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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.
The traditional collaborative algorithm based on collision avoidance, team formation and aggregation rules has the tendency of cohesion and speed convergence, and it is difficult for the groups to carry out the grouping automatically under the stimulation of external information.Therefore, we propose a distributed collaboration that combines neighborhood following behaviors Control algorithm is proposed in this paper.On the basis of short-range rejection, long-distance attraction and speed-consistent behavior, this algorithm introduces the individual’s follow-up movement to the neighbor with the fastest change in the perceived distance and implements the external information through the dynamic update of the following target Under the action of the group self-organized grouping behavior, the simulation experiment verifies the feasibility of the algorithm and the grouping effectiveness.