3-D motion estimation, understanding, and prediction from nosiy image sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
An analytic solution for the perspective 4-point problem
Computer Vision, Graphics, and Image Processing
A survey of kinematic calibration
The robotics review 1
Robot Manipulators: Mathematics, Programming, and Control
Robot Manipulators: Mathematics, Programming, and Control
IEEE Transactions on Pattern Analysis and Machine Intelligence
| Hi-index | 0.98 |
A self-calibration model of a hand-eye system having a stereo camera mounted on the manipulator end-effector is presented. The proposed self-calibration method is based on estimating the motion parameters of an object observed by the stereo camera under varying manipulator configurations. The object is assumed fixed in space or moving with a known form of trajectory but with unknown parameters. First, we derive theoretically a general form of self-calibration model for an overview of the proposed method. Then, a detailed set of self-calibration equations is formulated by relating the noise and biases involved in the hand-eye system to the variations of an object pose estimation error in time. The noise and biases include the uncertainty and nonlinearity involved in imaging and 3-D reconstruction, as well as the uncalibrated optical and kinematic parameters of the camera and manipulator. Simulations are conducted to verify the validity of the proposed self-calibration model.