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Takács K, Takács B, Garamvölgyi T, Tarsoly S, Alexy M, Móga K, Rudas IJ, Galambos P, Haidegger T. Sensor-Enhanced Smart Gripper Development for Automated Meat Processing. SENSORS (BASEL, SWITZERLAND) 2024; 24:4631. [PMID: 39066030 PMCID: PMC11281046 DOI: 10.3390/s24144631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 07/08/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024]
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.
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Affiliation(s)
- Kristóf Takács
- Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary (S.T.); (P.G.)
| | - Bence Takács
- Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary (S.T.); (P.G.)
- John von Neumann Faculty of Informatics, Óbuda University, 1034 Budapest, Hungary
| | - Tivadar Garamvölgyi
- Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary (S.T.); (P.G.)
| | - Sándor Tarsoly
- Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary (S.T.); (P.G.)
| | - Márta Alexy
- Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary (S.T.); (P.G.)
| | - Kristóf Móga
- Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary (S.T.); (P.G.)
| | - Imre J. Rudas
- University Research and Innovation Center, Óbuda University, 1034 Budapest, Hungary
| | - Péter Galambos
- Antal Bejczy Center of Intelligent Robotics, Óbuda University, 1034 Budapest, Hungary (S.T.); (P.G.)
- University Research and Innovation Center, Óbuda University, 1034 Budapest, Hungary
| | - Tamás Haidegger
- University Research and Innovation Center, Óbuda University, 1034 Budapest, Hungary
- School of Computing, Queens University, Kingston, ON K7L 3N6, Canada
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Rethinking production technology for meat packers. Anim Front 2022; 12:5-6. [PMID: 35505839 PMCID: PMC9056028 DOI: 10.1093/af/vfac019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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