Robust Invariants From Functionally Constrained Motion

We address in the problem of control-based recovery of robot pose and the environmental lay-out. Panoramic sensors provide us with an 1D projection of characteristic features of a 2D operation map. Trajectories of these projections contain the 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, like area, 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 our method can be embedded in the well-known affine reconstruction paradigm. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-98-08. This technical report is available at ScholarlyCommons: http://repository.upenn.edu/cis_reports/809 Robust Invariants from Functionally Constrained Mot ion

[1]  Margrit Betke,et al.  Mobile robot localization using landmarks , 1997, IEEE Trans. Robotics Autom..

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

[3]  Francis Seeley Foote,et al.  Surveying theory and practice , 1940 .

[4]  Claude Pégard,et al.  A mobile robot using a panoramic view , 1996, Proceedings of IEEE International Conference on Robotics and Automation.