Journal of System Simulation
Abstract
Abstract: For the challenges such as large disaster area, uneven distribution of key areas and limited rescue time in emergency rescue, a multi-UAV collaborative priority coverage search algorithm is proposed. The search area is rasterized, and each grid is probabilistically labeled according to the disaster prediction information. The search area is divided into sub-regions of similar size and equal number of UAVs by K-means++ algorithm, and the search starting point of each sub-region is determined based on the clustering center, so that the multiple UAVs can carry out the partition cooperative search of the whole area. The score of each grid is calculated according to the balance between grid probability and current distance, which is used as a benchmark by the improved greedy algorithm for priority search and reducing the duplicate paths in the sub-region, while A* algorithm is introduced to solve the grid score redundancy problem. The results show that the proposed algorithm effectively reduces the path length and search time while ensuring the priority search, and provides an effective solution to the search problem in emergency rescue.
Recommended Citation
Yu, Xiang; Deng, Qianrui; Duan, Sirui; and Jiang, Chen
(2024)
"A Multi-UAV Collaborative Priority Coverage Search Algorithm,"
Journal of System Simulation: Vol. 36:
Iss.
4, Article 17.
DOI: 10.16182/j.issn1004731x.joss.22-1476
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol36/iss4/17
First Page
991
Last Page
1000
CLC
TP391.9
Recommended Citation
Yu Xiang, Deng Qianrui, Duan Sirui, et al. A Multi-UAV Collaborative Priority Coverage Search Algorithm[J]. Journal of System Simulation, 2024, 36(4): 991-1000.
DOI
10.16182/j.issn1004731x.joss.22-1476
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