• DocumentCode
    716422
  • Title

    Model-based feed-forward and setpoint generation in a multi-robot sewing cell

  • Author

    Schrimpf, Johannes ; Bjerkeng, Magnus ; Lind, Morten ; Mathisen, Geir

  • Author_Institution
    Dept. of Eng. Cybern., Norwegian Univ. of Sci. & Technol., Trondheim, Norway
  • fYear
    2015
  • fDate
    26-30 May 2015
  • Firstpage
    2027
  • Lastpage
    2033
  • Abstract
    This paper describes an automated sewing system that focuses on sewing of curved edge segments. The sewing cell includes an industrial sewing machine as well as three industrial robots that handle the parts during the sewing process. Based on experiences from previous work, several improvements are presented that address issues with previous implementations. The main contribution concerning the control system is a model-based generation of the feed-forward velocity for the robot tool movement, based on a geometric description of the parts. This approach increases performance, especially in the case of curved fabric, as well as robustness in case of faulty sensor data. Additionally, this paper describes hardware upgrades that address mechanical challenges that were described in former publications. Finally, the paper presents experiments comparing the model-based control approach with the former control system based on constant feed-forwards velocity and setpoints.
  • Keywords
    feedforward; geometry; industrial robots; multi-robot systems; sewing machines; automated sewing system; curved edge segments; curved fabric; faulty sensor data; feedforward velocity; geometric description; hardware upgrades; industrial robots; industrial sewing machine; model-based control approach; multirobot sewing cell; robot tool movement; setpoint generation; Force; Image edge detection; Needles; Robot sensing systems; Sensor systems; Service robots;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2015 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • Type

    conf

  • DOI
    10.1109/ICRA.2015.7139464
  • Filename
    7139464