Inverse Depth to Depth Conversion for Monocular SLAM

— Recently it has been shown that an inverse depth parametrization can improve the performance of real-time monocular EKF SLAM, permitting undelayed initialization of features at all depths. However, the inverse depth parametrization requires the storage of 6 parameters in the state vector for each map point. This implies a noticeable computing overhead when compared with the standard 3 parameter XYZ Euclidean encoding of a 3D point, since the computational complexity of the EKF scales poorly with state vector size. In this work we propose to restrict the inverse depth parametrization only to cases where the standard Euclidean encoding implies a departure from linearity in the measurement equations. Every new map feature is still initialized using the 6 parameter inverse depth method. However, as the estimation evolves, if according to a linearity index the alternative XYZ coding can be considered linear, we show that feature parametrization can be transformed from inverse depth to X...

• Type: Conference
• Year: 2007
• Where: ICRA
• Authors: Javier Civera, Andrew J. Davison, J. M. M. Montiel
• Keywords: ICRA 2007, Inverse Depth, Inverse Depth Parametrization, Parameter Inverse Depth, Robotics