Frequency-domain force measurements for discrete event contact recognition

Abstract

Discrete event recognition based on force measurements in the frequency-domain, is presented. The force signals arise from interaction between the workpiece and the environment in a planar assembly task. The discrete events are modeled as hidden Markov models (HMMs), where the models are trained off-line with the Baum-Welch re-estimation algorithm. After the HMMs have been trained, we use them online in a robotic system to recognise discrete events as they occur. Event recognition with an accuracy as high as 98% was accomplished in 0.5-0.6 s with a relatively small training set.