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Constructing a cohesive pattern for collective navigation based on a swarm of robotics

机译:基于机器人的群体构建集体导航的凝聚力模式

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摘要

Swarm robotics carries out complex tasks beyond the power of simple individual robots. Limited capabilities of sensing and communication by simple mobile robots have been essential inspirations for aggregation tasks. Aggregation is crucial behavior when performing complex tasks in swarm robotics systems. Many difficulties are facing the aggregation algorithm. These difficulties are as such: this algorithm has to work under the restrictions of no information about positions, no central control, and only local information interaction among robots. This paper proposed a new aggregation algorithm. This algorithm combined with the wave algorithm to achieve collective navigation and the recruitment strategy. In this work, the aggregation algorithm consists of two main phases: the searching phase, and the surrounding phase. The execution time of the proposed algorithm was analyzed. The experimental results showed that the aggregation time in the proposed algorithm was significantly reduced by 41% compared to other algorithms in the literature. Moreover, we analyzed our results using a one-way analysis of variance. Also, our results showed that the increasing swarm size significantly improved the performance of the group.
机译:群机器人进行超越了简单的个人机器人的电源复杂的任务。通过简单的移动机器人传感和通信的能力有限一直是聚集任务必不可少的灵感。聚合是在表演群体机器人系统复杂的任务时,至关重要的行为。许多困难所面临的聚合算法。这些困难是这样:该算法下的任何有关位置的信息,没有中央控制和机器人之间只有本地信息交互的限制工作。本文提出了一种新的聚合算法。该算法与波算法相结合,以实现集体导航和招聘策略。在这项工作中,聚合算法由两个主要阶段:搜索阶段,和周围的阶段。该算法的执行时间进行了分析。实验结果表明,在所提出的算法的聚集时间显著降低了41%相比,在文献中其它算法。此外,我们使用方差单向分析来分析我们的结果。此外,我们的结果表明,增加群体大小显著改善组的性能。

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