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    Multi-UAV Standoff Tracking in Unknown Complex Environments Using a Modulated Adaptive Guiding Vector Field
    (2026-03-01)
    Chen, Guodong
    ;
    Yuan, Shuai
    ;
    Liu, Jingzong
    ;
    Zhang, Zexu
    ;
    Kamsing, Patcharin
    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.
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    Cooperative Motion Planning for Multiple UAVs via the Bézier Curve Guided Line of Sight Techniques
    (2022-01-01)
    Hematulin, Warunyu
    ;
    Kamsing, Patcharin
    ;
    Torteeka, Peerapong
    ;
    Somjit, Thanaporn
    ;
    Phisannupawong, Thaweerath
    Multiple motion planning plays an essential role in several vehicle motions. This paper proposes a cooperative method between the Line of Sight techniques and the Bézier curve, applying this to motion planning for unmanned aerial vehicles. The experiment is implemented using the AirSim plugin on Unreal Engine 4. The results of the proposed method are compared with those for the conventional Line of Sight techniques to control multiple unmanned aerial vehicles. The results illustrate that the proposed method takes more time to process than the conventional one. However, the proposed method can reach a higher performance by addressing the target unmanned aerial vehicles and the pre-defining path more than the conventional method does, which is shown in all three simulation cases.
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    Cooperative motion planning for multiple uavs via the bezier curve guided line of sight techniques
    (2021-02-07)
    Hematulin, Warunyu
    ;
    Kamsing, Patcharin
    ;
    Torteeka, Peerapong
    ;
    Somjit, Thanaporn
    ;
    Phisannupawong, Thaweerath
    Multiple motion planning plays an essential role in several vehicle motions. This paper proposes a cooperative method between the Line of Sight techniques and the Bezier curve, applying this to motion planning for unmanned aerial vehicles. The experiment is implemented using the AirSim plugin on Unreal Engine 4. The results of the proposed method are compared with those for the conventional Line of Sight techniques to control multiple unmanned aerial vehicles. The results illustrate that the proposed method takes more time to process than the conventional one. However, the proposed method can reach a higher performance by addressing the target unmanned aerial vehicles and the pre-defining path more than the conventional method does, which is shown in all three simulation cases.