Neural Behavior Chain Learning of Mobile Robot Actions

Abstract EN

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.