Discrimination-based perception for robot touch

Abstract

Biomimetic tactile sensors often need a large amount of training to distinguish between a large number of different classes of stimuli. But when stimuli vary in one continuous property such as sharpness, it is possible to reduce training by using a discrimination approach rather than a classification approach. By presenting a biomimetic tactile sensing device, the TacTip, with a single exemplar of edge sharpness, the sensor was able to discriminate between unseen stimuli by comparing them to the trained exemplar. This technique reduces training time and may lead to more biologically relevant models of perceptual learning and discrimination.