Uncalibrated visual servoing using the fundamental matrix

This paper describes a new algorithm for visual control of an uncalibrated 3 DOF joint system, using two weakly calibrated fixed cameras. The algorithm estimates on-line the Image Jacobian, a matrix which linearly relates joint velocity and image feature velocity. In our experiments we prove that by using the fundamental matrix, robustness of the estimation in the presence of noise is significantly increased with respect to already existing algorithms in specialized literature.

[1]  Lee E. Weiss,et al.  Dynamic sensor-based control of robots with visual feedback , 1987, IEEE Journal on Robotics and Automation.

[2]  Seth Hutchinson,et al.  Visual Servo Control Part I: Basic Approaches , 2006 .

[3]  Clifford C. Geschke A System for Programming and Controlling Sensor-Based Robot Manipulators , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Richard I. Hartley,et al.  In Defense of the Eight-Point Algorithm , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  François Chaumette,et al.  Visual servo control. II. Advanced approaches [Tutorial] , 2007, IEEE Robotics & Automation Magazine.

[6]  Rajeev Sharma,et al.  The role of exploratory movement in visual servoing without calibration , 1998, Robotics Auton. Syst..

[7]  O. Faugeras,et al.  The Geometry of Multiple Images , 1999 .

[8]  Yoshiaki Shirai,et al.  Guiding a robot by visual feedback in assembling tasks , 1973, Pattern Recognit..

[9]  Harvey Lipkin,et al.  Uncalibrated dynamic visual servoing , 2004, IEEE Transactions on Robotics and Automation.

[10]  François Chaumette,et al.  Visual servo control. I. Basic approaches , 2006, IEEE Robotics & Automation Magazine.

[11]  M. Jagersand,et al.  Evaluation of model independent image-based visual servoing , 2004, First Canadian Conference on Computer and Robot Vision, 2004. Proceedings..

[12]  Lizardo Pari,et al.  A New Method for the Estimation of the Image Jacobian for the Control of an Uncalibrated Joint System , 2005, IbPRIA.

[13]  Radu Horaud,et al.  Controlling robots with two cameras: how to do it properly , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[14]  Gregory D. Hager,et al.  A modular system for robust positioning using feedback from stereo vision , 1997, IEEE Trans. Robotics Autom..

[15]  Danica Kragic,et al.  Advances in robot vision , 2005, Robotics Auton. Syst..

[16]  S. Hutchinson,et al.  Visual Servo Control Part II : Advanced Approaches , 2007 .

[17]  Lee E. Weiss,et al.  Dynamic visual servo control of robots: An adaptive image-based approach , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[18]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[19]  Danica Kragic,et al.  Survey on Visual Servoing for Manipulation , 2002 .

[20]  Peter I. Corke,et al.  A tutorial on visual servo control , 1996, IEEE Trans. Robotics Autom..

[21]  E. Malis,et al.  2 1/2 D Visual Servoing , 1999 .

[22]  Minoru Asada,et al.  Adaptive binocular visual servoing for independently moving target tracking , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[23]  Jiang Qian,et al.  Online estimation of image Jacobian matrix by Kalman-Bucy filter for uncalibrated stereo vision feedback , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[24]  Peter Corke,et al.  Visual Control of Robots: High-Performance Visual Servoing , 1996 .

[25]  Olivier D. Faugeras,et al.  The geometry of multiple images - the laws that govern the formation of multiple images of a scene and some of their applications , 2001 .