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A Study on 6D Pose Estimation Method Using Industrial Robot and 2D Vision

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2024, 10(5), pp.19-26
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : August 12, 2024
  • Accepted : October 8, 2024
  • Published : October 31, 2024

Yang-Su Jang 1 JANG, KYUNGBAE 1

1고려사이버대학교

Accredited

ABSTRACT

This study presents and verifies an easy, fast, and relatively cost-effective method for 6D pose estimation using industrial robots for bin picking in the manufacturing sector. Specifically, it details a method involving the integration of industrial robots with 2D cameras to ① acquire multi-view images of objects and collect training data, ② select variables from the collected data and implement a linear regression model, and ③ apply the trained model to estimate, verify, and evaluate the 6D pose of objects on industrial robots. The proposed data collection method and implemented linear regression model demonstrated statistically significant results. The estimated 6D poses were validated against ground true values and evaluated in their application to industrial robots, confirming their validity. By using feature point information extracted from images instead of direct image inputs as inputs to the regression model, the data size was reduced, enabling direct embedding on the robot. This research approaches the problem of spatial coordinates in 3D from a data analysis perspective, rather than from geometrical or computer vision perspectives.

Citation status

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