Using motor representations for topological mapping and navigation

We propose the use of motor vocabulary, that express a robot’s specific motor capabilities, for topological mapbuilding and navigation. First, the motor vocabulary is created automatically through an imitation behaviour where the robot learns about its own motor repertoire, by following a tutor and associating its own motion perception to motor words. The learnt motor representation is then used for building the topological map. The robot is guided trough the environment and automatically captures relevant (omnidirectional) images and associates motor words to links between places in the topological map. Finally, the created map is used for navigation, by invoking sequences of motor words that represent the actions for reaching a desired goal. In addition, a reflex-type behaviour based on optical flow extracted from omnidirectional images is used to avoid lateral collisions during navigation. The relation between motor vocabulary and imitation is stressed by the recent findings in neurophysiology, of visuomotor (mirror) neurons that may represent an internal motor representation related to the animal’s capacity of imitation. This approach provides a natural adaptation between the robot’s motion capabilities, the environment representations (maps) and navigation processes. Encouraging results are presented and discussed.