Task-relevant relaxation network for visuo-motory systems

摘要

The basic idea of our approach is to avoid the separation of perception and the generation of action. Therefore, information extracted from the environment is selected according to the relevance of the system's intended action. Task-specific attention emerges in an attention selection map from a competition among several hypotheses in consideration of task relevant subgoals. This decision initiates the emergence of a task-specific focus of attention in a saliency map which refers to a textured or coloured region in a scene. The networks underlying the attention selection map and the saliency map consist of interacting columns with local excitatory and global inhibitory coupled feedback. In the attention selection map lateral cooperation is used as a way to integrate task pertinent subgoals. Implemented subgoals are the size of regions, the security of a classification hypothesis and the valuation of the hypothesis for the task. The performance is demonstrated on a real-world selection of textured objects for a robot grasping task.