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An Evolutionary-Cooperative Model Based on Cellular Automata and Genetic Algorithms for the Navigation of Robots Under Formation Control

机译:基于蜂窝自动机和遗传算法的形成控制下的遗传算法的进化协作模型

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Formation control is the task of coordinating a group of robots to get into and to maintain a formation with a specific shape while moving in the environment. In this work we investigated models based on cellular automata applied to this task. We implemented methods previously described in the literature and found some limitations. Thus, an evolutionary-cooperative method is proposed, using the search power of a genetic algorithm along with the compact rules and simplified processing of cellular automata. The proposal required low computational infrastructure and was tested in a robotics simulator (Webots) with a team of 3 e-puck robots. The new model exhibited a better behaviour than their precursors in several scenarios, improving the robot's trajectory and formation maintenance.
机译:形成控制是协调一组机器人进入并在环境中移动时以特定形状保持形成的任务。在这项工作中,我们研究了基于蜂窝自动机应用于此任务的模型。我们实施了先前在文献中描述的方法,发现了一些限制。因此,提出了一种使用遗传算法的搜索能力以及蜂窝自动机的简化处理来提出进化协作方法。该提案需要低计算基础设施,并在机器人模拟器(博彩)中进行测试,其中一支由3个E-PACK机器人团队进行测试。新模型在几种情况下表现出比其前体更好的行为,提高了机器人的轨迹和形成维护。

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