Automatically tightening tiny screw using two images and positioning control

Shou Yu Chen, Jeng-Rong Ho, Pi Cheng Tung, Chih Kuang Lin

Research output: Contribution to journalArticlepeer-review

Abstract

This paper describes how to tighten M1.4 screws by controlling a manipulator. The whole process is based on a human–machine interface designed using Visual Studio C++ to run image processing algorithms and control the position of a manipulator. Two charge-coupled device cam-eras are used. One is fixed on the stationary frame above screw holes and used to take pictures of the holes. The positions of the holes are determined using image processing algorithms and then transformed into the coordinate system of the manipulator by using coordinate transformation. The other camera, installed on the end effect of the manipulator, photographs the screw hole to fine-tune the position of the manipulator, improving positioning control. The image processing methods including grayscale, Gaussian filter, bilateral filter, binarization, edge detection, center of gravity, and minimum circumcircle are used to find the center coordinates of the target holes. Experimental study shows that M1.4 screws can be tightened into the target holes with the manipulator.

Original languageEnglish
Article number2521
JournalMathematics
Volume9
Issue number19
DOIs
StatePublished - 1 Oct 2021

Keywords

  • Coordinate transformation
  • Image processing
  • Manipulator

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