Robot Vision System for Coordinate Measurement of Feature Points on Large Scale Automobile Part

In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine（CMM）.Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error（RMSE） of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods.

A High Speed Autofocusing System for Micro System Applications

In this paper,we present a high speed autofocus system for micro system applications and design a look-up-table based autofocusing algorithm for applications when a target object is always visible,e.g.,manufacturing parts with alignment fiducials.We perform an evaluation of 24 focus measures to verify that which focus measure is the best for the look-up-table based method.From the evaluation,we find that the Chebyshev moments-based focus measure（CHEB） is the most suitable.Furthermore,we also develop a look-up-table based autofocus system that uses CHEB as the focus measure.In training phase,we offline construct a table from training images of an object that are captured at several lens distances.Each entry of table consists of focus measure computed from image and lens distance.In working phase,given an input image,the algorithm first computes the focus measure and then finds the best match focus measure from the table and looks up the corresponding lens position for moving it into the in-focus position.Our algorithm can perform autofocusing within only 2 steps of lens moving.The experiment shows that the system can perform high speed autofocusing of micro objects.