Real-Time 6-DOF Monocular Visual SLAM based on ORB-SLAM2

Here, real-time 6-DOF monocular visual SLAM, which can be mapping with texture, is presented. The proposed method aims to compute 6-DOF camera pose and 3D landmarks position using monocular camera as the only sensor, and utilize texture to render the map of visualization quickly. By exploiting additional structural information such as camera height from the ground, the epipolar geometry is transformed into the perspective-n-point problem, restoring the indeterminate scale. In addition, this structural information is used to segment the point cloud of ground. This is of great help to clustering obstacles and constructing the spatial segmentation relationship of point cloud. The real-time performance of system is demonstrated using only GPU to render map. The effectiveness of the proposed method is demonstrated on various sequences including the KITTI dataset and outdoor image sequences captured on experimental vehicle.