期刊
CHINESE JOURNAL OF AERONAUTICS
卷 32, 期 12, 页码 2706-2716出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.cja.2019.05.012
关键词
Ant Colony Optimization (ACO); Cooperative control; Mission planning; Search-attack integration; Self-organized; Unmanned Aerial Vehicle (UAV)
资金
- National Natural Science Foundation of China [61741313, 61673209, 61533008]
- Jiangsu Six Peak of Talents Program, China [KTHY-027]
- Postgraduate Research & Practice Innovation Program of Jiangsu Province, China [KYCX18_0303]
This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning (DISOMP) algorithm for multiple Unmanned Aerial Vehicles (multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization (ACO) algorithm, an attack module designed based on the Parallel Approach (PA) scheme, a threat avoidance module designed based on the Dubins Curve (DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem. (C) 2019 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd.
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