Joint Stiction Avoidance with Null-Space Motion in Real-Time Model Predictive Control for Redundant Collaborative Robots
(2021) 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021 In IEEE International Conference on Robot and Human Interactive Communication, RO-MAN p.307-314- Abstract
Model Predictive Control (MPC) is an efficient point-to-point trajectory-generation method for robots that can be used in situations that occur under time constraints. The motion plan can be recalculated online to increase the accuracy of the trajectory when getting close to the goal position. We have implemented this strategy in a Franka Emika Panda robot, a redundant collaborative robot, by extending previous research that was performed on a 6-DOF robot. We have also used null-space motion to ensure a continuous movement of all joints during the entire trajectory execution as an approach to avoid joint stiction and allow accurate kinesthetic teaching. As is conventional for collaborative and industrial robots, the Panda robot is... (More)
Model Predictive Control (MPC) is an efficient point-to-point trajectory-generation method for robots that can be used in situations that occur under time constraints. The motion plan can be recalculated online to increase the accuracy of the trajectory when getting close to the goal position. We have implemented this strategy in a Franka Emika Panda robot, a redundant collaborative robot, by extending previous research that was performed on a 6-DOF robot. We have also used null-space motion to ensure a continuous movement of all joints during the entire trajectory execution as an approach to avoid joint stiction and allow accurate kinesthetic teaching. As is conventional for collaborative and industrial robots, the Panda robot is equipped with an internal controller, which allows to send position and velocity references directly to the robot. Therefore, null-space motion can be added directly to the MPC-generated velocity references. The observed trajectory deviation caused by discretization approximations of the Jacobian matrix when implementing null-space motion has been corrected experimentally using sensor feedback for the real-time velocity-reference recalculation and by performing a fast sampling of the null-space vector. Null-space motion has been experimentally seen to contribute to reducing the friction torque dispersion present in static joints.
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- author
- Salt Ducaju, Julian M. LU ; Olofsson, Bjorn LU ; Robertsson, Anders LU and Johansson, Rolf LU
- organization
- publishing date
- 2021-08-08
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
- series title
- IEEE International Conference on Robot and Human Interactive Communication, RO-MAN
- pages
- 8 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
- conference location
- Virtual, Vancouver, Canada
- conference dates
- 2021-08-08 - 2021-08-12
- external identifiers
-
- scopus:85115100144
- ISSN
- 1944-9437
- 1944-9445
- ISBN
- 9781665404921
- DOI
- 10.1109/RO-MAN50785.2021.9515514
- project
- RobotLab LTH
- Human-Robot Collaboration for Kinesthetic Teaching
- language
- English
- LU publication?
- yes
- id
- fb129a30-a41d-401a-8b5e-0c83a97a53fb
- date added to LUP
- 2021-10-04 11:13:11
- date last changed
- 2024-09-22 02:19:28
@inproceedings{fb129a30-a41d-401a-8b5e-0c83a97a53fb, abstract = {{<p>Model Predictive Control (MPC) is an efficient point-to-point trajectory-generation method for robots that can be used in situations that occur under time constraints. The motion plan can be recalculated online to increase the accuracy of the trajectory when getting close to the goal position. We have implemented this strategy in a Franka Emika Panda robot, a redundant collaborative robot, by extending previous research that was performed on a 6-DOF robot. We have also used null-space motion to ensure a continuous movement of all joints during the entire trajectory execution as an approach to avoid joint stiction and allow accurate kinesthetic teaching. As is conventional for collaborative and industrial robots, the Panda robot is equipped with an internal controller, which allows to send position and velocity references directly to the robot. Therefore, null-space motion can be added directly to the MPC-generated velocity references. The observed trajectory deviation caused by discretization approximations of the Jacobian matrix when implementing null-space motion has been corrected experimentally using sensor feedback for the real-time velocity-reference recalculation and by performing a fast sampling of the null-space vector. Null-space motion has been experimentally seen to contribute to reducing the friction torque dispersion present in static joints.</p>}}, author = {{Salt Ducaju, Julian M. and Olofsson, Bjorn and Robertsson, Anders and Johansson, Rolf}}, booktitle = {{2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021}}, isbn = {{9781665404921}}, issn = {{1944-9437}}, language = {{eng}}, month = {{08}}, pages = {{307--314}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE International Conference on Robot and Human Interactive Communication, RO-MAN}}, title = {{Joint Stiction Avoidance with Null-Space Motion in Real-Time Model Predictive Control for Redundant Collaborative Robots}}, url = {{https://lup.lub.lu.se/search/files/160718327/RO_MAN21_FINAL_5_.pdf}}, doi = {{10.1109/RO-MAN50785.2021.9515514}}, year = {{2021}}, }