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  4. A Stable Adaptive Extended Kalman Filter for Estimating Robot Manipulators Link Velocity and Acceleration
 
conference paper

A Stable Adaptive Extended Kalman Filter for Estimating Robot Manipulators Link Velocity and Acceleration

Birjandi, Seyed Ali Baradaran
•
Khurana, Harshit  
•
Billard, Aude  
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January 1, 2023
2023 Ieee/Rsj International Conference On Intelligent Robots And Systems, Iros
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

One can estimate the velocity and acceleration of robot manipulators by utilizing nonlinear observers. This involves combining inertial measurement units (IMUs) with the motor encoders of the robot through a model-based sensor fusion technique. This approach is lightweight, versatile (suitable for a wide range of trajectories and applications), and straightforward to implement. In order to further improve the estimation accuracy while running the system, we propose to adapt the noise information in this paper. This would automatically reduce the system vulnerability to imperfect modelings and sensor changes. Moreover, viable strategies to maintain the system stability are introduced. Finally, we thoroughly evaluate the overall framework with a seven DoF robot manipulator whose links are equipped with IMUs.

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Type
conference paper
DOI
10.1109/IROS55552.2023.10342476
Web of Science ID

WOS:001133658800035

Author(s)
Birjandi, Seyed Ali Baradaran
Khurana, Harshit  
Billard, Aude  
Haddadin, Sami
Corporate authors
IEEE
Date Issued

2023-01-01

Publisher

IEEE

Publisher place

New York

Published in
2023 Ieee/Rsj International Conference On Intelligent Robots And Systems, Iros
ISBN of the book

978-1-6654-9190-7

Start page

346

End page

353

Subjects

Technology

•

Stability

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LASA  
Event nameEvent placeEvent date
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Detroit, MI

OCT 01-05, 2023

FunderGrant Number

Lighthouse Initiative Geriatronics by StMWi Bayern

IUK-1807-0007//IUK582/001

LongLeif GaPa gGmbH (Project Y)

European Union

871899

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Available on Infoscience
March 18, 2024
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/206309
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