基于邻域跟随的群集系统分群控制算法

传统基于避撞、组队和聚集规则的个体运动协同算法具有内聚和速度一致趋势,群体在外部信息刺激下难以自发实施分群.为此,提出一种融合了邻域跟随行为的分布式协同控制算法.该算法在短距排斥、长距吸引和速度一致行为的基础上,引入个体对于其感知域内间距变化最快的邻居的跟随运动,并通过对跟随目标的动态更新,实现了外部信息作用下群体的自组织分群行为.仿真实验验证了算法的可行性和分群有效性.

Fission control algorithm for swarm based on local followinginteraction

Traditionally, the motion cooperative algorithms for swarm base on the interaction rules of attraction, repulsion
and alignment have the properties of group cohesion and velocity consensus, which prevent the splitting of the group under
multiple external stimulus. Therefore, a distributed motion cooperative algorithm is proposed by integrating a following
interaction with the behaviors of long-range attraction, short-range repulsion and consensus-based alignment, where the
following behavior is applied locally to one of the proximity neighbors with the fastest change of inter-individuals distance
and vanished after a short acting time. Then, the swarm can split autonomously into multiple sub-groups when multiple
stimulus are introduced. Finally, simulation results show the feasibility and effectiveness of the proposed algorithm for the
fission control.