This paper shows results on outdoor vision-based loop closing for Simultaneous Localization and Mapping. Our experiments show that for loops of over 50m, the pose estimates maintained with a Delayed-State Extended Information Filter are consistent enough to guarantee assertion of vision-based pose constraints for loop closure, provided no necessary information links are added to the estimator. The technique computes relative pose constraints via a robust least squares minimization of 3D point correspondences, which are in turn obtained from the matching of SIFT features over candidate image pairs. We propose a loop closure test that checks both for closeness of means and for highly informative updates at the same time.


computer vision, robots.

Scientific reference

V. Ila, J. Andrade-Cetto, R. Valencia and A. Sanfeliu. Vision-based loop closing for delayed state robot mapping, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007, San Diego, CA, USA, pp. 3892-3897, IEEE.