Vision based system for camera tracking in eye-in-hand configuration

This paper presents an effective approach to estimate the fixed internal and varying external parameters of the camera for real time experiments using 2D-3D point correspondences. Images are acquired at each time step, a pose estimation algorithm is then employed to determine the camera pose w.r.t the object. A simple homogenous transformation is derived between the camera and end-effector to determine the position of the manipulator end-effector, as camera is mounted on the tool in eye-in-hand configuration. The paper focuses on determining the pose accurately and to look upon those issues that we encounter in real time. The major contribution of this paper is in two folds: camera pose parameters are easily and accurately recovered from 2D to 3D point correspondence; second is that experiments using real images are conducted, which presents good results.

[1]  Andrew Zisserman,et al.  Multiple View Geometry in Computer Vision (2nd ed) , 2003 .

[2]  Tommy Chang,et al.  Road detection and tracking for autonomous mobile robots , 2002, SPIE Defense + Commercial Sensing.

[3]  Warren E. Dixon,et al.  Adaptive homography-based visual servo tracking for a fixed camera configuration with a camera-in-hand extension , 2005, IEEE Transactions on Control Systems Technology.

[4]  Soren W. Henriksen,et al.  Manual of photogrammetry , 1980 .

[5]  John J. Leonard,et al.  Directed Sonar Sensing for Mobile Robot Navigation , 1992 .

[6]  Olivier D. Faugeras,et al.  A theory of self-calibration of a moving camera , 1992, International Journal of Computer Vision.

[7]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[8]  C. A. HART,et al.  Manual of Photogrammetry , 1947, Nature.

[9]  Antonis A. Argyros,et al.  Fusion of laser and visual data for robot motion planning and collision avoidance , 2003, Machine Vision and Applications.

[10]  Yiannis Aloimonos,et al.  Observability of 3D Motion , 2000, International Journal of Computer Vision.

[11]  Reinhard Koch,et al.  Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[12]  François Chaumette,et al.  Theoretical improvements in the stability analysis of a new class of model-free visual servoing methods , 2002, IEEE Trans. Robotics Autom..

[13]  S. Hutchinson,et al.  A new hybrid image-based visual servo control scheme , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[14]  François Chaumette,et al.  2 1/2 D visual servoing: a possible solution to improve image-based and position-based visual servoings , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).