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

Abstract

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.

Keywords

• Meat factory cell (MFC)
• Pork primal cuts
• CT-scan generated model
• 3D point clouds
• Bayesian coherent point drift
• Cutting trajectories