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Sensorless Kinesthetic Teaching of Robotic Manipulators Assisted by Observer-Based Force Control

Capurso, Martino; Ghazaei, Mahdi LU ; Johansson, Rolf LU ; Robertsson, Anders LU and Rocco, Paolo (2017) IEEE International Conference on Robotics and Automation (ICRA 2017) In Proceedings of IEEE International Conference on Robotics and Automation (ICRA) 2017 p.945-950
Abstract
In modern day industry, robots are indispensable for achieving high production rates and competitiveness. In small and medium scale enterprises, where the production may shift rapidly, it is vital to be able to reprogram robots quickly. Kinesthetic teaching, also known as lead-through programming (LTP), provides a fast approach for teaching a trajectory. In this approach, a trajectory is demonstrated by physical interaction with the robot, i.e., the user manually guides the manipulator. This paper presents a sensorless approach to LTP for redundant robots that eliminates the need for expensive force/torque sensors. The active implementation enhances the passive LTP by an admittance control in joint space based on the external forces... (More)
In modern day industry, robots are indispensable for achieving high production rates and competitiveness. In small and medium scale enterprises, where the production may shift rapidly, it is vital to be able to reprogram robots quickly. Kinesthetic teaching, also known as lead-through programming (LTP), provides a fast approach for teaching a trajectory. In this approach, a trajectory is demonstrated by physical interaction with the robot, i.e., the user manually guides the manipulator. This paper presents a sensorless approach to LTP for redundant robots that eliminates the need for expensive force/torque sensors. The active implementation enhances the passive LTP by an admittance control in joint space based on the external forces applied by the user, estimated with a Kalman filter using the generalized momentum formulation. To improve the quality of the estimation and hence LTP, we use a dithering technique. The active LTP has been implemented on ABB YuMi robot and experimental comparison with an earlier passive LTP is presented. (Less)
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author
organization
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type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Proceedings of IEEE International Conference on Robotics and Automation (ICRA) 2017
pages
6 pages
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
IEEE International Conference on Robotics and Automation (ICRA 2017)
external identifiers
  • scopus:85027970374
ISBN
978-1-5090-4633-1
978-1-5090-4633-4
DOI
10.1109/ICRA.2017.7989115
language
English
LU publication?
yes
id
742b1f18-5b40-4d87-a134-b65cb906309e
date added to LUP
2017-05-29 21:07:57
date last changed
2018-01-07 12:05:33
@inproceedings{742b1f18-5b40-4d87-a134-b65cb906309e,
  abstract     = {In modern day industry, robots are indispensable for achieving high production rates and competitiveness. In small and medium scale enterprises, where the production may shift rapidly, it is vital to be able to reprogram robots quickly. Kinesthetic teaching, also known as lead-through programming (LTP), provides a fast approach for teaching a trajectory. In this approach, a trajectory is demonstrated by physical interaction with the robot, i.e., the user manually guides the manipulator. This paper presents a sensorless approach to LTP for redundant robots that eliminates the need for expensive force/torque sensors. The active implementation enhances the passive LTP by an admittance control in joint space based on the external forces applied by the user, estimated with a Kalman filter using the generalized momentum formulation. To improve the quality of the estimation and hence LTP, we use a dithering technique. The active LTP has been implemented on ABB YuMi robot and experimental comparison with an earlier passive LTP is presented.},
  author       = {Capurso, Martino and Ghazaei, Mahdi and Johansson, Rolf and Robertsson, Anders and Rocco, Paolo},
  booktitle    = {Proceedings of IEEE International Conference on Robotics and Automation (ICRA) 2017},
  isbn         = {978-1-5090-4633-1 },
  language     = {eng},
  month        = {05},
  pages        = {945--950},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Sensorless Kinesthetic Teaching of Robotic Manipulators Assisted by Observer-Based Force Control},
  url          = {http://dx.doi.org/10.1109/ICRA.2017.7989115},
  year         = {2017},
}