Camera-aided SCARA arm calibration

The focus of this thesis is the kinematic calibration of a SCARA arm with a hand-mounted camera. Kinematic calibration can greatly improve the accuracy of SCARA arms, which are widely used in electronic assembly lines. Vision-based robot calibration has the potential of being a fast, nonintrusive, low-cost, and autonomous approach. In this thesis, we apply a vision-based technique to calibrate SCARA arms. The robot under investigation is modeled by the modified complete and parametrically continuous model. By repeatedly calibrating the camera, the pose of the robot end-effector are collected at various robot measurement configurations. A least squares technique is then applied to estimate the geometric error parameters of the SCARA arm using the measured robot poses. In order to improve the robustness of the method, a new approach is proposed to calibrate the hand-mounted camera. The calibration algorithm is designed to deal with the case in which the camera sensor plane is nearly-parallel to the camera calibration board. Practical issues regarding robot calibration in general and SCARA arm calibration in particular are also addressed. Experiment studies reveal that the proposed camera-aided approach is a viable means for accuracy enhancement of SCARA arms.