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针对多个无人机(unmanned aerial vehicle,UAV)执行基于视觉的目标跟踪的最佳协调问题,提高不可预知的地面目标的最佳结合点的视觉测量效果,提出了一种基于随机网格回归Monte Carlo的UAV最优目标跟踪策略。首先,通过无人机动力学和目标动力学分析,获得双UAV情况下的随机最优协调控制目标;其次,针对提出的控制目标,引入Monte Carlo求解方案,同时为解决标准Monte Carlo方案中存在的状态空间维度较高,计算复杂且精度不高的问题,利用随机网格方式构建回归Monte Carlo方案,实现UAV的最优协调控制;最后,通过仿真实验验证了所提方法的有效性。
Aiming at the optimal coordination of visual tracking based on unmanned aerial vehicle (UAV) and improving the visual measurement of the best combination point of unpredictable ground targets, a new method based on random grid regression Monte Carlo UAV optimal target tracking strategy. Firstly, through UAV dynamics and target dynamics analysis, we get the goal of stochastic optimal coordinated control in dual UAV. Secondly, we introduce the Monte Carlo solution to the proposed control objectives. At the same time, to solve the problem that exists in the standard Monte Carlo scheme The state space dimension is high, the calculation is complicated and the accuracy is not high. The Monte Carlo scheme is constructed by random grid to realize the optimal coordinated control of UAV. Finally, the validity of the proposed method is verified by simulation experiments.