A simple technique for improving camera displacement estimation in eye-in-hand visual servoing

A simple technique for estimating the camera displacement from point correspondences in eye-in-hand visual servoing is presented. The idea for providing more accurate results than existing methods consists of taking into account that the point correspondences used during the camera motion correspond to stationary spatial points, hence exploiting additional information, This is done by first estimating the object Euclidean structure and then estimating the camera displacement from this estimate.

[1]  Zhengyou Zhang,et al.  Determining the Epipolar Geometry and its Uncertainty: A Review , 1998, International Journal of Computer Vision.

[2]  Paul D. Fiore,et al.  Efficient Linear Solution of Exterior Orientation , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Olivier Faugeras,et al.  Motion and Structure from Motion in a piecewise Planar Environment , 1988, Int. J. Pattern Recognit. Artif. Intell..

[4]  William J. Wilson,et al.  Relative end-effector control using Cartesian position based visual servoing , 1996, IEEE Trans. Robotics Autom..

[5]  Koichiro Deguchi,et al.  Optimal motion control for image-based visual servoing by decoupling translation and rotation , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[6]  François Chaumette,et al.  2 1/2 D Visual Servoing with Respect to Unknown Objects Through a New Estimation Scheme of Camera Displacement , 2000, International Journal of Computer Vision.

[7]  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 .

[8]  Philippe Martinet,et al.  Position based visual servoing: keeping the object in the field of vision , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[9]  Rachid Deriche,et al.  Robust Recovery of the Epipolar Geometry for an Uncalibrated Stereo Rig , 1994, ECCV.

[10]  Camillo J. Taylor,et al.  Robust vision-based pose control , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[11]  Long Quan,et al.  Linear N-Point Camera Pose Determination , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Ezio Malis,et al.  Vision-based control invariant to camera intrinsic parameters: stability analysis and path tracking , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[13]  Kostas Daniilidis,et al.  Linear Pose Estimation from Points or Lines , 2002, ECCV.

[14]  Tsutomu Kimoto,et al.  Manipulator control with image-based visual servo , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[15]  Peter I. Corke,et al.  A new partitioned approach to image-based visual servo control , 2001, IEEE Trans. Robotics Autom..

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

[17]  Narendra Ahuja,et al.  Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Patrick Rives,et al.  A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..

[19]  Gregory D. Hager,et al.  Fast and Globally Convergent Pose Estimation from Video Images , 2000, IEEE Trans. Pattern Anal. Mach. Intell..