A Risk-based Path Planning Strategy to Compute Optimum Risk Path for Unmanned Aircraft Systems over Populated Areas
A Risk-based Path Planning Strategy to Compute Optimum Risk Path for Unmanned Aircraft Systems over Populated Areas
复制标题
基于风险的路径规划策略，用于计算人口稠密地区无人机系统的最佳风险路径
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
A. Rizzo
中科院分区：
文献类型：
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作者：
Stefano Primatesta;M. Scanavino;G. Guglieri;A. Rizzo
无人机系统（UAS）的大规模扩散需要一个合适的策略来设计安全的飞行任务。本文提出了一种新的路径规划策略来计算无人机在人口密集地区的最优风险路径，该策略基于快速探索随机树“星星”算法的变体，在路径规划阶段进行风险评估。与其他基于RRT的算法一样，所提出的路径规划通过构造图来探索状态空间。每次向图中添加新节点时，该算法都会估计新节点所涉及的风险级别，评估放置在分析节点中的UAS的飞行方向和速度。风险级别量化了飞越特定位置的风险，并使用概率风险评估方法定义，考虑了无人机参数和环境特征。然后，该算法通过最小化总体风险和飞行时间来计算渐进最优路径，仿真结果验证了该方法的有效性，证明了该方法能够在城市地区计算出有效且安全的路径。
The large diffusion of Unmanned Aircraft Systems (UAS) requires a suitable strategy to design safe flight missions. In this paper, we propose a novel path planning strategy to compute optimum risk path for UAS over populated areas.The proposed strategy is based on a variant of the RRT* (Rapidly-exploring Random Tree "Star") algorithm, performing a risk assessment during the path planning phase. Like other RRT-based algorithms, the proposed path planning explores the state space by constructing a graph. Each time a new node is added to the graph, the algorithm estimates the risk level involved by the new node, evaluating the flight direction and velocity of the UAS placed in the analyzed node.The risk level quantifies the risk of flying over a specific location and it is defined using a probabilistic risk assessment approach taking into account the drone parameters and environmental characteristics.Then, the proposed algorithm computes an asymptotically optimal path by minimizing the overall risk and flight time.Simulation results in realistic environments corroborate the proposed approach proving how the proposed risk-based path planning is able to compute an effective and safe path in urban areas.