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by Janusz Racz, Artur Dubrawski
http://www.cs.cmu.edu/afs/cs.cmu.edu/user/awd/www/irs94_racz_dubrawski.ps.gz
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Abstract:
Abstract. This paper presents a neural network based approach to a mobile robot positioning in front of a certain local object. The robot is equipped with ultrasonic range sensors mounted round the platform. We employ the Fuzzy-ARTMAP network for supervised learning of associations between vectors of sensors readouts and the robot's pose coordinates. In this approach, a world model in a form of a map, as well as its updating routine, become superflous for the considered problem solution. The system, trained on a real world data of a door neighborhood region reveals satisfactory performance, sufficient for a door passing task purposes. The proposed method of a mobile robot positioning may be efficiently applied in environments containing natural, geometrical beacons. 1
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