Bayesian State Estimation of a Flexible Industrial Robot [Elektronisk resurs]

• A sensor fusion method for state estimation of a flexible industrial robot is developed. By measuring the acceleration at the end-effector, the accuracy of the arm angular position, as well as the estimated position of the end-effector are improved. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; the extended Kalman filter and the particle filter. In a simulation study on a realistic flexible industrial robot, the angular position performance is shown to be close to the fundamental Cramér-Rao lower bound. The technique is also verified in experiments on an ABB robot, where the dynamic performance of the position for the end-effector is significantly improved. 

Ämnesord

Engineering and Technology  (hsv)

Electrical Engineering, Electronic Engineering, Information Engineering  (hsv)

Control Engineering  (hsv)

Teknik och teknologier  (hsv)

Elektroteknik och elektronik  (hsv)

Reglerteknik  (hsv)

TECHNOLOGY  (svep)

Information technology  (svep)

Automatic control  (svep)

TEKNIKVETENSKAP  (svep)

Informationsteknik  (svep)

Reglerteknik  (svep)

Indexterm och SAB-rubrik

Industrial robot

Positioning

Estimation

Particle filter

Extended Kalman filter

Cramér–Rao lower bound