Detection and Control of Contact Force Transients in Robotic Manipulation without a Force Sensor
(2018) 2018 IEEE International Conference on Robotics and Automation- Abstract
- In this research, it is shown that robot joint torques can be used to recognize contact force transients induced during robotic manipulation, thus detecting when a task is completed. The approach does not assume any external sensor, which is a benefit compared to the state of the art. The joint torque data are used as input to a recurrent neural network (RNN), and the output of the RNN indicates whether the task is completed. A real-time application for force transient detection is developed, and verified experimentally on an industrial robot.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/e297ddcb-4bb4-493f-8267-080ee874acc4
- author
- Karlsson, Martin LU ; Robertsson, Anders LU and Johansson, Rolf LU
- organization
- publishing date
- 2018-05-21
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2018 IEEE International Conference on Robotics and Automation (ICRA)
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2018 IEEE International Conference on Robotics and Automation
- conference location
- Brisbane, Australia
- conference dates
- 2018-05-21 - 2018-05-25
- external identifiers
-
- scopus:85059806636
- project
- RobotLab LTH
- SARAFun—Smart Assembly Robot with Advanced FUNctionalities
- Kirurgens Perspektiv
- language
- English
- LU publication?
- yes
- id
- e297ddcb-4bb4-493f-8267-080ee874acc4
- date added to LUP
- 2018-03-13 09:11:20
- date last changed
- 2024-04-01 02:34:16
@inproceedings{e297ddcb-4bb4-493f-8267-080ee874acc4, abstract = {{In this research, it is shown that robot joint torques can be used to recognize contact force transients induced during robotic manipulation, thus detecting when a task is completed. The approach does not assume any external sensor, which is a benefit compared to the state of the art. The joint torque data are used as input to a recurrent neural network (RNN), and the output of the RNN indicates whether the task is completed. A real-time application for force transient detection is developed, and verified experimentally on an industrial robot.}}, author = {{Karlsson, Martin and Robertsson, Anders and Johansson, Rolf}}, booktitle = {{2018 IEEE International Conference on Robotics and Automation (ICRA)}}, language = {{eng}}, month = {{05}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Detection and Control of Contact Force Transients in Robotic Manipulation without a Force Sensor}}, url = {{https://lup.lub.lu.se/search/files/39855538/karlsson2018detection.pdf}}, year = {{2018}}, }