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Distributed Cooperative Search Control Method of Multiple UAVs for Moving Target

机译:多目标移动目标的分布式协同搜索控制方法

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摘要

To reduce the impact of uncertainties caused by unknown motion parameters on searching plan of moving targets and improve the efficiency of UAV’s searching, a novel distributed Multi-UAVs cooperative search control method for moving target is proposed in this paper. Based on detection results of onboard sensors, target probability map is updated using Bayesian theory. A Gaussian distribution of target transition probability density function is introduced to calculate prediction probability of moving target existence, and then target probability map can be further updated in real-time. A performance index function combining with target cost, environment cost, and cooperative cost is constructed, and the cooperative searching problem can be transformed into a central optimization problem. To improve computational efficiency, the distributed model predictive control method is presented, and thus the control command of each UAV can be obtained. The simulation results have verified that the proposed method can avoid the blindness of UAV searching better and improve overall efficiency of the team effectively.
机译:为了减少运动参数未知带来的不确定性对运动目标搜索计划的影响,提高无人机的搜索效率,提出了一种新颖的分布式多无人机协同运动目标搜索控制方法。根据机载传感器的检测结果,使用贝叶斯理论更新目标概率图。引入目标转移概率密度函数的高斯分布来计算移动目标存在的预测概率,然后可以进一步实时更新目标概率图。构建了结合目标成本,环境成本和合作成本的绩效指标函数,将合作搜索问题转化为集中优化问题。为了提高计算效率,提出了一种分布式模型预测控制方法,从而可以获得每架无人机的控制命令。仿真结果表明,该方法可以较好地避免无人机搜索的盲目性,有效提高了团队的整体效率。

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