Self-Calibration and Error Compensation of Flexible Coordinate Measuring Robot

A self-calibration method, based on relative measurement instead of Cartesian coordinate measurement, is proposed to calibrate flexible coordinate measuring robot on the manufacturing industry. Compared with traditional calibration methods this self-calibration is more advantageous in terms its implementation and the accuracy of parameter estimation. In order to achieve the high accuracy required by a measuring robot, thermally-induced errors have to be taken into account. The effect of thermally-induced errors on the measuring robot performance is under investigation. A general methodology has been developed to calibrate these errors. Principal component analysis and orthogonal regression are used to construct the empirical models so that the thermally-induced error can be compensated for by monitoring the system´s temperature field, therefore the measuring robot´s accuracy can be maintained. Intensive experimental studies are conducted to check validity of the theoretical results. The results demonstrate that using this technique to calibrate measuring robot, the measuring accuracy of robot has been sharply improved 3 times.