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A Path Planning Algorithm for AGV Combining the Improved Dynamic Window Approach and Artificial Potential Field Method
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Yu-qing LI1, Zhong-nan LIANG2, *, Yan-zhao ZHAO2, Kun ZHOU3
Science Technology and Engineering | 2025, 25(14) : 5924 - 5933
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Science Technology and Engineering | 2025, 25(14): 5924-5933
• Papers·Automation and Computational Technology •
A Path Planning Algorithm for AGV Combining the Improved Dynamic Window Approach and Artificial Potential Field Method
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Yu-qing LI1, Zhong-nan LIANG2, *, Yan-zhao ZHAO2, Kun ZHOU3
Affiliations
  • 1. Shenhua Group Zhungeer Energy Co., Ltd., Ordos 010300, China
  • 2. Qingdao Wohua Soft Control Co., Ltd., Qingdao 266071, China
  • 3. College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China
Published: 2025-05-18 doi: 10.12404/j.issn.1671-1815.2405367
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Considering the oscillation phenomenon of the original DWA(dynamic window approach) in path planning, an improved DWA path planning algorithm was designed, which is integrated with the artificial potential field method. Firstly, the safety constraint of the DWA algorithm is improved, and the linear obstacle distance evaluation function in the original DWA was improved to the nonlinear obstacle potential field function in the artificial potential field method. Secondly, the improved DWA was combined with the smooth A* path of the gradient descent method to solve the problem of poor global planning of the traditional algorithm. Finally, the feasibility of the algorithm was verified by simulation experiments and physical experiments. In the simulation experiments, compared with the original algorithm, the improved algorithm in this paper reduces the path of the designed obstacle scene by 9.84%, reduces the running time by 31.71%, and improves the smoothness by 6.49%. Meanwhile, compared with the results of related literatures, the results of this paper have been improved to different degrees in different scenarios. In the physical experiments of automated guided vehicle, the path length is reduced by 10.76% and the elapsed time is reduced by 13.09%. Therefore, the improved DWA generates better path smoothness, shorter path length and shorter elapsed time.

automated guided vehicle  /  path planning  /  DWA(dynamic window approach)  /  artificial potential field method
Yu-qing LI, Zhong-nan LIANG, Yan-zhao ZHAO, Kun ZHOU. A Path Planning Algorithm for AGV Combining the Improved Dynamic Window Approach and Artificial Potential Field Method[J]. Science Technology and Engineering, 2025 , 25 (14) : 5924 -5933 . DOI: 10.12404/j.issn.1671-1815.2405367
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Article Info
doi: 10.12404/j.issn.1671-1815.2405367
  • Receive Date：2024-07-17
  • Online Date：2025-07-09
  • Published：2025-05-18
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History
  • Received：2024-07-17
  • Revised：2025-02-28
Funding
Affiliations
    1. Shenhua Group Zhungeer Energy Co., Ltd., Ordos 010300, China
    2. Qingdao Wohua Soft Control Co., Ltd., Qingdao 266071, China
    3. College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China
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