ICRA'09 Paper Abstract


Paper FrB3.3

Marzorati, Daniele (UniversitÓ di Milano - Bicocca), Matteucci, Matteo (Politecnico di Milano), Migliore, Davide (Politecnico di Milano), Sorrenti, Domenico G. (UniversitÓ di Milano - Bicocca)

On the Use of Inverse Scaling in Monocular SLAM

Scheduled for presentation during the Regular Sessions "Mapping - II" (FrB3), Friday, May 15, 2009, 11:10−11:30, Room: 401

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 24, 2022

Keywords SLAM, Mapping, Computer Vision for Robotics and Automation


Recent works have shown that it is possible to solve the Simultaneous Localization And Mapping problem using an Extended Kalman Filter and a single perspective camera. The principal drawback of these works is an inaccurate modeling of measurement uncertainties, which therefore causes inconsistencies in the filter estimations. A possible solution to proper uncertainty modeling is the Unified Inverse Depth parametrization. In this paper we propose the Inverse Scaling parametrization that still allows an un-delayed initialization of features, while reducing the number of needed parameters and simplifying the measurement model. This novel approach allows a better uncertainty modeling of both low and high parallax features and reduces the likelihood of inconsistencies. Experiments in simulation demonstrate that the use of the Inverse Scaling solution improves the performance of the monocular EKF SLAM filter when compared with the Unified Inverse Depth approach; experiment on real data confirm the applicability of the idea.



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