动态环境下基于极限环的多智能体协调

Sajjad Manzoor, Youngjin Choi
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引用次数: 1

摘要

提出了一种新的基于神经振荡器的多机器人编队与导航极限环方法。一组点机器人被引导向目标移动,并在目标周围形成一个圆形。首先研究了无障碍物静止目标的避障算法,然后将其推广到动态目标,进而推广到包括静态和动态障碍物的避障算法。利用神经振荡器极限环的吸引特性,使机器人能够绕任意半径的目标进行圆周运动。一组追逐的机器人以这样一种方式到达目标,即它们与目标保持期望的距离,并保持围绕目标的均匀分布角度。另一个发现是,通信(或传感器)矩阵的变化会使瞬态形成不同,尽管最终形状保持不变。最后,通过仿真验证了所提方法的有效性。
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Multi-agent coordination using limit cycles in dynamic environment
The paper presents a novel neural oscillator-based limit cycle approach for multiple robots formation and navigation. A group of point-robots is directed to move towards a target as well as to form a circular shape surrounding it. Initially the algorithm for a stationary target in absence of obstacle is developed, and then it is extended to dynamic target and further to an obstacle avoidance including static and dynamic obstacles. An attraction property of neural oscillator-based limit cycle is used for the robots to move towards circle around target with an arbitrary radius. The group of pursuing robots reaches the target in such a way that they remain at a desired distance from it keeping equally distributed angle around it. Another finding is that a change of communication (or sensor) matrix makes a transient formation to be different, though the final shape remains the same. Finally, the effectiveness of the proposed method is verified through several simulations.
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