Frequency-domain force measurements for discrete event contact recognition

Author

Hovland, G.E. ; McCarragher, B.J.

Author_Institution

Dept. of Eng., Australian Nat. Univ., Canberra, ACT, Australia

Volume

2

fYear

1996

fDate

22-28 Apr 1996

Firstpage

1166

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

Keywords

assembling; discrete event systems; force measurement; frequency-domain analysis; hidden Markov models; learning systems; mechanical contact; monitoring; pattern recognition; production control; Baum-Welch re-estimation algorithm; discrete event contact recognition; force measurements; force signals; frequency-domain; hidden Markov models; planar assembly task; process monitoring; robotic system; Event detection; Force measurement; Frequency measurement; Hidden Markov models; Information technology; Monitoring; Robotic assembly; Robots; Telerobotics; Torque measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on

Conference_Location

Minneapolis, MN

ISSN

1050-4729

Print_ISBN

0-7803-2988-0

Type

conf

DOI

10.1109/ROBOT.1996.506865

Filename

506865