Path Planning for Robot Navigation u sing View Sequences

Navigation based on visual memories is very common among humans. However, planning long trips requires also a more sophisticated represen- tation of the environment, such as a topological map. This paper describes a system that learns paths by storing sequences of images and image information in a Sparse Distributed Memory. Connections between paths are detected by exploring similarities in the im- ages, and a topological representation of the connec- tions is created. The robot is then able to plan paths and skip from one path to another at the connection points. The system was tested under reconstitutions of country and urban environments, and it was able to successfully plan paths and navigate.

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