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Full-Pose Calibration of a Robot Manipulator Using a Coordinate-Measuring MachineMorris R. Driels, Lt W. Swayze USN and Lt S. Potter USNDepartment of Mechanical Engineering, Naval Postgraduate School, Monterey, California, USThe work reported in this article addresses the kinematiccalibration of a robot manipulator using a coordinate measuringmachine (CMM) which is able to obtain the full pose ofthe end-effector. A kinematic model is developed for themanipulator, its relationship to the world coordinate frame andthe tool. The derivation of the tool pose from experimentalmeasurements is discussed, as is the identification methodology.A complete simulation of the experiment is performed, allowingthe observation strategy to be defined. The experimental workis described together with the parameter identification andaccuracy verification. The principal conclusion is that themethod is able to calibrate the robot successfully, with aresulting accuracy approaching that of its repeatability.Keywords: Robot calibration; Coordinate measurement; Parameteridentification; Simulation study; Accuracy enhancement1. IntroductionIt is well known that robot manipulators typically havereasonable repeatability (0.3 ram), yet exhibit poor accuracy(10.0 mm). The process by which robots may be calibratedin order to achieve accuracies approaching that of themanipulator is also well understood 1. In the calibrationprocess, several sequential steps enable the precise kinematicparameters of the manipulator to be identified, leading toimproved accuracy. These steps may be described as follows:1. A kinematic model of the manipulator and the calibrationprocess itself is developed and is usually accomplished withstandard kinematic modelling tools 2. The resulting modelis used to define an error quantity based on a nominal(manufacturers) kinematic parameter set, and an unknown,actual parameter set which is to be identified.2. Experimental measurements of the robot pose (partial orcomplete) are taken in order to obtain data relating to theactual parameter set for the robot.3.The actual kinematic parameters are identified by systematicallychanging the nominal parameter set so as to reducethe error quantity defined in the modelling phase. Oneapproach to achieving this identification is determiningthe analytical differential relationship between the posevariables P and the kinematic parameters K in the formof a Jacobian, and then inverting the equation to calculate the deviation ofthe kinematic parameters from their nominal valuesAlternatively, the problem can be viewed as a multidimensionaloptimisation task, in which the kinematic parameterset is changed in order to reduce some defined error functionto zero. This is a standard optimisation problem and maybe solved using well-known 3 methods.4. The final step involves the incorporation of the identifiedkinematic parameters in the controller of the robot arm,the details of which are rather specific to the hardware ofthe system under study.This paper addresses the issue of gathering the experimentaldata used in the calibration process. Several methods areavailable to perform this task, although they vary in complexity,cost and the time taken to acquire the data. Examples ofsuch techniques include the use of visual and automatictheodolites 4, 5, 6, servocontrolled laser interferometers 7,acoustic sensors 8 and vidual sensors 9. An ideal measuringsystem would acquire the full pose of the manipulator (positionand orientation), because this would incorporate the maximuminformation for each position of the arm. All of the methodsmentioned above use only the partial pose, requiring moredata to be taken for the calibration process to proceed.2. TheoryIn the method described in this paper, for each position inwhich the manipulator is placed, the full pose is measured,although several intermediate measurements have to be takenin order to arrive at the pose. The device used for the posemeasurement is a coordinate-measuring machine (CMM),which is a three-axis, prismatic measuring system with aquoted accuracy of 0.01 ram. The robot manipulator to becalibrated, a PUMA 560, is placed close to the CMM, and aspecial end-effector is attached to the flange. Fig. 1 showsthe arrangement of the various parts of the system. In thissection the kinematic model will be developed, the poseestimation algorithms explained, and the parameter identificationmethodology outlined.2.1 Kinematic ParametersIn this section, the basic kinematic structure of the manipulatorwill be specified, its relation to a user-defined world coordinatesystem discussed, and the end-point toil modelled. From thesemodels, the kinematic parameters which may be identifiedusing the proposed technique will be specified, and a methodfor determining those parameters described.The fundamental modelling tool used to describe the spatialrelationship between the various objects and locations in themanipulator workspace is the Denavit-Hartenberg method2, with modifications proposed by Hayati 10, Mooring11 and Wu 12 to account for disproportional models 13when two consecutive joint axes are nominally parallel. Asshown in Fig. 2, this method places a coordinate frame oneach object or manipulator link of interest, and the kinematicsare defined by the homogeneous transformation required tochange one coordinate frame into the next. This transformationtakes the familiar form The above equation may be interpreted as a means totransform frame n-1 into frame n by means of four out ofthe five operations indicated. It is known that only fourtransformations are needed to locate a coordinate frame withrespect to the previous one. When consecutive axes are notparallel, the value of/3. is defined to be zero, while for thecase when consecutive axes are parallel, d. is the variablechosen to be zero.When coordinate frames are placed in conformance withthe modified Denavit-Hartenberg method, the transformationsgiven in the above equation will apply to all transforms ofone frame into the next, and these may be written in ageneric matrix form, where the elements of the matrix arefunctions of the kinematic parameters. These parameters aresimply the variables of the transformations: the joint angle0., the common normal offset d., the link length a., the angleof twist a., and the angle /3. The matrix form is usuallyexpressed as follows:For a serial linkage, such as a robot manipulator, a coordinateframe is attached to each consecutive link so that both theinstantaneous position together with the invariant geometryare described by the previous matrix transformation. Thetransformation from the base link to the nth link will thereforebe given byFig. 3 shows the PUMA manipulator with theDenavit-Hartenberg frames attached to each link, togetherwith world coordinate frame and a tool frame. The transformationfrom the world frame to the base frame of themanipulator needs to be considered carefully, since there arepotential parameter dependencies if certain types of transformsare chosen. Consider Fig. 4, which shows the world framexw, y, z, the frame Xo, Yo, z0 which is defined by a DHtransform from the world frame to the first joint axis ofthe manipulator, frame Xb, Yb, Zb, which is the PUMAmanufacturers defined base frame, and frame xl, Yl, zl whichis the second DH frame of the manipulator. We are interestedin determining the minimum number of parameters requiredto move from the world frame to the frame x, Yl, z. Thereare two transformation paths that will accomplish this goal:Path 1: A DH transform from x, y, z, to x0, Yo, zoinvolving four parameters, followed by another transformfrom xo, Yo, z0 to Xb, Yb, Zb which will involve only twoparameters b and d in the transformFinally, another DH transform from xb, Yb, Zb to Xt, y, Zwhich involves four parameters except that A01 and 4 areboth about the axis zo and cannot therefore be identifiedindependently, and Adl and d are both along the axis zo andalso cannot be identified independently. It requires, therefore,only eight independent kinematic parameters to go from theworld frame to the first frame of the PUMA using this path.Path 2: As an alternative, a transform may be defined directlyfrom the world frame to the base frame Xb, Yb, Zb. Since thisis a frame-to-frame transform it requires six parameters, suchas the Euler form:The following DH transform from xb, Yb, zb tO Xl, Yl, zlwould involve four parameters, but A0 may be resolved into4, 0b, , and Ad resolved into Pxb, Pyb, Pzb, reducing theparameter count to two. It is seen that this path also requireseight parameters as in path i, but a different set.Either of the above methods may be used to move fromthe world frame to the second frame of the PUMA. In thiswork, the second path is chosen. The tool transform is anEuler transform which requires the specification of sixparameters:The total number of parameters used in the kinematic modelbecomes 30, and their nominal values are defined in Table12.2 Identification MethodologyThe kinematic parameter identification will be performed asa multidimensional minimisation process, since this avoids thecalculation of the system Jacobian. The process is as follows:1. Begin with a guess set of kinematic parameters, such asthe nominal set.2. Select an arbitrary set of joint angles for the PUMA.3. Calculate the pose of the PUMA end-effector.4. Measure the actual pose of the PUMA end-effector forthe same set of joint angles. In general, the measured andpredicted pose will be different.5. Modify the kinematic parameters in an orderly manner inorder to best fit (in a least-squares sense) the measuredpose to the predicted pose.The process is applied not to a single set of joint angles butto a number of joint angles. The total number of joint anglesets required, which also equals the number of physicalmeasurement made, must satisfywhereKp is the number of kinematic parameters to be identifiedN is the number of measurements (poses) takenDr represents the number of degrees of freedom present ineach measurementIn the system described in this paper, the number of degreesof freedom is given bysince full pose is measured. In practice, many more measurementsshould be taken to offset the effect of noise in theexperimental measurements. The optimisation procedure usedis known as ZXSSO, and is a standard library function in theIMSL package 14.2.3 Pose MeasurementIt is apparent from the above that a means to determine thefull pose of the PUMA is required in order to perform thecalibration. This method will now be described in detail. Theend-effector consists of an arrangement of five precisiontoolingballs as shown in Fig. 5. Consider the coordinates ofthe centre of each ball expressed in terms of the tool frame(Fig. 5) and the world coordinate frame, as shown in Fig. 6.The relationship between these coordinates may be writtenaswhere Pi is the 4 x 1 column vector of the coordinates ofthe ith ball expressed with respect to the world frame, P isthe 4 x 1 column vector of the coordinates of the ith ballexpressed with respect to the tool frame, and T is th
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