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Cooperative search of UAV swarm based on improved ant colony algorithm in uncertain environment

机译:不确定环境下基于改进蚁群算法的无人机群协同搜索

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摘要

Considering the situation that the regional environment is completely unknown and is dynamically changing, a novel method for multi-UAV (Unmanned Aerial Vehicle) conducting cooperative area search based on Ant Colony (AC) Theory is proposed. Firstly, the regional environment model and the UAV dynamic model were established. Secondly, the transfer rules of the waypoints were determined for UAVs by improving the behavior criterion of the ant colony algorithm and the updating principle of the pheromone map. Finally, Compared with the conventional search methods, the simulation results with higher coverage rate and search efficiency demonstrated the improved ant colony algorithm was rationality and validity.
机译:鉴于区域环境完全未知且不断变化的情况,提出了一种新的基于蚁群理论的多UAV协同区域搜索方法。首先,建立了区域环境模型和无人机动态模型。其次,通过改进蚁群算法的行为准则和信息素图的更新原理,确定了无人机的航点传递规则。最后,与传统搜索方法相比,具有更高的覆盖率和搜索效率的仿真结果表明,改进的蚁群算法是合理有效的。

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