Real-time 6-DOF monocular visual SLAM in a large-scale environment

Abstract

Real-time approach for monocular visual simultaneous localization and mapping (SLAM) within a large-scale environment is proposed. From a monocular video sequence, the proposed method continuously computes the current 6-DOF camera pose and 3D landmarks position. The proposed method successfully builds consistent maps from challenging outdoor sequences using a monocular camera as the only sensor, while existing approaches have utilized additional structural information such as camera height from the ground. By using a binary descriptor and metric-topological mapping, the system demonstrates real-time performance on a large-scale outdoor environment without utilizing GPUs or reducing input image size. The effectiveness of the proposed method is demonstrated on various challenging video sequences including the KITTI dataset and indoor video captured on a micro aerial vehicle.