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Navigation of Distinct Euclidean Particles via Hierarchical Clustering

机译:通过分层聚类导航不同的欧几里德粒子

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We present a centralized online (completely reactive) hybrid navigation algorithm for bringing a swarm of n perfectly sensed and actuated point particles in Euclidean d space (for arbitrary n and d) to an arbitrary goal configuration with the guarantee of no collisions along the way. Our construction entails a discrete abstraction of configurations using cluster hierarchies, and relies upon two prior recent constructions: (i) a family of hierarchy-preserving control policies and (ii) an abstract discrete dynamical system for navigating through the space of cluster hierarchies. Here, we relate the (combinatorial) topology of hierarchical clusters to the (continuous) topology of configurations by constructing "portals" - open sets of configurations supporting two adjacent hierarchies. The resulting online sequential composition of hierarchy-invariant swarming followed by discrete selection of a hierarchy "closer" to that of the destination along with its continuous instantiation via an appropriate portal configuration yields a computationally effective construction for the desired navigation policy.
机译:我们在欧几里德D空间(用于任意N和D)中,在欧几里德D空间(用于任意N和D)中的N个完全感测和致动点粒子的群体的集中在线(完全反应性)混合导航算法以任意的目标配置,以保证沿途没有碰撞。我们的施工需要使用群集层次结构进行离散的配置抽象,并依赖于两个先前的最近结构:(i)一个层次结构保留控制策略系列和(ii)一种抽象的离散动态系统,用于通过集群层次结构的空间导航。在这里,我们通过构建支持两个相邻层次结构的“门户” - 打开的配置,将分层集群的(组合)拓扑对(连续)拓扑进行了分层集群。由此产生的在线顺序组成的层级 - 不变蜂鸣的组成,然后通过适当的门户配置的连续实例化分离地选择层次结构“更接近”的层级“更接近”,产生了所需导航策略的计算有效结构。

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