Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm
Path planning is crucial in the scheduling and motion planning of multiple robots. However, solving multi-robot path-planning problems efficiently and quickly is challenging due to their high complexity and long computational time, especially when dealing with many robots. This paper presents a unif...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-08-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/16/3483 |
| _version_ | 1797584909787725824 |
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| author | Dewei Zhao Sheng Zhang Faming Shao Li Yang Qiang Liu Heng Zhang Zihan Zhang |
| author_facet | Dewei Zhao Sheng Zhang Faming Shao Li Yang Qiang Liu Heng Zhang Zihan Zhang |
| author_sort | Dewei Zhao |
| collection | DOAJ |
| description | Path planning is crucial in the scheduling and motion planning of multiple robots. However, solving multi-robot path-planning problems efficiently and quickly is challenging due to their high complexity and long computational time, especially when dealing with many robots. This paper presents a unified mathematical model and algorithm for the path planning of multiple robots moving from one formation to another in an area with obstacles. The problem was initially simplified by constructing a cost matrix, and then the route planning was achieved by integrating an elite enhanced multi-population genetic algorithm and an ant colony algorithm. The performance of the proposed planning method was verified through numerical simulations in various scenarios. The findings indicate that this method exhibits high computational efficiency and yields a minimal overall path distance when addressing the path-planning problem of a multi-robot formation reconstruction. As a result, it holds promising potential for the path-planning problem of a multi-robot formation reconstruction. |
| first_indexed | 2024-03-10T23:59:24Z |
| format | Article |
| id | doaj.art-9ac028ecee174212bd4c050ddb77cd89 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T23:59:24Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-9ac028ecee174212bd4c050ddb77cd892023-11-19T00:54:20ZengMDPI AGElectronics2079-92922023-08-011216348310.3390/electronics12163483Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated AlgorithmDewei Zhao0Sheng Zhang1Faming Shao2Li Yang3Qiang Liu4Heng Zhang5Zihan Zhang6College of Field Engineering, Army Engineering University, PLA, Nanjing 210007, ChinaCollege of Field Engineering, Army Engineering University, PLA, Nanjing 210007, ChinaCollege of Field Engineering, Army Engineering University, PLA, Nanjing 210007, ChinaCollege of Field Engineering, Army Engineering University, PLA, Nanjing 210007, ChinaCollege of Field Engineering, Army Engineering University, PLA, Nanjing 210007, ChinaCollege of Field Engineering, Army Engineering University, PLA, Nanjing 210007, ChinaCollege of Field Engineering, Army Engineering University, PLA, Nanjing 210007, ChinaPath planning is crucial in the scheduling and motion planning of multiple robots. However, solving multi-robot path-planning problems efficiently and quickly is challenging due to their high complexity and long computational time, especially when dealing with many robots. This paper presents a unified mathematical model and algorithm for the path planning of multiple robots moving from one formation to another in an area with obstacles. The problem was initially simplified by constructing a cost matrix, and then the route planning was achieved by integrating an elite enhanced multi-population genetic algorithm and an ant colony algorithm. The performance of the proposed planning method was verified through numerical simulations in various scenarios. The findings indicate that this method exhibits high computational efficiency and yields a minimal overall path distance when addressing the path-planning problem of a multi-robot formation reconstruction. As a result, it holds promising potential for the path-planning problem of a multi-robot formation reconstruction.https://www.mdpi.com/2079-9292/12/16/3483multi-robot path planningformation reconstructionmulti-population genetic algorithmant colony algorithm |
| spellingShingle | Dewei Zhao Sheng Zhang Faming Shao Li Yang Qiang Liu Heng Zhang Zihan Zhang Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm Electronics multi-robot path planning formation reconstruction multi-population genetic algorithm ant colony algorithm |
| title | Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm |
| title_full | Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm |
| title_fullStr | Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm |
| title_full_unstemmed | Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm |
| title_short | Path Planning for the Rapid Reconfiguration of a Multi-Robot Formation Using an Integrated Algorithm |
| title_sort | path planning for the rapid reconfiguration of a multi robot formation using an integrated algorithm |
| topic | multi-robot path planning formation reconstruction multi-population genetic algorithm ant colony algorithm |
| url | https://www.mdpi.com/2079-9292/12/16/3483 |
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