Distributed intelligent self-organized mission planning of multi-UAV for dynamic targets cooperative search-attack

Abstract 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.

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