Automatic Soft Gripper Implementation on Foods Using Machine Vision

Suharyadi Pancono, Wahyu Adhie Candra, Andi Aqil

2022

Abstract

The rigid frame of conventional robots makes the food industry still need a lot of human involvement. Soft gripper is created as one of the solutions for food handling automation system. Various studies have developed a variety of soft grippers in food pick-and-place process. The gripper with 2 finger configurations showing better performance compared to the gripper with single finger configuration because it can handle more diverse object, but the configuration of the fingers is still selected and changed manually. This study proposed a method to automatically selecting and changing the finger configuration. This study developed 4-finger soft gripper with a conversion mechanism for 2 finger configurations. The finger configuration is selected based on the object’s length-to-width ratio that calculated using machine vision. Canny edge detection method is used to detect edge contours from the object’s image. The results obtained in this study show that the finger configuration conversion mechanism on the soft gripper made has good repeatability performance, the length-to-width ratio measurement using machine vision has accuracy up to 97,81% compared to manual measurement, and food pick-and-place experiment with 100% success rate.

Paper Citation

in Harvard Style

Pancono S., Adhie Candra W. and Aqil A. (2022). Automatic Soft Gripper Implementation on Foods Using Machine Vision. In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES; ISBN 978-989-758-619-4, SciTePress, pages 971-975. DOI: 10.5220/0011973700003575

in Bibtex Style

@conference{icast-es22,
author={Suharyadi Pancono and Wahyu Adhie Candra and Andi Aqil},
title={Automatic Soft Gripper Implementation on Foods Using Machine Vision},
booktitle={Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES},
year={2022},
pages={971-975},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011973700003575},
isbn={978-989-758-619-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES
TI - Automatic Soft Gripper Implementation on Foods Using Machine Vision
SN - 978-989-758-619-4
AU - Pancono S.
AU - Adhie Candra W.
AU - Aqil A.
PY - 2022
SP - 971
EP - 975
DO - 10.5220/0011973700003575
PB - SciTePress