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Lizheng Deng, Hongyong Yuan, & Lida Huang. (2018). Optimal UAV 3D Path Planning in Mountainous Environments for Post-Earthquake Multi-region Search. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (p. 1122). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: During the earthquake rescue, rapidly locating the trapped person is a critical issue to reduce casualties. Compared with the ground search after the earthquake, the unmanned aerial vehicle (UAV) life detection is not only more expeditious but also safer. For shortening the mission completion time of UAV, we propose the coupling method of Dijkstra's algorithm and simulated annealing (SA) algorithm to optimize the search path. Concisely, the mathematical model is further abstracted as the Traveling Salesman Problem (TSP) and the shortest loop can be obtained by SA algorithm. The real geo-environment of Jiuzhaigou and the actual large-scale rescue scenarios are taken into consideration. Setting six key search areas as our life detection objects, the UAV 3D path simulation is conducted with MATLAB, which achieves the obstacle avoidance. Our UAV path planning method can significantly speed up the search process and save more people in the post-disaster search.
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