Object Subtraction Planar RGB-D SLAM

When using RGB-D SLAM algorithms, a robot often considers dynamic and static objects during the 3D mapping step. To address this problem, this paper aims to present an approach in planar RGB-D SLAM, here called Object Subtraction SLAM (OS-SLAM), using only low-cost RGB-D sensors. Our approach subtracts objects from the 3D environment and creates a clean 3D map projecting estimated planes without identified objects encountered along the mapping procedure. To validate our approach, we performed two experiments, one in a real environment and one with an open dataset. The algorithms were applied to a TurtleBot 2 platform which has a RGB-D sensor as its main sensor. The results demonstrates the efficiency on generating a clean and accurate map using the OS-SLAM algorithm.