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 minimisation 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.
CitationIla, Viorela; Andrade-Cetto, Juan; Sanfeliu, Alberto. "Efficient vision-based loop closing techniques for delayed state robot mapping". A: 2008 Frontier Science Conference Series for Young Researchers: Experimental Cognitive Robotics (FSCYR:ECR), Kanagawa, Japó, 2008. ESF-JSPS, 2008, p. 1-6.
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