Accelerated Patch Sorting by a Robotic Swarm

A. Vardy
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引用次数: 14

Abstract

We introduce a new method for distributed object sorting by a swarm of robots. The patch sorting task involves pushing randomly distributed objects into homogeneous clusters. Most existing methods do not make use of vision and are therefore restricted to sensing the objects that lie immediately in front of the robot. We utilize vision both to sense the presence of a cluster and judge its homogeneity, and to seek out distant clusters or isolated objects to pick up. The objects to be sorted are coloured pucks. We present results using a realistic simulation which shows that a simple guidance strategy based on the size of distant clusters can dramatically accelerate the sorting process.
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机器人群加速补丁排序
提出了一种由机器人群进行分布式目标排序的新方法。补丁排序任务包括将随机分布的对象推入同类簇。大多数现有的方法没有利用视觉,因此仅限于感知机器人前方的物体。我们利用视觉来感知集群的存在和判断其同质性,并寻找遥远的集群或孤立的物体来拾取。要分类的物体是彩色的冰球。我们给出了一个真实的仿真结果,表明基于距离簇大小的简单制导策略可以显着加快排序过程。
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