A Force Recognition System for Distinguishing Click Responses of Various Objects

Abstract

This study proposes a technique for determining completion of robotic tasks considering a characteristics that some features on force responses are common among various objects. In particular, this paper focuses on the click response because its pattern is common to many objects, although the magnitude of the response differs depending on the object. A discriminator for detecting the click response based on the force sensor values, which combines mel-frequency cepstral coefficient and time-delay neural network is introduced. Based on this discriminator, how to improve the generalization performance to untrained objects is investigated to detect click responses in general for various objects. The experimental results show that the performance can be improved by including several kinds of objects with close time constants and different amplitudes of click responses in the training data.