Navigation of Distinct Euclidean Particles via Hierarchical Clustering

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Departmental Papers (ESE)
General Robotics, Automation, Sensing and Perception Laboratory
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GRASP
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Electrical and Computer Engineering
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Systems Engineering
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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.

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2014-08-01
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Departmental Papers (ESE)
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2023-05-17T11:09:51.000
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For more information: Kod*Lab (http://kodlab.seas.upenn.edu/Omur/WAFR2014)
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@InProceedings{arslan_guralnik_kod_WAFR2014, Title = {Navigation of Distinct Euclidean Particles via Hierarchical Clustering}, Author = {Omur Arslan and Dan P. Guralnik and Daniel E. Koditschek}, Booktitle = {2014 International Workshop on the Algorithmic Foundations of Robotics (WAFR2014)}, Year = {2014}, Month = {August}, }
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