Tool position estimation of a flexible industrial robot using recursive bayesian methods [Elektronisk resurs] /Patrik Axelsson, Rickard Karlsson, Mikael Norrlöf
Text
E-bokEngelska2011
Förlag, utgivningsår, omfång ...
Linköping :Department of Electrical Engineering, Linköpings universitet,2011
6 s.
Nummerbeteckningar
LIBRIS-ID:13993780
Serie
LiTH-ISY-R,1400-3902 ;3024
Anmärkningar
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.