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Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things

机译:基于物联网的多智能体混合社会认知优化的多人无人驾驶编队生成

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摘要

Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, formation principles, formation scale, unmanned vehicle formation safety distance, and formation evaluation indicators are taken into consideration. The application of the IoT enables the optimization of distributed computing. To ensure the reliability of the formation algorithm, the convergence of MAHSCO has been proved. Finally, computer simulation and actual unmanned aerial vehicle (UAV) formation generation flight generating four typical formations are carried out. The result of the actual UAV formation generation flight is consistent with the simulation experiment, and the algorithm performs well. The MAHSCO algorithm based on the IoT is proved to be able to generate formations that meet the mission requirements quickly and accurately.
机译:提出了基于物联网(IoT)的多主体混合社会认知优化方法(MAHSCO),以解决无人驾驶车辆编队生成问题。通过对无人机编队问题的分析,综合考虑编队原理,编队规模,无人机编队安全距离和编队评价指标。物联网的应用实现了分布式计算的优化。为了确保形成算法的可靠性,已经证明了MAHSCO的收敛性。最后,计算机模拟和实际的无人机编队生成飞行生成四个典型编队。实际无人机编队生成飞行的结果与仿真实验相吻合,算法性能良好。实践证明,基于物联网的MAHSCO算法能够快速,准确地生成满足任务要求的编队。

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