Visual odometry priors for robust EKF-SLAM

— One of the main drawbacks of standard visual EKF-SLAM techniques is the assumption of a general camera motion model. Usually this motion model has been implemented in the literature as a constant linear and angular velocity model. Because of this, most approaches cannot deal with sudden camera movements, causing them to lose accurate camera pose and leading to a corrupted 3D scene map. In this work we propose increasing the robustness of EKF-SLAM techniques by replacing this general motion model with a visual odometry prior, which provides a real-time relative pose prior by tracking many hundreds of features from frame to frame. We perform fast pose estimation using the two-stage RANSAC-based approach from [1]: a two-point algorithm for rotation followed by a one-point algorithm for translation. Then we integrate the estimated relative pose into the prediction step of the EKF. In the measurement update step, we only incorporate a much smaller number of landmarks into the 3D map to ...

• Type: Journal
• Year: 2010
• Where: ICRA
• Authors: Pablo Fernández Alcantarilla, Luis Miguel Bergasa, Frank Dellaert
• Keywords: Angular Velocity Model, Constant Linear, ICRA 2010, Motion Model, Robotics