Complex Analysis for Reconstruction from Controlled Motion

We address the problem of control-based recovery of robot pose and the environmental lay-out. Panoramic sensors provide us with a 1D projection of characteristic features of a 2D operation map. Trajectories of these projections contain information about the position of a priori unknown landmarks in the environment. We introduce here the notion of spatiotemporal signatures of projection trajectories. These signatures are global measures, characterized by considerably higher robustness with respect to noise and outliers than the commonly applied point correspondence. By modeling the 2D motion plane as the complex plane we show that by means of complex analysis the reconstruction problem is reduced to a system of two quadratic - or even linear in some cases - equations in two variables. The algorithm is tested in simulations and real experiments.

[1]  Naokazu Yokoya,et al.  Visual surveillance and monitoring system using an omnidirectional video camera , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[2]  Hormoz Shariat,et al.  Motion Estimation with More than Two Frames , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Allen R. Hanson,et al.  Description and reconstruction from image trajectories of rotational motion , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[4]  Avinash C. Kak,et al.  Fast Vision-guided Mobile Robot Navigation Using Model-based Reasoning And Prediction Of Uncertainties , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Avinash C. Kak,et al.  Fast vision-guided mobile robot navigation using model-based reasoning and prediction of uncertainties , 1992, CVGIP Image Underst..

[6]  D.J. Kriegman,et al.  Stereo vision and navigation in buildings for mobile robots , 1989, IEEE Trans. Robotics Autom..

[7]  Shree K. Nayar,et al.  Catadioptric omnidirectional camera , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Gregory D. Hager,et al.  Global Signatures for Robot Control and Reconstruction , 2000 .

[9]  M. Srinivasan,et al.  Range estimation with a panoramic visual sensor , 1997 .

[10]  Yasushi Yagi,et al.  Map-based navigation for a mobile robot with omnidirectional image sensor COPIS , 1995, IEEE Trans. Robotics Autom..

[11]  Carlos A. Berenstein,et al.  Complex Variables: An Introduction , 1997 .

[12]  Richard Szeliski,et al.  3-D Scene Data Recovery Using Omnidirectional Multibaseline Stereo , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  Tom,et al.  Epipolar Geometry for Panoramic Cameras Epipolar Geometry for Panoramic Cameras ? , 1998 .

[14]  Gérard G. Medioni,et al.  Map-based localization using the panoramic horizon , 1995, IEEE Trans. Robotics Autom..