Pablo F. Alcantarilla, Luis M. Bergasa Department of Electronics, University of Alcalá, Madrid, Spain

Olivier Stasse, Sebastien DruonJoint Robotics Laboratory, CNRS-AIST, Tsukuba, Japan

Frank DellaertSchool of Interactive Computing, Georgia Institute of Technology, Atlanta, USA

Submission to Autonomous Robots

• STEREO VISUAL SLAM• We learn a 3D map of the environment, by means

of stereo visual SLAM techniques

• MONOCULAR VISION-BASED

LOCALIZATION• Monocular Vision-Based Localization given a prior

3D map and camera poses from a previous 3D reconstruction

• We perform Visibility Prediction to predict the most highly visible 3D points given a prior camera pose

• Then, we establish 2D-3D correspondences between

detected 2D features and 3D map elements

• Finally, after data association we solve the PnP problem

and estimate the localization of the robot in the map

• LOCALIZATION EXPERIMENTS

O Detected 2D Features

+ Visible 3D Map Points Re-Projections

Inlier PnP problem

Outlier PnP problem

+ Predicted Visible 3D Points

+ 3D Map Points

RGB Camera Pose

Robot Trajectory