Neural Behavior Chain Learning of Mobile Robot Actions. (6th December 2012)

• Record Type: Journal Article
• Authors: Banjanovic-Mehmedovic, Lejla; Golic, Dzenisan; Mehmedovic, Fahrudin; Havic, Jasna
• Other Names: Saravanan R. Academic Editor.
• Is Part Of: Applied computational intelligence and soft computing. Volume 2012(2012)
• Publication Date: 2012-12-06
• Subjects: Computational intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• DOI: 10.1155/2012/382782
• Languages: English
• ISSNs: 1687-9724

Abstract

Abstract : 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.