Multi-target pinning flocking algorithm combined with local adaptive tracking

Abstract

Abstract:

In view of the problem that the traditional multi-Agent flocking algorithms are not universal when a single target tracking is considered, and the existing multi-target flocking control is controlled by centralized coordinated movement based on global target information, rather than the distributed coordinated control based on local destination information. Therefore, a distributed motion cooperative pinning flocking algorithm combined with local adaptive tracking was presented. First, the local adaptive tracking strategy based on separation, aggregation, velocity matching and direct feedback was introduced to achieve local following interaction dynamically. Secondly, a node influence index evaluation algorithm based on pinning idea was presented to select the m information Agents to track m targets, playing an important role in simulating external information; different information individuals indirectly lead individuals with a different target to track the respective target due to local adaptive detection mechanism. Finally, a new class of potential functions of aggregation and exclusion with the advantages of less adjustable parameters and high efficiency was designed; the Agents with same target could gather in the process of tracking, and the Agents with different target could avoid collision based on the potential function. The experimental results under three dimensional space show the feasibility and effectiveness of multi-target tracking.

摘要：

针对以往的多智能体蜂拥控制算法在考虑单个目标追踪情形时不具普适性,以及现有的多目标蜂拥控制都是基于全局目标信息来进行集中式协调控制,而非基于局部目标信息下的分布式协调控制的问题,提出一种融合局部自适应检测机制的分布式协同牵制蜂拥算法。首先,算法在分离、聚合、速度匹配和引导反馈的基础上,引入局部自适应追踪策略,实现智能体的局部动态跟随运动；其次,受牵制思想启发,根据节点影响力指数评估算法选取m个信息个体分别向m个目标进行多目标追踪,起到模拟外部信息的作用,不同的信息个体会由于局部自适应检测机制间接地引领周围局部个体向不同目标进行追踪；最后,设计一类新的聚集和排斥势能函数,实现相同目标智能体的聚集,以及不同目标智能体的避碰,具有可调参数少和效率高的优势。通过三维仿真实验验证了算法的多目标追踪可行性和有效性。

CLC Number:

TP18

WANG Hai LUO Qi XU Tengfei. Multi-target pinning flocking algorithm combined with local adaptive tracking[J]. Journal of Computer Applications, 2014, 34(12): 3428-3432.

王海罗琦徐腾飞. 融合局部自适应追踪的多目标牵制蜂拥算法[J]. 计算机应用, 2014, 34(12): 3428-3432.

References

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