A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints
In this paper, a multi-robot persistent coverage of the region of interest is considered, where persistent coverage and cooperative coverage are addressed simultaneously. Previous works have mainly concentrated on the paths that allow for repeated coverage, but ignored the coverage period requiremen...
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| Format: | Article |
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MDPI AG
2019-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/9/1994 |
| _version_ | 1828154982728204288 |
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| author | Guibin Sun Rui Zhou Bin Di Zhuoning Dong Yingxun Wang |
| author_facet | Guibin Sun Rui Zhou Bin Di Zhuoning Dong Yingxun Wang |
| author_sort | Guibin Sun |
| collection | DOAJ |
| description | In this paper, a multi-robot persistent coverage of the region of interest is considered, where persistent coverage and cooperative coverage are addressed simultaneously. Previous works have mainly concentrated on the paths that allow for repeated coverage, but ignored the coverage period requirements of each sub-region. In contrast, this paper presents a combinatorial approach for path planning, which aims to cover mission domains with different task periods while guaranteeing both obstacle avoidance and minimizing the number of robots used. The algorithm first deploys the sensors in the region to satisfy coverage requirements with minimum cost. Then it solves the travelling salesman problem to obtain the frame of the closed path. Finally, the approach partitions the closed path into the fewest segments under the coverage period constraints, and it generates the closed route for each robot on the basis of portioned segments of the closed path. Therefore, each robot can circumnavigate one closed route to cover the different task areas completely and persistently. The numerical simulations show that the proposed approach is feasible to implement the cooperative coverage in consideration of obstacles and coverage period constraints, and the number of robots used is also minimized. |
| first_indexed | 2024-04-11T22:46:47Z |
| format | Article |
| id | doaj.art-022c50c0d5e7428187177c10a4427e6b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T22:46:47Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-022c50c0d5e7428187177c10a4427e6b2022-12-22T03:58:44ZengMDPI AGSensors1424-82202019-04-01199199410.3390/s19091994s19091994A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period ConstraintsGuibin Sun0Rui Zhou1Bin Di2Zhuoning Dong3Yingxun Wang4School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, ChinaNational Innovation Institute of Defense Technology, Academy of Military Sciences PLA China, Beijing 100071, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, ChinaSchool of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, ChinaIn this paper, a multi-robot persistent coverage of the region of interest is considered, where persistent coverage and cooperative coverage are addressed simultaneously. Previous works have mainly concentrated on the paths that allow for repeated coverage, but ignored the coverage period requirements of each sub-region. In contrast, this paper presents a combinatorial approach for path planning, which aims to cover mission domains with different task periods while guaranteeing both obstacle avoidance and minimizing the number of robots used. The algorithm first deploys the sensors in the region to satisfy coverage requirements with minimum cost. Then it solves the travelling salesman problem to obtain the frame of the closed path. Finally, the approach partitions the closed path into the fewest segments under the coverage period constraints, and it generates the closed route for each robot on the basis of portioned segments of the closed path. Therefore, each robot can circumnavigate one closed route to cover the different task areas completely and persistently. The numerical simulations show that the proposed approach is feasible to implement the cooperative coverage in consideration of obstacles and coverage period constraints, and the number of robots used is also minimized.https://www.mdpi.com/1424-8220/19/9/1994multi-robotcooperative coveragepersistent coveragepath planningcoverage period constraintsobstacle avoidance |
| spellingShingle | Guibin Sun Rui Zhou Bin Di Zhuoning Dong Yingxun Wang A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints Sensors multi-robot cooperative coverage persistent coverage path planning coverage period constraints obstacle avoidance |
| title | A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints |
| title_full | A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints |
| title_fullStr | A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints |
| title_full_unstemmed | A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints |
| title_short | A Novel Cooperative Path Planning for Multi-robot Persistent Coverage with Obstacles and Coverage Period Constraints |
| title_sort | novel cooperative path planning for multi robot persistent coverage with obstacles and coverage period constraints |
| topic | multi-robot cooperative coverage persistent coverage path planning coverage period constraints obstacle avoidance |
| url | https://www.mdpi.com/1424-8220/19/9/1994 |
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