부산대학교 도서관

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.