凸多边形多智能体避障系统的分布式群集控制

IF 4.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Yaxin Li, Yingmin Jia
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引用次数: 0

摘要

研究了具有障碍物和有限通信区域的二阶凸多边形多智能体系统的分布式群集控制问题。现有研究往往将智能体形状简化为粒子或圆形,忽略了无人船、无人车等真实形状,导致空间资源利用效率低下。为解决这一问题,提出了一种计算凸多边形体间相对距离的新方法。基于这一相对距离,设计了一个包含引力和斥力的势函数。吸引函数促进内聚,排斥函数防止碰撞。采用有限截止函数来设计斥力函数,以避免两体距离过近时产生无限斥力。当智能体与障碍物之间的距离小于安全距离时,为其运动设置蜂拥参考轨迹,为其避障设置避障参考轨迹。所提出的控制律将势函数和参考轨迹相结合,实现了群集和避障。通过在无障碍物和有障碍物环境中对不同形状的智能体进行仿真,验证了所提控制算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed flocking control of convex polygonal multiagent systems with obstacle avoidance
This paper studies the distributed flocking control problem for second-order convex polygonal multiagent systems with obstacles and limited communication regions. Existing research often simplifies agent shapes to particles or circles, neglecting the real shapes like unmanned ships and vehicles, which can result in inefficient use of spatial resources. To solve this problem, a new method for calculating the relative distance between convex polygonal agents is introduced. A potential function incorporating attractive and repulsive forces is designed based on this relative distance. The attractive function promotes cohesion, while the repulsive function prevents collisions. A finite cut-off function is used to design the repulsive function to avoid infinite repulsion when agents are too close. A flocking reference trajectory is set for movement, and an obstacle-avoidance reference trajectory is assigned for avoiding obstacles when the distance between the agent and the obstacle is less than the safe distance. The proposed control law integrates potential function and reference trajectory to achieve both flocking and obstacle avoidance. The effectiveness of the proposed control algorithm is validated through simulation on agents of different shapes in both obstacle-free and obstacle environments.
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来源期刊
CiteScore
7.30
自引率
14.60%
发文量
586
审稿时长
6.9 months
期刊介绍: The Journal of The Franklin Institute has an established reputation for publishing high-quality papers in the field of engineering and applied mathematics. Its current focus is on control systems, complex networks and dynamic systems, signal processing and communications and their applications. All submitted papers are peer-reviewed. The Journal will publish original research papers and research review papers of substance. Papers and special focus issues are judged upon possible lasting value, which has been and continues to be the strength of the Journal of The Franklin Institute.
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