Neural Behavior Chain Learning of Mobile Robot Actions

This paper presents a visual/motor behavior learning approach, based on neural networks. We propose Behavior Chain Model (BCM) in order to create a way of behavior learning. Our behavior-based system evolution task is a mobile robot detecting a target and driving/acting towards it. First, the mappin...

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Bibliographic Details
Published in:Applied computational intelligence and soft computing 2012-01, Vol.2012 (2012), p.1-8
Main Authors: Banjanovic-Mehmedovic, Lejla, Golic, Dzenisan, Mehmedovic, Fahrudin, Havic, Jasna
Format: Article
Language:English
Subjects:
Behavior
Dynamic programming
Health sciences
Neural networks
Robotics
Robots
Studies
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Summary:This paper presents a visual/motor behavior learning approach, based on neural networks. We propose Behavior Chain Model (BCM) in order to create a way of behavior learning. Our behavior-based system evolution task is a mobile robot detecting a target and driving/acting towards it. First, the mapping relations between the image feature domain of the object and the robot action domain are derived. Second, a multilayer neural network for offline learning of the mapping relations is used. This learning structure through neural network training process represents a connection between the visual perceptions and motor sequence of actions in order to grip a target. Last, using behavior learning through a noticed action chain, we can predict mobile robot behavior for a variety of similar tasks in similar environment. Prediction results suggest that the methodology is adequate and could be recognized as an idea for designing different mobile robot behaviour assistance.
ISSN:1687-9724
1687-9732
DOI:10.1155/2012/382782