Tactile sensing for tissue discrimination in robotic meat cutting: A feasibility study

Article

Aly, Basem Adel, Low, Tobias, Long, Derek, Brett, Peter and Baillie, Craig. 2024. "Tactile sensing for tissue discrimination in robotic meat cutting: A feasibility study." Journal of Food Engineering. 363. https://doi.org/10.1016/j.jfoodeng.2023.111754
Article Title

Tactile sensing for tissue discrimination in robotic meat cutting: A feasibility study

ERA Journal ID9657
Article CategoryArticle
AuthorsAly, Basem Adel, Low, Tobias, Long, Derek, Brett, Peter and Baillie, Craig
Journal TitleJournal of Food Engineering
Journal Citation363
Article Number111754
Number of Pages12
Year2024
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN0260-8774
1873-5770
Digital Object Identifier (DOI)https://doi.org/10.1016/j.jfoodeng.2023.111754
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S0260877423003527
Abstract

This investigation explores an approach for tactile sensing to guide a knife attached to a robot to cut red meat. During cutting, the discrimination of tissue types and the approach to tissue interfaces is an important factor in this variable, deforming medium. Using a force sensor attached to a standard knife controlled by a 6-axis robotic manipulator, cuts were performed to a depth of approximately 20 mm across striploin chops. Force patterns showed significant similarity in cross-correlation analysis, with an 80–97% correlation coefficient. The force sensor reading exhibited identifiable patterns that could be tracked to pinpoint critical stages of the cutting process, validating the potential of tactile sensing in meat processing. The insights gained will facilitate the development of automated perception and corrective actuation strategies for maintaining the knife on the desired cutting path relative to tissue interfaces, adapting to the deformable nature of the meat in real-time.

KeywordsTactile; Force sensor; Robot; Tissues; Red meat
Related Output
Is part ofTactile perception by tissue force characteristics for robotic red eat cutting
Article Publishing Charge (APC) FundingResearcher
Contains Sensitive ContentContains sensitive content
ANZSRC Field of Research 2020309999. Other agricultural, veterinary and food sciences not elsewhere classified
401499. Manufacturing engineering not elsewhere classified
400702. Automation engineering
Public Notes

This article is part of a UniSQ Thesis by publication. See Related Output.

Byline AffiliationsSchool of Engineering
Centre for Agricultural Engineering
School of Agriculture and Environmental Science
Centre for Agricultural Engineering (Operations)
Grains Research and Development Corporation, Australia
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