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A Distributed boundary detection algorithm for multi-robot systems

机译:一种多机器人系统的分布式边界检测算法

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We describe a distributed boundary detection algorithm suitable for use on multi-robot systems with dynamic network topologies. We assume that each robot has access to its local network geometry, which is the combination of a robot's network connectivity and the positions of its neighbors measured relative to itself. Our algorithm uses this information to classify robots as boundary or interior in one communications round, which is fast enough for rapidly changing networks. We use the local boundary classifications to create a robust boundary subgraph, and to determine if the boundary is an interior void or the exterior boundary. A proof of the key property of the boundary detection algorithm is provided, and all the algorithms are extensively tested on a swarm of 25-35 robots in rapidly changing network topologies.
机译:我们描述了一种适用于具有动态网络拓扑的多机器人系统的分布式边界检测算法。我们假设每个机器人都可以访问其本地网络几何形状,这是机器人的网络连接性及其邻居相对于自己的位置的组合。我们的算法使用此信息在一个通信回合中将机器人分类为边界或内部,这对于快速变化的网络而言足够快。我们使用局部边界分类来创建鲁棒的边界子图,并确定边界是内部空隙还是外部边界。提供了边界检测算法关键特性的证明,并且在快速变化的网络拓扑中,所有算法都在25-35个机器人群中进行了广泛测试。

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