Null-Space Compliance Variation for Safe Human-Robot Collaboration in Redundant Manipulators using Safety Control Barrier Functions
(2023) p.5903-5909- Abstract
- In this paper, Safety Control Barrier Functions (SCBFs) were used to adjust the null-space compliant behavior of a redundant robot to improve safety in Human–Robot Collaboration (HRC) without modifying the robot behavior with respect to its main Cartesian task. A Lyapunov function was included in an energy storage formulation compatible with strict passivity to provide global asymptotic stability guarantees for the null-space compliance variation, and the necessary conditions for stability were formulated as inequality constraints of the optimization problem used for the null-space compliance variation. Experimental validation was performed using a Franka Emika Panda robot for a collaborative assembly application and its results showed... (More)
- In this paper, Safety Control Barrier Functions (SCBFs) were used to adjust the null-space compliant behavior of a redundant robot to improve safety in Human–Robot Collaboration (HRC) without modifying the robot behavior with respect to its main Cartesian task. A Lyapunov function was included in an energy storage formulation compatible with strict passivity to provide global asymptotic stability guarantees for the null-space compliance variation, and the necessary conditions for stability were formulated as inequality constraints of the optimization problem used for the null-space compliance variation. Experimental validation was performed using a Franka Emika Panda robot for a collaborative assembly application and its results showed that safety can be improved by using SCBFs simultaneously to the optimization of the robot configuration, while employing a single degree of freedom. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/0a9580e9-55fc-4527-813b-b4b7c97c2f64
- author
- Salt Ducaju, Julian LU ; Olofsson, Björn LU ; Robertsson, Anders LU and Johansson, Rolf LU
- organization
- publishing date
- 2023-12
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proc. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)
- pages
- 7 pages
- external identifiers
-
- scopus:85182526597
- DOI
- 10.1109/IROS55552.2023.10342181
- project
- Human-Robot Collaboration for Kinesthetic Teaching
- RobotLab LTH
- language
- English
- LU publication?
- yes
- id
- 0a9580e9-55fc-4527-813b-b4b7c97c2f64
- date added to LUP
- 2023-12-04 10:09:05
- date last changed
- 2024-03-08 14:33:18
@inproceedings{0a9580e9-55fc-4527-813b-b4b7c97c2f64, abstract = {{In this paper, Safety Control Barrier Functions (SCBFs) were used to adjust the null-space compliant behavior of a redundant robot to improve safety in Human–Robot Collaboration (HRC) without modifying the robot behavior with respect to its main Cartesian task. A Lyapunov function was included in an energy storage formulation compatible with strict passivity to provide global asymptotic stability guarantees for the null-space compliance variation, and the necessary conditions for stability were formulated as inequality constraints of the optimization problem used for the null-space compliance variation. Experimental validation was performed using a Franka Emika Panda robot for a collaborative assembly application and its results showed that safety can be improved by using SCBFs simultaneously to the optimization of the robot configuration, while employing a single degree of freedom.}}, author = {{Salt Ducaju, Julian and Olofsson, Björn and Robertsson, Anders and Johansson, Rolf}}, booktitle = {{Proc. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023)}}, language = {{eng}}, pages = {{5903--5909}}, title = {{Null-Space Compliance Variation for Safe Human-Robot Collaboration in Redundant Manipulators using Safety Control Barrier Functions}}, url = {{https://lup.lub.lu.se/search/files/166086728/IROS2023_reviewed_clean_shortened_6_.pdf}}, doi = {{10.1109/IROS55552.2023.10342181}}, year = {{2023}}, }