Using On-line Simulation for Adaptive Path Planning of UAVs

Farzad Kamrani, R. Ayani
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引用次数: 44

Abstract

In a surveillance mission, the task of Unmanned Aerial Vehicles (UAV) path planning can in some cases be addressed using Sequential Monte Carlo (SMC) simulation. If sufficient a priori information about the target and the environment is available an assessment of the future state of the target is obtained by the SMC simulation. This assessment is used in a set of "what-if" simulations to compare different alternative UAV paths. In a static environment this simulation can be conducted prior to the mission. However, if the environment is dynamic, it is required to run the "what-if" simulations on-line i.e. in real-time. In this paper the details of this on-line simulation approach in UAV path planning is studied and its performance is compared with two other methods: an off-line simulationaided path planning and an exhaustive search method. The conducted simulations indicate that the on-line simulation has generally a higher performance compared with the two other methods.
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基于在线仿真的无人机自适应路径规划
在监视任务中,无人机(UAV)的路径规划任务在某些情况下可以使用顺序蒙特卡罗(SMC)仿真来解决。如果有足够的关于目标和环境的先验信息可用,则通过SMC模拟获得目标未来状态的评估。该评估用于一组“假设”模拟,以比较不同的备选无人机路径。在执行任务之前,可以在静态环境中进行这种模拟。然而,如果环境是动态的,则需要在线(即实时)运行“假设”模拟。本文详细研究了在线仿真方法在无人机路径规划中的应用,并与离线仿真辅助路径规划方法和穷举搜索方法进行了性能比较。仿真结果表明,与其他两种方法相比,在线仿真总体上具有更高的性能。
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