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3D model based adaptive cutting system for the meat factory cell: Overcoming natural variability

Ian de Medeiros Esper, Lars Erik Gangsei, L. E. Cordova-Lopez, Dmytro Romanov, Per Håkon Bjørnstad, Ole Alvseike, Pål Johan From, Alex Mason

发表年份
2023
引用次数
8

摘要

This article presents a comprehensive framework for executing primal cuts on pigs within a Meat Factory Cell (MFC) context, with potential applications for small and medium-sized producers. The framework begins by creating a 3D model from CT-scans, which is then aligned with a 3D point cloud acquired from an Intel© Realsense™ camera using an initial coarse estimate, and refined through Bayesian Coherent Point Drift. Cutting trajectories are generated based on a custom 3D model of the cutting surface, designed with consideration of the pig's skeletal structure and the cutting properties of the knife tool attached to the robot. A qualitative evaluation of the cuts performed by a professional butcher reveals promising results, while also identifying areas for improvement. The article underscores the potential of integrating CT-scans, 3D point clouds, and cutting models to automate primal cuts in the meat industry, addressing the inherent anatomical variability among animals.

关键词

Point cloudContext (archaeology)Factory (object-oriented programming)Computer sciencePoint (geometry)Image stitchingArtificial intelligenceComputer visionMathematicsGeology

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