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This paper proposes a novel trajectory planning approach for target tracking with multiple UAVs in obstacle environments. It incorporates the dynamic features of fixed-wing UAVs to enhance the effectiveness of tracking systems and the reliability of trajectories. To address the complexity of unresolved models and nonlinear constraints, an improved grey wolf optimizer with efficient and stable (GWO-ES) algorithm is introduced. This algorithm effectively solves trajectory planning problems with multiple constraints in complex environments, enabling continuous target tracking by multiple UAVs. Simulation results indicate that the GWO-ES algorithm exhibits superior search capability and stability, effectively meeting the continuous tracking requirements of multiple UAVs for the target.

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Multi-UAV Tracking of Ground Moving Target in Obstacle Environments

  • 会议论文

  • 发表日期：

    2025年

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  • Guodong Chen,
  • Kang Tan,
  • Chao Yan,
  • Shuai Yuan,
  • Zexu Zhang

摘要

This paper proposes a novel trajectory planning approach for target tracking with multiple UAVs in obstacle environments. It incorporates the dynamic features of fixed-wing UAVs to enhance the effectiveness of tracking systems and the reliability of trajectories. To address the complexity of unresolved models and nonlinear constraints, an improved grey wolf optimizer with efficient and stable (GWO-ES) algorithm is introduced. This algorithm effectively solves trajectory planning problems with multiple constraints in complex environments, enabling continuous target tracking by multiple UAVs. Simulation results indicate that the GWO-ES algorithm exhibits superior search capability and stability, effectively meeting the continuous tracking requirements of multiple UAVs for the target.