Following this, a robot accuracy enhancement framework is proposed in which both techniques are integrated for an industrial robotic work cell where the strengths of one method are used to compensate for the inherent weaknesses of the other. The second method is a non-model-based compensation approach where sensor information is used to establish the relative pose of the work object and tool frames at discrete locations. The first method is a model-based calibration approach, where the end-effector poses and corresponding joint angles are measured and used to improve the kinematic model of the robot. Strong and recent background in two of the following robots: Fanuc (iR Vision). Subsequently, two methods to improve robot work cell accuracy are proposed to illustrate the concepts behind calibration and error compensation. Actually, I would like to calibrate the position of an object in my robotic cell using the Fanuc 2D camera using irVision.
I did some research but I can't figure out how to fix my problem. A literature survey on recent calibration and compensation methods is presented as well as an overview of existing commercially available solutions. I am new to programming Fanuc robots and I am having a problem with irVision. However, accuracy is significantly poorer due to the numerous error sources in the robot work cell. Industrial robotic manipulators have excellent repeatability.