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首页> 外文期刊>SIAM journal on applied dynamical systems >Risk-Based Path Planning Optimization Methods for Unmanned Aerial Vehicles Over Inhabited Areas
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Risk-Based Path Planning Optimization Methods for Unmanned Aerial Vehicles Over Inhabited Areas

机译：基于风险的路径规划优化方法，用于居住区的无人空中车辆

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Operating unmanned aerial vehicles (UAVs) over inhabited areas requires mitigating the risk to persons on the ground. Because the risk depends upon the flight path, UAV operators need approaches that can find low-risk flight paths between the mission's start and finish points. Because the flight paths with the lowest risk could be excessively long and indirect, UAV operators are concerned about the tradeoff between risk and flight time. This paper presents a risk assessment technique and bi-objective optimization methods to find low-risk and time (flight path) solutions and computational experiments to evaluate the relative performance of the methods (their computation time and solution quality). The methods were a network optimization approach that constructed a graph for the problem and used that to generate initial solutions that were then improved by a local approach and a greedy approach and a fourth method that did not use the network solutions. The approaches that improved the solutions generated by the network optimization step performed better than the optimization approach that did not use the network solutions.
机译：在居住地区经营无人驾驶的空中车辆（无人机）要求将危险的人降低到地面上的风险。因为风险取决于飞行路径，所以无人机运营商需要能够在特派团开始和完成点之间找到低风险飞行路径的方法。由于具有最低风险的飞行路径可能是过度长而间接的，因此无人机运营商关注风险和飞行时间之间的权衡。本文介绍了风险评估技术和双目标优化方法，以查找低风险和时间（飞行路径）解决方案和计算实验，以评估方法的相对性能（其计算时间和解决方案质量）。该方法是一种网络优化方法，构建了问题的图表，并使用它来产生通过本地方法和贪婪的方法和不使用网络解决方案的第四种方法改善的初始解决方案。改进网络优化步骤生成的解决方案的方法比不使用网络解决方案的优化方法更好地执行。

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