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Cooperative Self-Organization in a Heterogeneous Swarm Robotic System

机译:异构群机器人系统中的合作自组织

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We study how a swarm robotic system consisting of two different types of robots can solve a foraging task. The first type of robots are small wheeled robots, called foot-bots, and the second type are flying robots that can attach to the ceiling, called eye-bots. While the foot-bots perform the actual foraging, i.e. they move back and forth between a source and a target location, the eye-bots are deployed in stationary positions against the ceiling, with the goal of guiding the foot-bots. The key component of our approach is a process of mutual adaptation, in which foot-bots execute instructions given by eye-bots, and eye-bots observe the behavior of foot-bots to adapt the instructions they give. Through a simulation study, we show that this process allows the system to find a path for foraging in a cluttered environment. Moreover, it is able to converge onto the shortest of two paths, and spread over different paths in case of congestion. Since our approach involves mutual adaptation between two sub-swarms of different robots, we refer to it as cooperative self-organization. This is to our knowledge the first work that investigates such a system in swarm robotics.
机译:我们研究了由两种不同类型的机器人组成的群体机器人系统如何解决觅食任务。第一种类型的机器人是称为脚机器人的小型轮式机器人,第二种类型是可以固定在天花板上的飞行机器人,称为护眼机器人。当步行机器人执行实际的觅食时,即它们在源和目标位置之间来回移动,而步行机器人则以固定位置部署在天花板上,以引导步行机器人。我们方法的关键组成部分是相互适应的过程,其中,步行机器人执行眼机器人给出的指令,而眼机器人则观察足机器人的行为以适应它们给出的指令。通过仿真研究,我们表明此过程使系统能够找到在杂乱环境中觅食的路径。而且,它能够收敛到两条路径中最短的一条,并在拥塞的情况下分布在不同的路径上。由于我们的方法涉及不同机器人的两个子群之间的相互适应,因此我们将其称为协作自组织。据我们所知,这是研究群体机器人技术中此类系统的第一项工作。

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