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

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.