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A Distributed Model for Mobile Robot Environment-Learning and Navigation

dc.date.accessioned2004-10-20T20:22:47Z
dc.date.accessioned2018-11-24T10:22:46Z
dc.date.available2004-10-20T20:22:47Z
dc.date.available2018-11-24T10:22:46Z
dc.date.issued1990-05-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/7027
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/7027
dc.description.abstractA distributed method for mobile robot navigation, spatial learning, and path planning is presented. It is implemented on a sonar-based physical robot, Toto, consisting of three competence layers: 1) Low-level navigation: a collection of reflex-like rules resulting in emergent boundary-tracing. 2) Landmark detection: dynamically extracts landmarks from the robot's motion. 3) Map learning: constructs a distributed map of landmarks. The parallel implementation allows for localization in constant time. Spreading of activation computes both topological and physical shortest paths in linear time. The main issues addressed are: distributed, procedural, and qualitative representation and computation, emergent behaviors, dynamic landmarks, minimized communication.en_US
dc.format.extent9091597 bytes
dc.format.extent7065742 bytes
dc.language.isoen_US
dc.titleA Distributed Model for Mobile Robot Environment-Learning and Navigationen_US


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