Iterative Reference Learning for Cartesian Impedance Control of Robot Manipulators
Salt Ducaju, Julian LU
; Olofsson, Björn
LU
and Johansson, Rolf
LU
(2024)
IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
p.11171-11178
- Abstract
- In this paper, an iterative learning strategy was developed to improve trajectory tracking for an impedance-controlled robot manipulator. In this learning strategy, an update law was proposed to modify the Cartesian reference of an impedance controller. Also, the conditions that ensure its convergence considering the dynamics of the robot were derived. Finally, an experimental evaluation was performed using a Franka Emika Panda robot in two different robot tasks, and its results showed that robot task completion was achieved in a lower number of iterations, while maintaining a smooth physical interaction between the robot and its surroundings.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/5dc7a6ae-c915-4d61-8803-5b37eb225b5e
- author
- Salt Ducaju, Julian
LU
; Olofsson, Björn
LU
and Johansson, Rolf
LU
- organization
- publishing date
- 2024
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- pages
- 8 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024
- conference location
- Abu Dabi, United Arab Emirates
- conference dates
- 2024-10-14 - 2024-10-18
- external identifiers
-
- scopus:85216446376
- ISBN
- 979-8-3503-7770-5
- 979-8-3503-7771-2
- DOI
- 10.1109/IROS58592.2024.10801796
- project
- RobotLab LTH
- Human-Robot Collaboration for Kinesthetic Teaching
- language
- English
- LU publication?
- yes
- id
- 5dc7a6ae-c915-4d61-8803-5b37eb225b5e
- date added to LUP
- 2025-01-07 19:33:34
- date last changed
- 2025-07-17 10:48:21
@inproceedings{5dc7a6ae-c915-4d61-8803-5b37eb225b5e,
abstract = {{In this paper, an iterative learning strategy was developed to improve trajectory tracking for an impedance-controlled robot manipulator. In this learning strategy, an update law was proposed to modify the Cartesian reference of an impedance controller. Also, the conditions that ensure its convergence considering the dynamics of the robot were derived. Finally, an experimental evaluation was performed using a Franka Emika Panda robot in two different robot tasks, and its results showed that robot task completion was achieved in a lower number of iterations, while maintaining a smooth physical interaction between the robot and its surroundings.}},
author = {{Salt Ducaju, Julian and Olofsson, Björn and Johansson, Rolf}},
booktitle = {{2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}},
isbn = {{979-8-3503-7770-5}},
language = {{eng}},
pages = {{11171--11178}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Iterative Reference Learning for Cartesian Impedance Control of Robot Manipulators}},
url = {{https://lup.lub.lu.se/search/files/206302733/IROS24.pdf}},
doi = {{10.1109/IROS58592.2024.10801796}},
year = {{2024}},
}