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Related Experiment Video

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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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Applying High-Speed Vision Sensing to an Industrial Robot for High-Performance Position Regulation under

Shouren Huang1, Niklas Bergström2, Yuji Yamakawa3

  • 1Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan. Huang_shouren@ipc.i.u-tokyo.ac.jp.

Sensors (Basel, Switzerland)
|August 3, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a novel coarse-to-fine strategy for industrial robot position regulation, overcoming uncertainties with an add-on module. This method achieves high-performance control with minimal manual teaching, enhancing robotic task accuracy.

Keywords:
add-on modulecompensation of uncertaintiesdynamic compensationfast and accurate robotic position regulationhigh-speed vision sensingindustrial robots

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Area of Science:

  • Robotics
  • Control Systems Engineering
  • Mechatronics

Background:

  • Industrial robots face challenges in precise position control due to internal (dynamics mismatch, backlash) and external (calibration, workpiece) uncertainties.
  • Traditional methods often require extensive manual teaching, limiting adaptability and speed.

Purpose of the Study:

  • To develop a systematic approach for high-performance position regulation in industrial robots under uncertainty.
  • To enable precise robotic control with minimal or no manual intervention.
  • To enhance the accuracy and success rate of robotic manipulation tasks.

Main Methods:

  • A coarse-to-fine strategy using an add-on module with a high-speed vision sensor (1000 Hz) and actuator.
  • The main robot performs coarse motion, guided by automatically planned trajectories from a static camera.
  • The add-on module compensates for accumulated uncertainties, enabling fine adjustments.

Main Results:

  • Demonstrated successful implementation on a commercial parallel-link robot for 1D peg-and-hole alignment.
  • Achieved an almost 100% success rate for fast peg-in-hole manipulation.
  • Attained a regulation accuracy of approximately 0.1 mm even with randomly placed workpieces.

Conclusions:

  • The proposed systematic approach effectively addresses uncertainties in industrial robot position regulation.
  • The add-on module strategy significantly enhances robotic manipulation accuracy and success rates.
  • This method offers a pathway to high-performance, adaptable robotic systems with reduced manual setup.