Precise 3D Calibration of Wafer Handling Robot by Visual Detection and Tracking of Elliptic-shape Wafers

Abstract

This work provides a framework for the 3D calibration of wafers and a wafer handling robot by monocular vision. The proposed method precisely reconstructs the 3D poses of wafers from a set of images captured by the camera mounted on the robot. In addition, it calibrates the robot kinematics simultaneously. A robust ellipse detection and tracking algorithm based on the edge arcs is developed to recognize wafers among images. Then a joint optimization is constructed from a multi-object pose graph to solve the 3D poses of wafers and other calibration parameters of the robot-camera system. The proposed tracking method is able to associate multiple incomplete elliptic segments using a Gaussian Mixture Model-based registration algorithm. The algorithm is point-based where no feature descriptor is required. The proposed 3D pose optimization incorporates shape constraints, and is more accurate than the point-wise reconstruction produced by classic bundle adjustment methods.