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A centroidal Voronoi tessellation based intelligent control algorithm for the self-assembly path planning of swarm robots

机译:基于质心Voronoi细分的群体机器人自组装路径规划智能控制算法

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Swarm robots have been an active topic in the field of intelligent machines in recent years. Self-assembly is an important function of swarm robots that provides an effective way for building different kinds of configurations by autonomous docking. For a self-assembly process, the path planning control is a key technique. The present paper proposes a CVT (Centroidal Voronoi Tessellation) based intelligent control algorithm for the self-assembly path planning. It can enable swarm robots to move from an initial virtual region into the target virtual region by a synchronous collaborative scheduling method. Matlab simulations are performed on the self-assembly control of three typical configurations including the line-shape, cross-shape and H-shape. The time consumption is compared under different error conditions, the effectiveness of the new algorithm is validated and its limitation is also pointed out. Overall, this algorithm provides a promising way for the intelligent control of self-assembly path planning of swarm robots. (C) 2017 Elsevier Ltd. All rights reserved.
机译:近年来,群体机器人一直是智能机器领域的活跃主题。自组装是群体机器人的一项重要功能,它通过自主对接提供了一种有效的方式来构建各种配置。对于自组装过程,路径规划控制是一项关键技术。本文提出了一种基于CVT(Centroidal Voronoi Tessellation)的智能控制算法,用于自组装路径规划。它可以使群体机器人通过同步协作调度方法从初始虚拟区域移动到目标虚拟区域。 Matlab仿真是对三种典型配置的自组装控制执行的,包括线形,十字形和H形。比较了不同错误条件下的时间消耗,验证了新算法的有效性,并指出了其局限性。总体而言,该算法为群体机器人自组装路径规划的智能控制提供了一种有希望的方法。 (C)2017 Elsevier Ltd.保留所有权利。

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