  Inspired by the recent success of application of dense data approach by using
ORB-SLAM and RGB-D SLAM, we propose a better pipeline of real-time SLAM in
dynamics environment. Different from previous SLAM which can only handle static
scenes, we are presenting a solution which use RGB-D SLAM as well as YOLO
real-time object detection to segment and remove dynamic scene and then
construct static scene 3D. We gathered a dataset which allows us to jointly
consider semantics, geometry, and physics and thus enables us to reconstruct
the static scene while filtering out all dynamic objects.
