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Spatial Learning for Navigation in Dynamic Environments

By Brian Yamauchi and Randall Beer


This article describes techniques that have been developed for spatial learning in dynamic environments and a mobile robot system, ELDEN, that integrates these techniques for exploration and navigation in dynamic environments. In this research, we introduce the concept of adaptive place networks, incrementally-constructed spatial representations that incorporate variable-confidence links to model uncertainty about topological adjacency. These networks guide the robot's navigation while constantly adapting to any topological changes that are encountered. ELDEN integrates these networks with a reactive controller that is robust to transient changes in the environment and a relocalization system that uses evidence grids to recalibrate dead reckoning. Footnotes 1 Manuscript received . . . 2 Department of Computer Engineering and Science, Case Western Reserve University, Cleveland, OH, 44106, USA (email:, URL:

Topics: Figure Captions
Year: 1996
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