GRASPING AND REPOSITIONING OBJECTS USING INVERSE KINEMATIC METHOD FOR ARM ROBOT BASED ON PIXEL POSITION REGRESSION

S. Sendari*, Y. R. Wahyudi, I. A.E. Zaeni, A. N. Handayani, M. Muladi, N. Wicaksono, M. A. Fatwaddin, H. Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper presented a method of recognizing objects' positions using a vision sensor to identify the grasping point of the arm robot. The arm robot used an embedded color vision Pixy CMUcam5 camera (Pixy camera) to capture and process the colored object image. Pixy camera is low in cost and easily programmed with high-speed FPS in real-time data processing. However, it still has the fisheye effect problem when recognizing the object's position. Thus, the pixel position regression algorithm was chosen to transform the colored objects' positions in the real coordinates. This method was implemented in the arm robot for grasping, picking, and repositioning tasks. The transformation results were employed to calculate the kinematics of the arm robot's joints. The experimental results showed that the Pixy camera could identify objects in the real world and transform the objects' positions. The error value at the real-world position was no more than 1.67

Original languageEnglish
Pages (from-to)43-54
Number of pages12
JournalJournal of Advanced Manufacturing Technology
Volume16
Issue number3
StatePublished - 2022

Keywords

  • Arm Robot
  • Embedded Color Vision
  • Object Recognition
  • Pixel Position Regression
  • Repositioning

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