Tool Position Estimation of a Flexible Industrial Robot using Recursive Bayesian Methods
2012 (English)In: Proceedings of the 2012 IEEE International Conference on Robotics and Automation, 2012, 5234-5239 p.Conference paper (Refereed)
A sensor fusion method for state estimation of a flexible industrial robot is presented. By measuring the acceleration at the end-effector, the accuracy of the arm angular position is improved significantly when these measurements are fused with motor angle observation. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; one using the extended Kalman filter (EKF) and one using the particle filter (PF). The technique is verified on experiments on the ABB IRB4600 robot, where the accelerometer method is showing a significant better dynamic performance, even when model errors are present.
Place, publisher, year, edition, pages
2012. 5234-5239 p.
Bayes methods, Kalman filters, Flexible manipulators, Position control, State estimation
IdentifiersURN: urn:nbn:se:liu:diva-87587DOI: 10.1109/ICRA.2012.6224625ISI: 000309406705041ISBN: 978-1-4673-1403-9ISBN: 978-1-4673-1404-6OAI: oai:DiVA.org:liu-87587DiVA: diva2:589538
2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA, 14-18 May, 2012
FunderVinnovaSwedish Foundation for Strategic Research