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Molded article picking robot using image processing technique and pixel-based visual feedback control

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Abstract

This paper aims to develop a robotic system that is able to find and remove unwanted molded articles, which fell in a narrow metallic mold space. Currently, this task is being supported by skilled workers. The proposed robotic system has the ability to estimate the orientation of articles using transfer learning-based convolutional neural networks (CNNs). The orientation information is essential and indispensable to realize stable robot picking operations. In addition, pixel-based visual feedback (PBVF) controller is introduced by referring to the center of gravity (COG) position of articles computed by image processing techniques. Hence, it is possible to eliminate the complex calibration between the camera and the robot coordinate systems. The implementation and effectiveness of the pick and place robot are demonstrated, where the conventional calibration of such task is not required.

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Authors and Affiliations

  1. Graduate School of Engineering, Sanyo-Onoda City University, 1-1-1 Daigaku-Dori, Sanyo-Onoda, 756-0884, Japan

    Kohei Miki, Fusaomi Nagata & Takeshi Ikeda

  2. Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan

    Keigo Watanabe

  3. Mechanical Engineering Department, School of Sciences and Engineering, American University in Cairo, Cairo, Egypt

    Maki K. Habib

Authors
  1. Kohei Miki
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  2. Fusaomi Nagata
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  3. Takeshi Ikeda
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  4. Keigo Watanabe
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  5. Maki K. Habib
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Corresponding author

Correspondence to Fusaomi Nagata.

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This work was presented in part at the 26th International Symposium on Artificial Life and Robotics (Online, January 21–23, 2021).

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Miki, K., Nagata, F., Ikeda, T. et al. Molded article picking robot using image processing technique and pixel-based visual feedback control. Artif Life Robotics 26, 390–395 (2021). https://doi.org/10.1007/s10015-021-00692-0

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  • DOI: https://doi.org/10.1007/s10015-021-00692-0

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