Skip to main content
SpringerLink
Log in

Gripper Design and Motion Control Algorithm Development for Oyster Handling

  • Short Communication
  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

Currently, the seafood industry has a hazardous working environment because of inefficient production methods and aging processing equipment. Therefore, smart technology must be applied to the domestic seafood industry at the production and circulation stages. In this study, we focused on the automation of the oyster production stage. For the automation of the oyster production stage, a soft gripper capable of handling oysters must be designed. Additionally, to grip and classify oysters moving at high speeds on conveyors, object recognition and gripping point recognition algorithms must be studied. Therefore, this study, soft gripper design and object and gripping point recognition algorithm research were conducted. A test bed was built to verify the gripper and algorithm, and a gripping experiment was conducted to verify the gripper’s performance. In addition, the object and gripping point recognition algorithms were verified. The gripping experiment, showed a success rate of 100%, and the object recognition experiment showed a success rate of 88%. Through this study, the possibility of automating the production stage of oysters was confirmed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6:
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Abbreviations

PTP:

Point to point

px:

Pixel

r:

Radius 

N:

Resolution

References

  1. A new paradigm in the seafood industry, smart technology, Korea Fisheries Economy. Retrieved May 16, 2022 from http://www.fisheco.com/.

  2. Park, J. S., Park, J. N., Park, J. K., Han, I. J., Jung, P. M., Song, B. S., Choi, J. I., Kim, J. H., Han, S. B., Byun, M. W., & Lee, J. W. (2008). Microbiological, physicochemical, and sensory characteristics of gamma-irradiated fresh oysters during storage. Journal of Radiation Industry, 2, 85–91.

    Google Scholar 

  3. Kim, S. E., & Yoon, H. (2022). Development of a universal-purpose settlement gripper using a flexible sub-arm and triggering mechanism. International Journal of Precision Engineering & Manufacturing, 23(12), 1431–1441. https://doi.org/10.1007/s12541-022-00714-2

    Article  Google Scholar 

  4. Gwon, M. S., Park, G., Hong, D., Park, Y., Han, S., Kang, D., & Koh, J. (2022). Soft directional adhesion gripper fabricated by 3D printing process for gripping flexible printed circuit boards. International Journal of Precision Engineering & Manufacturing-Green Technology, 9(4), 1151–1163. https://doi.org/10.1007/s40684-021-00368-x

    Article  Google Scholar 

  5. Lee, E. S., & Yoon, H. (2022). Development of a rod gripper for drones using flexible fingers and bistable structures. International Journal of Precision Engineering & Manufacturing, 23(11), 1325–1335. https://doi.org/10.1007/s12541-022-00697-0

    Article  Google Scholar 

  6. Ren, Z., Fang, F., Yan, N., & Wu, Y. (2022). State of the art in defect detection based on machine vision. International Journal of Precision Engineering & Manufacturing-Green Technology, 9(2), 661–691. https://doi.org/10.1007/s40684-021-00343-6

    Article  Google Scholar 

  7. Kim, H. S., Han, Y., & Kim, J. (2023). 3D measurement using a single image for smart manufacturing of microscopic products in a ceramic powder pressing process. International Journal of Precision Engineering & Manufacturing-Green Technology, 10(1), 233–243. https://doi.org/10.1007/s40684-022-00434-y

    Article  Google Scholar 

  8. Son, J. W. (2023). A review on robust control of robot manipulators for future manufacturing. International Journal of Precision Engineering and Manufacturing, 24, 1083–1102.

    Article  Google Scholar 

  9. Shin, D. H. (2022). Gripper design and algorithm development for oyster handing. In Proceedings of the Korean society for precision engineering conference (pp. 226–226).

Download references

Acknowledgements

This study was conducted with the support of the Institute for Promotion of Oceans and Fisheries Science and Technology, with funding from the Ministry of Oceans and Fisheries in 2021 (Development of Aquatic Food Smart Processing Technology, 20210671).

Author information

Authors and Affiliations

  1. Integrated Robotic Systems R&D Division, Korea Institute of Robotics and Technology Convergence, Pohang, Gyeongsangbuk-do, Korea

    Dong Ho Shin, Jong Hwan Baek, Myeong Su Jeong & Jae Youl Lee

Authors
  1. Dong Ho Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jong Hwan Baek
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Myeong Su Jeong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jae Youl Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jae Youl Lee.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shin, D.H., Baek, J.H., Jeong, M.S. et al. Gripper Design and Motion Control Algorithm Development for Oyster Handling. Int. J. Precis. Eng. Manuf. 24, 1685–1693 (2023). https://doi.org/10.1007/s12541-023-00892-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-023-00892-7

Keywords

Search

Navigation