An Behavior-based Robotics
Neural Network Perception for Mobile Robot Guidance
Neural Network Perception for Mobile Robot Guidance
Vision and learning for intelligent human-computer interaction
Vision and learning for intelligent human-computer interaction
Visual Perception and Robotic Manipulation: 3D Object Recognition, Tracking and Hand-Eye Coordination (Springer Tracts in Advanced Robotics)
Perception through visuomotor anticipation in a mobile robot
Neural Networks
Codevelopmental Learning Between Human and Humanoid Robot Using a Dynamic Neural-Network Model
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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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.