Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments
Addressing the path planning problem for multiple wheeled mobile robots (WMRs) in uncertain environments, this paper proposes a multi-WMR path planning algorithm based on the fusion of artificial potential field and model predictive control. Firstly, an artificial potential field model for uncertain...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/1/39 |
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| author | Yang She Chao Song Zetian Sun Bo Li |
| author_facet | Yang She Chao Song Zetian Sun Bo Li |
| author_sort | Yang She |
| collection | DOAJ |
| description | Addressing the path planning problem for multiple wheeled mobile robots (WMRs) in uncertain environments, this paper proposes a multi-WMR path planning algorithm based on the fusion of artificial potential field and model predictive control. Firstly, an artificial potential field model for uncertain environments is established based on the APF method. Secondly, an MPC optimal controller that considers the artificial potential field model is designed to ensure the smooth avoidance of moving and concave obstacles by multiple WMRs in uncertain environments. Additionally, a formation control algorithm based on an enhanced APF method and the leader–follower algorithm is proposed to achieve formation maintenance, intra-formation collision avoidance, and obstacle circumvention, thereby ensuring formation stability. Finally, two sets of simulation experiments in uncertain environments demonstrate the effectiveness and superiority of the proposed method compared to the APF-MPC algorithm, enabling the control of multiple WMRs to reach their target positions safely, smoothly, and efficiently. Furthermore, two sets of real-world experiments validate the feasibility of the algorithm proposed in this paper. |
| format | Article |
| id | doaj-art-0db0177156af4f1b94bca8163be56ae2 |
| institution | Kabale University |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-0db0177156af4f1b94bca8163be56ae22025-01-24T13:29:44ZengMDPI AGDrones2504-446X2025-01-01913910.3390/drones9010039Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain EnvironmentsYang She0Chao Song1Zetian Sun2Bo Li3School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaAddressing the path planning problem for multiple wheeled mobile robots (WMRs) in uncertain environments, this paper proposes a multi-WMR path planning algorithm based on the fusion of artificial potential field and model predictive control. Firstly, an artificial potential field model for uncertain environments is established based on the APF method. Secondly, an MPC optimal controller that considers the artificial potential field model is designed to ensure the smooth avoidance of moving and concave obstacles by multiple WMRs in uncertain environments. Additionally, a formation control algorithm based on an enhanced APF method and the leader–follower algorithm is proposed to achieve formation maintenance, intra-formation collision avoidance, and obstacle circumvention, thereby ensuring formation stability. Finally, two sets of simulation experiments in uncertain environments demonstrate the effectiveness and superiority of the proposed method compared to the APF-MPC algorithm, enabling the control of multiple WMRs to reach their target positions safely, smoothly, and efficiently. Furthermore, two sets of real-world experiments validate the feasibility of the algorithm proposed in this paper.https://www.mdpi.com/2504-446X/9/1/39multi-WMRartificial potential fieldMPCleader–follower |
| spellingShingle | Yang She Chao Song Zetian Sun Bo Li Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments Drones multi-WMR artificial potential field MPC leader–follower |
| title | Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments |
| title_full | Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments |
| title_fullStr | Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments |
| title_full_unstemmed | Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments |
| title_short | Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments |
| title_sort | optimized model predictive control based path planning for multiple wheeled mobile robots in uncertain environments |
| topic | multi-WMR artificial potential field MPC leader–follower |
| url | https://www.mdpi.com/2504-446X/9/1/39 |
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