Cross-modal body representation based on visual attention by saliency

Abstract

In performing various kinds of tasks, body representation is one of the most fundamental issues for physical agents (humans, primates, and robots). Especially during tool-use by Japanese macaque monkeys, neurophysiological evidence shows that the representation can be dynamically reconstructed by spatio-temporal integration of different sensor modalities so that it can be adaptive to environmental changes [1]. However, to construct such a representation, an issue to be solved is how to associate which information among various sensory data. This paper presents a method that constructs cross-modal body representation from vision, touch, and proprioception. When the robot touches something, the activation of tactile sense triggers the construction process of the visual receptive field for body parts that can be found by visual attention based on saliency map and consequently regarded as the end effector. Simultaneously, proprioceptive information is associated with this visual receptive field to construct the cross-modal body representation. The computer simulation results are comparable to the activities of parietal neurons found in the Japanese macaque monkeys. Various conditions are also investigated so that what kind of information is important to generate the same results as findings in neurophysiology.