Inverse Depth Parametrization for Monocular SLAM

Recent work has shown that the probabilistic SLAM approach of explicit uncertainty propagation can succeed in permitting repeatable 3D real-time localization and mapping even in the `pure vision' domain of a single agile camera with no extra sensing. An issue which has caused difficulty in monocular SLAM however is the initialization of features, since information from multiple images acquired during motion must be combined to achieve accurate depth estimates. This has led algorithms to deviate from the desirable Gaussian uncertainty representation of the EKF and related probabilistic filters during special initialization steps. In this paper we present a new unified parametrization for point features within monocular SLAM which permits efficient and accurate representation of uncertainty during undelayed initialisation and beyond, all within the standard EKF (Extended Kalman Filter). The key concept is direct parametrization of inverse depth, where there is a high degree of linea...

• Type: Journal
• Year: 2008
• Where: TROB
• Authors: Javier Civera, Andrew J. Davison, J. M. M. Montiel
• Keywords: Explicit Uncertainty Propagation, Monocular Slam, Probabilistic Slam Approach, TROB 2008