Brain mechanisms for robotic object pose estimation

Abstract

Integration of multiple visual cues provides natural systems with superior abilities in dealing with nearby objects. This research is aimed at verifying if robotic systems could also benefit from the merging of different visual cues of the same stimulus. A computational model of stereoscopic and perspective orientation estimators, merged according to different criteria, is implemented on a robotic setup and tested in different conditions. Experimental results suggest that the principle of cue integration can make robot sensory systems more reliable and robust. The same results compared with data from human studies show that the model is able to reproduce some well-known neuropsychological effects.