Application of Octree Map in Robotic Environment Reconstruction

Abstract

For the autonomous navigation of robots in unknown environment, aiming at resolving the shortcomings of the traditional 3D point cloud map such as unclear navigational route planning, poor local scenes processing and large storage space, an octree-based 3D reconstruction method is presented, the octree map is used in RGB-D SLAM to realize the localization and mapping of the robot in this paper. The performance of the proposed approach is evaluated with both simulated and real data. The experimental results show that it can clearly plan the navigation path for the robot, effectively improve the ghosting phenomenon of point cloud maps. As well as, it storage space is less than point cloud maps under the same image resolution, and the advantage of octree maps storage space is more obvious when the image resolution is higher. Therefore, the binarized data form of the octree map, which can effectively optimize the reconstruction of the unknown environment mapping for a mobile robot.