Cooperative Optimal Control of UAVs Based on Brain-Attention Mechanism Neural Network

Ziyuan Ma, Huajun Gong, Xinhua Wang
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Abstract

With the increasing complexity and variety of mission environments, multiple-UAVs cooperative path optimization system is gradually becoming an important development direction in the future. Because the current intelligent level of UAV is difficult to meet the requirements of complex tasks, in order to improve the intelligence and collaborative ability of multiple-UAVs systems, this paper focuses on the intelligent decision-making and collaborative control of UAV in the collaborative path of multiple UAVs system. In this paper, an autonomous and innovative UAV Cooperative Path Optimization System Based on neural network of brain like attention mechanism is proposed. The experimental results show that this method has lower processing delay, can achieve positioning accuracy in a shorter time, and has higher reliability and accuracy than the traditional center controlled UAV cooperative positioning UAV method.
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基于脑注意机制神经网络的无人机协同最优控制
随着任务环境的日益复杂和多样化,多无人机协同路径优化系统逐渐成为未来重要的发展方向。由于目前无人机的智能化水平难以满足复杂任务的要求,为了提高多无人机系统的智能化和协同能力,本文重点研究了多无人机系统协同路径下无人机的智能决策和协同控制。提出了一种基于类脑注意机制神经网络的无人机自主创新协同路径优化系统。实验结果表明,该方法具有较低的处理延迟,可以在较短的时间内实现定位精度,并且比传统的中心控制无人机协同定位无人机方法具有更高的可靠性和精度。
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