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Cooperative Local Path Planning for Multi-unmanned Vehicles Formation Using the Enhanced Artificial Potential Field

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Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023) (ICAUS 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1177))

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Abstract

An enhanced approach utilizing APF(artificial potential field) method is introduced in this paper. By adopting this approach, the challenge of local minima that may occur when dealing with local path planning for unmanned vehicles is tackled. When the unmanned vehicle approaches an obstacle, a virtual attractive potential field is implemented, utilizing the deviation in the heading angle of the vehicle to control the steering angle. Consequently, the vehicle can avoid obstacles, resolving the issue of local minima and enabling its application in path planning for multi-unmanned vehicles. The ROS with Gazebo simulation platform is used to verify the enhanced algorithm’s effectiveness in multi-unmanned vehicle path planning in an unknown environment.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant 62173012 and Grant U20A20155, in part by the Beijing Municipal Key Research and Development Program under Grant Z221100002722001, in part by the Science and Technology Plan Projects of Beijing Municipal Commission of Transport under Grant 11000022210200021338-XM001, in part by the State Key Laboratory of Air Traffic Management System and Technology under Grant No. SKLATM202103, in part by the Opening Project of Key Laboratory of Operation Safety Technology on Transport Vehicles, Ministry of Transport, PRC, under Grant No. KFKT2021-05, in part by the Pilot Project for Strengthening Transportation of Research Institute of Highway Ministry of Transport under Grant No. QG2021-3-15-5, in part by the Key Technology Projects in the Transportation Industry under Grant No. 2021-ZD1-032.

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Authors and Affiliations

  1. Opening Project of Key Laboratory of Operation Safety Technology on Transport Vehicles, Ministry of Transport, PRC, Beijing, China

    Xin Zhang & Xuting Duan

  2. School of Transportation Science and Engineering, Beihang University, Beijing, China

    Xin Zhang, Xuting Duan & Jianshan Zhou

  3. State Key Lab of Intelligent Transportation System, Beijing, China

    Xin Zhang, Xuting Duan & Jianshan Zhou

  4. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, Beijing, China

    Xin Zhang, Xuting Duan & Jianshan Zhou

  5. Zhongguancun Laboratory, Beijing, China

    Xuting Duan

  6. National Key Laboratory of Science and Technology on Information System Security Institute of Systems Engineering, Beijing, China

    Long Zhang

Authors
  1. Xin Zhang
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  2. Xuting Duan
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  3. Jianshan Zhou
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  4. Long Zhang
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Corresponding author

Correspondence to Xuting Duan .

Editor information

Editors and Affiliations

  1. Nanjing University of Science and Technology, Nanjing, China

    Yi Qu

  2. Beijing HIWING Scientific and Technological Information Institute, Beijing, China

    Mancang Gu

  3. College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan, China

    Yifeng Niu

  4. Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an, Shaanxi, China

    Wenxing Fu

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Zhang, X., Duan, X., Zhou, J., Zhang, L. (2024). Cooperative Local Path Planning for Multi-unmanned Vehicles Formation Using the Enhanced Artificial Potential Field. In: Qu, Y., Gu, M., Niu, Y., Fu, W. (eds) Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023). ICAUS 2023. Lecture Notes in Electrical Engineering, vol 1177. Springer, Singapore. https://doi.org/10.1007/978-981-97-1103-1_34

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