Image feature generation by visio-motor map learning towards selective attention

Visual attention is one of the key issues for robots to accomplish the given tasks, and the existing methods specify the image features and attention control scheme in advance according to the task and the robot. However, in order to cope with environmental changes and/or task variations, the robot should construct its own attention mechanism. As the first step towards selective attention, this paper presents a method for image feature generation by visio-motor map learning for a mobile robot. The teaching data construct the visio-motor mapping that constrains the image feature generation and state vector estimation as well. The resultant image feature and state vector are nothing but task-oriented. The method is applied to indoor navigation and soccer shooting tasks, and a discussion is given.