Robot calibration

Industrial robots are highly repeatable but not accurate, therefore, robot accuracy can be improved through robot calibration. Robot calibration is the process of identifying certain parameters in the kinematic structure of an industrial robot, such as the relative position of robot links. Depending on the type of errors modeled, the calibration can be classified in three different ways. Level-1 calibration only models differences between actual and reported joint displacement values, (also known as mastering). Level-2 calibration, also known as kinematic calibration, concerns the entire geometric robot calibration which includes angle offsets and joint lengths. Level-3 calibration, also called a non-kinematic calibration, models errors other than geometric defaults such as stiffness, joint compliance and friction. Often Level-1 and Level-2 calibration are sufficient for most practical needs. Industrial robots are highly repeatable but not accurate, therefore, robot accuracy can be improved through robot calibration. Robot calibration is the process of identifying certain parameters in the kinematic structure of an industrial robot, such as the relative position of robot links. Depending on the type of errors modeled, the calibration can be classified in three different ways. Level-1 calibration only models differences between actual and reported joint displacement values, (also known as mastering). Level-2 calibration, also known as kinematic calibration, concerns the entire geometric robot calibration which includes angle offsets and joint lengths. Level-3 calibration, also called a non-kinematic calibration, models errors other than geometric defaults such as stiffness, joint compliance and friction. Often Level-1 and Level-2 calibration are sufficient for most practical needs. Non-parametric robot calibration circumvents the parameter identification. Used with serial robots, it is based on the direct compensation of mapped errors in the work space. Used with parallel robots, non-parametric calibration can be performed by the transformation of the configuration space. Parametric robot calibration is the process of determining the actual values of kinematic and dynamic parameters of an industrial robot (IR). Kinematic parameters describe the relative position and orientation of links and joints in the robot while the dynamic parameters describe arm and joint masses and internal friction. Robot calibration can remarkably improve the accuracy of robots programmed offline, also known as Off-line programming (robotics). A calibrated robot has a higher absolute as well as relative positioning accuracy than an uncalibrated one, i.e., the real position of the robot end effector corresponds better to the position calculated from the mathematical model of the robot. Absolute positioning accuracy is particularly relevant in connection with robot exchangeability and Off-line programming (robotics) of precision applications. Besides the calibration of the robot, the calibration of its tools and the workpieces it works with (the so-called cell calibration) can minimize occurring inaccuracies and improve process security. The international standard ISO 9283 sets different performance criteria for industrial robots and suggests test procedures in order to obtain appropriate parameter values. The most important criteria, and also the most commonly used, are pose accuracy (AP) and pose repeatability (RP). Repeatability is particularly important when the robot is moved towards the command positions manually ('Teach-In'). If the robot program is generated by a 3D simulation (off-line programming), absolute accuracy is vital, too. Both are generally influenced in a negative way by kinematic factors. Here especially the joint offsets and deviations in lengths and angles between the individual robot links take effect. There exist different possibilities for pose measurement with industrial robots, e.g. touching reference parts, using supersonic distance sensors, laser interferometry, theodolites, calipers or laser triangulation. Furthermore there are camera systems which can be attached in the robot’s cell or at the IR mounting plate and acquire the pose of a reference object. Measurement and calibration systems are made by such companies as Bluewrist, Dynalog, RoboDK, FARO Technologies, Creaform, Leica, Metris, Metronor, Wiest, Teconsult and Automated Precision,Inc.. The robot errors gathered by pose measurements can be minimized by numerical optimization. For kinematic calibration, a complete kinematical model of the geometric structure must be developed, whose parameters then can be calculated by mathematical optimization. The common system behaviour can be described with the vector model function as well as input and output vectors (see figure).The variables k, l, m, n and their derivates describe the dimensions of the single vector spaces. Minimization of the residual error r for the purpose of identification of the optimal parameter vector p follows from the difference between both output vectors using the Euclidean norm. For solving the kinematical optimization problems least-squares descent methods are convenient, e.g. a modified quasi-Newton method. This procedure supplies corrected kinematical parameters for the measured machine, which then for example can be used to update the system variables in the controller in order to adapt the used robot model to the real kinematics.