54692be19620ef5e4fc6d |
| institution | Directory Open Access Journal |
| issn | 2090-4479 |
| language | English |
| last_indexed | 2024-04-12T16:06:10Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj.art-52b1b24fbac54692be19620ef5e4fc6d2022-12-22T03:26:03ZengElsevierAin Shams Engineering Journal2090-44792022-09-01135101675Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning AlgorithmMadhu Sudan Das0Sourish Sanyal1Sanjoy Mandal2Indian Institute of Technology, Dhanbad, India; Corresponding author.Electronics & Communication Engineering Department, Cooch Behar Government Engineering College, West Bengal, IndiaElectrical Engineering Department, IIT Dhanbad, Jharkhand, IndiaThis paper proposes a new algorithm for multiple robots that can navigate from source to goal position in a coordinated and formative manner in an optimum path and time, efficiently avoiding static and dynamic obstacles. The proposed algorithm is applied here to track surveillance for two and four robots from starting point to the goal point in an obstacle environment without collision. This algorithm is inspired by the concept of the Artificial Potential Field (APF) method and behavior-based approximate reasoning. An exhaustive search approach is used to avoid the randomly appeared obstacles, approximately estimate positions of obstacles, thus reaching the surveillance point and then tracking the allotted path for the robots. The robots are governed to move in real-time, maintaining a formation between them to track the assigned path cooperatively. The performance of this algorithm is validated in a real-time and simulation environment using MATLAB/Simulink. It is observed from the results of performance measuring parameters path length and travel time that the proposed algorithm outperforms than existing A*, RRT, and GA algorithm.http://www.sciencedirect.com/science/article/pii/S2090447921004536Mobile robotsArtificial Potential Field (APF)Path planningUncertain environmentPSOA* |
| spellingShingle | Madhu Sudan Das Sourish Sanyal Sanjoy Mandal Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm Ain Shams Engineering Journal Mobile robots Artificial Potential Field (APF) Path planning Uncertain environment PSO A* |
| title | Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm |
| title_full | Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm |
| title_fullStr | Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm |
| title_full_unstemmed | Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm |
| title_short | Navigation of Multiple Robots in Formative Manner in an Unknown Environment using Artificial Potential Field Based Path Planning Algorithm |
| title_sort | navigation of multiple robots in formative manner in an unknown environment using artificial potential field based path planning algorithm |
| topic | Mobile robots Artificial Potential Field (APF) Path planning Uncertain environment PSO A* |
| url | http://www.sciencedirect.com/science/article/pii/S2090447921004536 |
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