Development of sensorless force-control-based end-effector for automated Robot polishing

Takuhiro Tsukada, Shotaro Ogawa, Katsuki Koto, Yasuhiro Kakinuma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As the finishing process in manufacturing a fine mold, manual polishing is typically performed to enhance the surface quality. On the other hand, manual polishing causes increase in costs and health damage to the workers due to sucking polishing dusts. Hence, polishing automation is strongly required by utilizing industrial robots. Regarding robot polishing, highly responsive polishing pressure control is definitely needed so that macro-micro system integrating high-performance end-effector into the articulated robot could be an appropriate approach because response of the robot itself is not sufficiently high. From this viewpoint, the purpose of this study is to develop an end-effector having the ability to simultaneously control polishing force and tool spindle speed. The mechanism and control system of the end-effector are designed and experimentally evaluated. In terms of force control, observer-based force control, which does not require any additional force sensor, is implemented. The experimental results show that the developed end-effector successfully control polishing force with 0.1 N and bandwidth up to 23 Hz.

Original languageEnglish
Title of host publication2020 International Symposium on Flexible Automation, ISFA 2020
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791883617
DOIs
Publication statusPublished - 2020
Event2020 International Symposium on Flexible Automation, ISFA 2020 - Virtual, Online
Duration: 2020 Jul 82020 Jul 9

Publication series

Name2020 International Symposium on Flexible Automation, ISFA 2020

Conference

Conference2020 International Symposium on Flexible Automation, ISFA 2020
CityVirtual, Online
Period20/7/820/7/9

Keywords

  • Automation
  • Polishing
  • Sensorless force control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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