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Multi — UAV path planning based on improved neural network

机译:基于改进神经网络的多无人机航迹规划

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Aiming at the problem of multi-UAV path planning in three - dimensional environment, a fast path planning method is designed by using the improved neural network algorithm. According to the distance between the UAV and the threat, when the UAV is not in the threat area, the method of taking large step is adopted to achieve the purpose of rapid generation of the path. When the UAV is inside the threat area, the method of taking the adjustable step size is used to achieve the fine search path. The UAV rapid out of the threat is achieved by combining with the dynamic adjustable step size and neural network and using the adaptive learning factors, and using the attack revenue and cost function to establish the revenue function, the strategy should be taken is given through the revenue. The simulation results show that the algorithm proposed in this paper not only guarantees the safety of UAV to bypass the threat, but also the better path is obtained and the best decision-making strategy is found.
机译:针对三维环境下的多无人机航路规划问题,利用改进的神经网络算法设计了一种快速航路规划方法。根据无人机与威胁的距离,当无人机不在威胁区域时,采用大步法来达到快速生成路径的目的。当无人机位于威胁区域内时,采用可调整步长的方法来实现精细搜索路径。通过结合动态可调步长和神经网络并利用自适应学习因素,并利用攻击收益和成本函数建立收益函数,可以实现无人机快速摆脱威胁。收入。仿真结果表明,本文提出的算法不仅保证了无人机绕过威胁的安全性,而且获得了较好的路径,并找到了最佳的决策策略。

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