Computing grip force and torque from finger nail images using Gaussian processesShow others and affiliations
2013 (English)In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, 2013, p. 4034-4039, article id 6696933Conference paper, Published paper (Refereed)
Abstract [en]
We demonstrate a simple approach with which finger force can be measured from nail coloration. By automatically extracting features from nail images of a finger-mounted CCD camera, we can directly relate these images to the force measured by a force-torque sensor. The method automatically corrects orientation and illumination differences. Using Gaussian processes, we can relate prepro-cessed images of the finger nail to measured force and torque of the finger, allowing us to predict the finger force at a level of 95%-98% accuracy at force ranges up to 10N, and torques around 90% accuracy, based on training data gathered in 90s. © 2013 IEEE.
Place, publisher, year, edition, pages
IEEE, 2013. p. 4034-4039, article id 6696933
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:umu:diva-206425DOI: 10.1109/IROS.2013.6696933Scopus ID: 2-s2.0-84893741429ISBN: 9781467363587 (print)OAI: oai:DiVA.org:umu-206425DiVA, id: diva2:1749115
Conference
2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013, Tokyo, Japan, November 3-8, 2013
2023-04-052023-04-052023-04-05Bibliographically approved