Evaluation of actuation precision in deboning process for pork leg using 6-DOF industrial robots

This paper evaluates the accuracy of the intersection over union (IoU) in the recognition of the exposed cross-section of the hip bone (pubic bone) on the external surface and the success rate of bone grasping actuation for the deboning process for pork leg using a 6-DOF industrial robot in the deboning system equipped with multiple robot arms in the "cell". Information on bone shapes and positions is analysed with the recognition unit which acquires an X-ray image and height/surface image including the surface position of the pubic bone. Deep learning and image analysis are applied to the acquired combined information in the recognition unit to obtain information on bone shapes and positions, which IoU is around 0.7 in average and the success rate of grasping the pubic bone is more than 99% among the evaluated workpieces which are being processed until the step of grasping the target position with the chuck equipped with a 6-DOF robot.