A Self-Organization Formation Configuration Based Assignment Probability and Collision Detection

IF 1.9 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Journal of Systems Engineering and Electronics Pub Date : 2024-03-12 DOI:10.23919/jsee.2024.000016
Wei Song, Tong Wang, Guangxin Yang, Peng Zhang
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Abstract

The formation control of multiple unmanned aerial vehicles (multi-UAVs) has always been a research hotspot. Based on the straight line trajectory, a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption. In order to avoid the collision between UAVs in the formation process, the concept of safety ball is introduced, and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs. Based on the idea of game theory, a method of UAV motion form setting based on the maximization of interests is proposed, including the maximization of self-interest and the maximization of formation interest is proposed, so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance. Finally, through simulation verification, the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length, and the UAV motion selection method based on the maximization interests can effectively complete the task formation.
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基于分配概率和碰撞检测的自组织编队配置
多无人机编队控制一直是研究热点。在直线轨迹的基础上,提出了一种基于分配概率的多无人机目标点分配算法,以较低的复杂度实现多无人机整体编队路径最短,并降低能耗。为了避免无人机在编队过程中发生碰撞,引入了安全球的概念,提出了基于两个时隙连续运动的碰撞检测和运动后的占道检测来避免无人机之间的碰撞。基于博弈论思想,提出了基于利益最大化的无人机运动形态设定方法,包括自身利益最大化和编队利益最大化,使多架无人机在事先分配好的线性轨迹下快速合理地完成编队任务。最后,通过仿真验证,本文提出的基于分配概率的多无人机目标分配算法能有效减少总路径长度,基于利益最大化的无人机运动选择方法能有效完成任务编队。
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来源期刊
Journal of Systems Engineering and Electronics
Journal of Systems Engineering and Electronics 工程技术-工程:电子与电气
CiteScore
4.10
自引率
14.30%
发文量
131
审稿时长
7.5 months
期刊介绍: Information not localized
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