Counter-ant algorithm for evolving multirobot collaboration

Abdelhak Chatty, I. Kallel, A. Alimi
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引用次数: 13

Abstract

The use of multirobot systems, is affecting our society in a fundamental way; from their use in hazardous environments, to their application in automated environmental cleanup. In an unknown environment, one of the most important problem related to multirobot systems, is to decide how to coordinate actions in order to achieve tasks in an optimal way. Ant algorithms are proved to be very useful in solving such distributed control problems. We introduce in this paper a modified version of the known ant algorithm, called Counter-Ant Algorithm (CAA). Indeed, the robots' collaborative behaviour is based on repulsion instead of attraction to pheromone, which is a chemical matter open to evaporation and representing the core of ants' cooperation. In order to test the performance of our CAA, we implement, simulate and test our algorithm in a generic multirobot environment. In practical terms, the subdivision of the cleaning space is achieved in emergent and evolving way. A series of simulations show the usefulness of our algorithm for adaptive and cooperative cleanup.
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进化多机器人协作的反蚁算法
多机器人系统的使用,正从根本上影响着我们的社会;从它们在危险环境中的使用,到它们在自动环境清理中的应用。在未知环境下,多机器人系统的一个重要问题是如何协调行动,以最优方式完成任务。蚁群算法被证明在解决这种分布式控制问题方面非常有用。本文介绍了一种已知蚂蚁算法的改进版本,称为反蚂蚁算法(anti - ant algorithm, CAA)。事实上,机器人的合作行为是基于对信息素的排斥而不是吸引,信息素是一种容易蒸发的化学物质,代表了蚂蚁合作的核心。为了测试我们的CAA的性能,我们在一个通用的多机器人环境中实现、模拟和测试了我们的算法。在实践中,清洁空间的细分是以突现和演化的方式实现的。一系列的仿真表明了我们的算法在自适应和协作清理方面的有效性。
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