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

Marzorati, D., Matteucci, M., Migliore, D., & Sorrenti, D. (2009). On the use of inverse scaling in monocular SLAM. In 2009 IEEE International Conference on Robotics and Automation : (ICRA); Kobe, Japan, 12 - 17 May 2009 (pp.2030-2036). Institute of Electrical and Electronics Engineers Inc. [10.1109/ROBOT.2009.5152640].

On the use of inverse scaling in monocular SLAM

Marzorati, D;Sorrenti, DG
2009

Abstract

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
No
slide + paper
Scientifica
SLAM, mapping, computer vision for robotics and automation
English
2009 IEEE International Conference on Robotics and Automation MAY 12-17
978-1-4244-2788-8
Marzorati, D., Matteucci, M., Migliore, D., & Sorrenti, D. (2009). On the use of inverse scaling in monocular SLAM. In 2009 IEEE International Conference on Robotics and Automation : (ICRA); Kobe, Japan, 12 - 17 May 2009 (pp.2030-2036). Institute of Electrical and Electronics Engineers Inc. [10.1109/ROBOT.2009.5152640].
Marzorati, D; Matteucci, M; Migliore, D; Sorrenti, D
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/6481
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