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Decentralized cooperative trajectory planning for multiple UAVs in dynamic and uncertain environments

机译:在动态和不确定环境中的多个无人机的分散合作轨迹规划

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This paper studies the problem of planning collision-free dynamically feasible trajectories for a team of autonomous unmanned aerial vehicles (UAVs) in real-time, where the UAVs try to fly through a complex 3-D environment to reach their specified destinations. First, the cooperative trajectory planning problem is mathematically formulated as a decentralized receding horizon optimal control problem (DRH-OCP). Second, a decentralized coordination strategy for multi-vehicle real-time trajectory planning is designed by effectively combining the benefits of inverse dynamics optimization method and receding horizon optimal control technique. This coordination strategy mainly features that each vehicle only solves a sub-problem for its own plan and vehicles in the team make plans in parallel. Finally, simulation results show the feasibility of the proposed planning strategies.
机译:本文研究了为一组自动无人驾驶飞行器(UAV)实时规划无碰撞动态可行轨迹的问题,其中无人飞行器试图在复杂的3D环境中飞行以到达其指定目的地。首先,将合作轨迹规划问题数学上表述为分散的后退地平线最优控制问题(DRH-OCP)。其次,通过有效结合逆动力学优化方法和后退水平最优控制技术的优点,设计了多车实时轨迹规划的分散协调策略。这种协调策略的主要特点是,每辆车只能解决自己计划的一个子问题,而团队中的车则并行制定计划。最后,仿真结果表明了所提策略的可行性。

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