The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2022
Session ID : 1A1-A05
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Jellyfish Grasping and Transportation with a Wire-Driven Gripper and Deep Learning Based Recognition
*Issei NATEZhongkui WANGShinichi HIRAI
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Abstract

Automation has been adopted and realized in many industrial fields in recent years. However, it has been barely implemented in the field of dealing with living creatures. Therefore in this paper, we propose a robotic system for grasping and transporting jellyfish to automate operations involving living creatures. We created a wire-driven robotic gripper specialized for grasping jellyfish that is very soft with an extremely low friction coefficient. We trained a YOLOv5 model for recognizing jellyfish and obtain the grasping position. In experiments, we used gel jellyfish fabricated using a 3D gel printer instead of living jellyfish. Finally, we conducted an experiment to automatically detect, grasp, and transport jellyfish from one tank to another with the proposed robotic gripper and deep learning based recognition method.

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© 2022 The Japan Society of Mechanical Engineers
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