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Improved A-STAR Algorithm for Power Line Inspection UAV Path Planning

Author

Listed:
  • Yanchu Li

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Xinzhou Dong

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Qingqing Ding

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Yinlong Xiong

    (Guangdong Power Grid Co., Ltd. Foshan Power Supply Bureau, Foshan 528000, China)

  • Huilian Liao

    (State Grid Henan Electric Power Company DC Center, Zhengzhou 450018, China)

  • Tao Wang

    (State Grid Henan Electric Power Company DC Center, Zhengzhou 450018, China)

Abstract

The operational areas for unmanned aerial vehicles (UAVs) used in power line inspection are highly complex; thus, the best path planning under known obstacles is of significant research value for UAVs. This paper establishes a three-dimensional spatial environment based on the gridding and filling of two-dimensional maps, simulates a variety of obstacles, and proposes a new optimization algorithm based on the A-STAR algorithm, considering the unique dynamics and control characteristics of quadcopter UAVs. By utilizing a novel heuristic evaluation function and uniformly applied quadratic B-spline curve smoothing, the planned path is optimized to better suit UAV inspection scenarios. Compared to the traditional A-STAR algorithm, this method offers improved real-time performance and global optimal solution-solving capabilities and is capable of planning safer and more realistic flight paths based on the operational characteristics of quadcopter UAVs in mountainous environments for power line inspection.

Suggested Citation

  • Yanchu Li & Xinzhou Dong & Qingqing Ding & Yinlong Xiong & Huilian Liao & Tao Wang, 2024. "Improved A-STAR Algorithm for Power Line Inspection UAV Path Planning," Energies, MDPI, vol. 17(21), pages 1-18, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5364-:d:1508556
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