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

Martino Capurso, Mahdi Ghazaei, Rolf Johansson, Anders Robertsson, Paolo Rocco

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

29 Citations (SciVal)
615 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationProceedings of IEEE International Conference on Robotics and Automation (ICRA) 2017
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages945-950
Number of pages6
ISBN (Electronic)978-1-5090-4633-1
DOIs
Publication statusPublished - 2017 May 30
EventIEEE International Conference on Robotics and Automation (ICRA 2017) - Sands Expo and Convention Centre, Singapore
Duration: 2017 May 292017 Jun 3
http://www.icra2017.org/

Conference

ConferenceIEEE International Conference on Robotics and Automation (ICRA 2017)
Abbreviated titleICRA17
Country/TerritorySingapore
Period2017/05/292017/06/03
Internet address

Subject classification (UKÄ)

  • Robotics
  • Control Engineering

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