Position Estimation and Modeling of a Flexible Industrial Robot
2004 (English)Report (Other academic)
A sensor fusion technique is presented and it is shown to achieve good estimates of the position for a 3 degrees-of-freedom industrial robot model. By using an accelerometer the estimate of the tool position accuracy can be improved. The computation of the position is formulated as a Bayesian estimation problem and two solutions are proposed. One using the extended Kalman ﬁlter and one using the particle ﬁlter. Since the aim is to use the positions estimates to improve trajectory tracking with an iterative learning control method, no computational constraints arise. In an extensive simulation study the performance is compared to the Cramér-Rao lower bound. A signiﬁcant improvement in position accuracy is achieved using the sensor fusion technique.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2004. , 9 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2629
Industrial robots, Estimation, Extended Kalman filter, Estimation algorithms
IdentifiersURN: urn:nbn:se:liu:diva-55998ISRN: LiTH-ISY-R-2629OAI: oai:DiVA.org:liu-55998DiVA: diva2:316737