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A Distributed Model for Mobile Robot Environment-Learning and Navigation

Author(s)
Mataric, Maja J.
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Abstract
A 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.
Date issued
1990-05-01
URI
http://hdl.handle.net/1721.1/7027
Other identifiers
AITR-1228
Series/Report no.
AITR-1228

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  • AI Technical Reports (1964 - 2004)

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