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Bayesian State Esti...
Bayesian State Estimation of a Flexible Industrial Robot
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- Axelsson, Patrik, 1985- (författare)
- Linköpings universitet,Reglerteknik,Tekniska högskolan
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- Karlsson, Rickard (författare)
- Linköpings universitet,Reglerteknik,Tekniska högskolan
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- Norrlöf, Mikael (författare)
- Linköpings universitet,Reglerteknik,Tekniska högskolan
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(creator_code:org_t)
- Linköping : Linköping University Electronic Press, 2011
- Svenska 9 s.
- Relaterad länk:
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Abstract
Ämnesord
Stäng
- 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
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Nyckelord
- Industrial robot
- Positioning
- Estimation
- Particle filter
- Extended Kalman filter
- Cramér-Rao lower bound
Publikations- och innehållstyp
- vet (ämneskategori)
- rap (ämneskategori)