Robot Cartesian Compliance Variation for Safe Kinesthetic Teaching using Safety Control Barrier Functions
(2022) IEEE 18th International Conference on Automation Science and Engineering (IEEE CASE2022) p.2259-2259- Abstract
- Kinesthetic teaching allows human operators to reprogram part of a robot’s trajectory by manually guiding the robot. To allow kinesthetic teaching, and also to avoid any harm to both the robot and its environment, Cartesian impedance control is here used for trajectory following. In this paper, we present an online method to modify the compliant behavior of a robot toward its environment, so that undesired parts of the robot’s workspace are avoided during kinesthetic teaching. The stability of the method is guaranteed by a well-known passivity-based energy-storage formulation that has been modified to include a strict Lyapunov function, i.e., its time derivative is a globally negative-definite function. Safety Control Barrier Functions... (More)
- Kinesthetic teaching allows human operators to reprogram part of a robot’s trajectory by manually guiding the robot. To allow kinesthetic teaching, and also to avoid any harm to both the robot and its environment, Cartesian impedance control is here used for trajectory following. In this paper, we present an online method to modify the compliant behavior of a robot toward its environment, so that undesired parts of the robot’s workspace are avoided during kinesthetic teaching. The stability of the method is guaranteed by a well-known passivity-based energy-storage formulation that has been modified to include a strict Lyapunov function, i.e., its time derivative is a globally negative-definite function. Safety Control Barrier Functions (SCBFs) that consider the rigid-body dynamics of the robot are formulated as inequality constraints of a quadratic optimization (QP) problem to ensure forward invariance of the robot’s states in a safe set. An experimental evaluation using a Franka Emika Panda robot is provided. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4252487f-a24f-489f-9a1e-350b2ce2223e
- author
- Salt Ducaju, Julian LU ; Olofsson, Björn LU ; Robertsson, Anders LU and Johansson, Rolf LU
- organization
- publishing date
- 2022-08
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proc. 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), August 20-24, 2022. Mexico City, Mexico
- pages
- 2266 pages
- conference name
- IEEE 18th International Conference on Automation Science and Engineering (IEEE CASE2022)
- conference location
- Mexico City, Mexico
- conference dates
- 2022-08-20 - 2022-08-24
- external identifiers
-
- scopus:85141737099
- DOI
- 10.1109/CASE49997.2022.9926525
- project
- Human-Robot Collaboration for Kinesthetic Teaching
- RobotLab LTH
- ELLIIT LU P06: Collaborative Robotic Systems
- WASP: Wallenberg AI, Autonomous Systems and Software Program at Lund University
- language
- English
- LU publication?
- yes
- id
- 4252487f-a24f-489f-9a1e-350b2ce2223e
- date added to LUP
- 2022-11-01 12:46:12
- date last changed
- 2023-11-19 22:20:24
@inproceedings{4252487f-a24f-489f-9a1e-350b2ce2223e, abstract = {{Kinesthetic teaching allows human operators to reprogram part of a robot’s trajectory by manually guiding the robot. To allow kinesthetic teaching, and also to avoid any harm to both the robot and its environment, Cartesian impedance control is here used for trajectory following. In this paper, we present an online method to modify the compliant behavior of a robot toward its environment, so that undesired parts of the robot’s workspace are avoided during kinesthetic teaching. The stability of the method is guaranteed by a well-known passivity-based energy-storage formulation that has been modified to include a strict Lyapunov function, i.e., its time derivative is a globally negative-definite function. Safety Control Barrier Functions (SCBFs) that consider the rigid-body dynamics of the robot are formulated as inequality constraints of a quadratic optimization (QP) problem to ensure forward invariance of the robot’s states in a safe set. An experimental evaluation using a Franka Emika Panda robot is provided.}}, author = {{Salt Ducaju, Julian and Olofsson, Björn and Robertsson, Anders and Johansson, Rolf}}, booktitle = {{Proc. 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), August 20-24, 2022. Mexico City, Mexico}}, language = {{eng}}, pages = {{2259--2259}}, title = {{Robot Cartesian Compliance Variation for Safe Kinesthetic Teaching using Safety Control Barrier Functions}}, url = {{https://lup.lub.lu.se/search/files/160718440/CASE22_reviewed_4_.pdf}}, doi = {{10.1109/CASE49997.2022.9926525}}, year = {{2022}}, }