Sensor-Enhanced Smart Gripper Development for Automated Meat Processing

Author:

Takács Kristóf1ORCID,Takács Bence12,Garamvölgyi Tivadar1,Tarsoly Sándor1,Alexy Márta1,Móga Kristóf1ORCID,Rudas Imre J.3ORCID,Galambos Péter13ORCID,Haidegger Tamás34ORCID

Affiliation:

1. Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary

2. John von Neumann Faculty of Informatics, Óbuda University, 1034 Budapest, Hungary

3. University Research and Innovation Center, Óbuda University, 1034 Budapest, Hungary

4. School of Computing, Queens University, Kingston, ON K7L 3N6, Canada

Abstract

Grasping and object manipulation have been considered key domains of Cyber-Physical Systems (CPS) since the beginning of automation, as they are the most common interactions between systems, or a system and its environment. As the demand for automation is spreading to increasingly complex fields of industry, smart tools with sensors and internal decision-making become necessities. CPS, such as robots and smart autonomous machinery, have been introduced in the meat industry in recent decades; however, the natural diversity of animals, potential anatomical disorders and soft, slippery animal tissues require the use of a wide range of sensors, software and intelligent tools. This paper presents the development of a smart robotic gripper for deployment in the meat industry. A comprehensive review of the available robotic grippers employed in the sector is presented along with the relevant recent research projects. Based on the identified needs, a new mechatronic design and early development process of the smart gripper is described. The integrated force sensing method based on strain measurement and magnetic encoders is described, including the adjacent laboratory and on-site tests. Furthermore, a combined slip detection system is presented, which relies on an optical flow-based image processing algorithm using the video feed of a built-in endoscopic camera. Basic user tests and application assessments are presented.

Funder

European Union’s Horizon 2020 research and innovation programme

National Research, Development and Innovation Fund of Hungary

Óbuda University—Doctoral School of Applied Informatics and Applied Mathematics

Hungarian Academy of Sciences

Distinguished Researcher program of Óbuda University

Publisher

MDPI AG

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