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<p>This paper proposes a novel trajectory planning method for multiple UAVs (Unmanned Aerial Vehicle, UAV) collaborative standoff tracking using a consistency GVF (Guiding Vector Field, GVF ) with an adaptive gain (AG-GVF), which is modulated by a modulation matrix for collision-free navigation in unknown complex environments. Firstly, the AG-GVF is established based on the desired path, with an adaptive gain and an additional virtual coordinate introduced to elevate dimensionality. The adaptive gain aims at reducing steady-state error and eliminating oscillations. This virtual coordinate is not only used for eliminating singular points but also utilized as a state variable for consistency control, ensuring uniform phase distribution among multiple UAVs during standoff tracking. Subsequently, in environments with obstacles, a modulation matrix is proposed to adjust the original GVF motion by estimating the normals of unknown obstacles using point clouds and constructing a modulation matrix to modify the AG-GVF direction for effective obstacle avoidance. Finally, the obtained desired path is optimized to generate flight trajectories that satisfy the kinematic constraints of fixed-wing UAVs. Simulation results demonstrate that the proposed method enables multiple UAVs to achieve collaborative standoff tracking with collision-free navigation in unknown complex environments.</p>

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Multi-UAV Standoff Tracking in Unknown Complex Environments Using a Modulated Adaptive Guiding Vector Field

  • 期刊论文

  • 发表日期：

    2026年1月14日

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  • Guodong Chen,
  • Shuai Yuan,
  • Jingzong Liu,
  • Zexu Zhang,
  • Patcharin Kamsing,
  • Peerapong Torteeka

摘要

This paper proposes a novel trajectory planning method for multiple UAVs (Unmanned Aerial Vehicle, UAV) collaborative standoff tracking using a consistency GVF (Guiding Vector Field, GVF ) with an adaptive gain (AG-GVF), which is modulated by a modulation matrix for collision-free navigation in unknown complex environments. Firstly, the AG-GVF is established based on the desired path, with an adaptive gain and an additional virtual coordinate introduced to elevate dimensionality. The adaptive gain aims at reducing steady-state error and eliminating oscillations. This virtual coordinate is not only used for eliminating singular points but also utilized as a state variable for consistency control, ensuring uniform phase distribution among multiple UAVs during standoff tracking. Subsequently, in environments with obstacles, a modulation matrix is proposed to adjust the original GVF motion by estimating the normals of unknown obstacles using point clouds and constructing a modulation matrix to modify the AG-GVF direction for effective obstacle avoidance. Finally, the obtained desired path is optimized to generate flight trajectories that satisfy the kinematic constraints of fixed-wing UAVs. Simulation results demonstrate that the proposed method enables multiple UAVs to achieve collaborative standoff tracking with collision-free navigation in unknown complex environments.