3D Mapping and Localization Using Leveled Map Accelerated ICP

摘要

The ability of a robot to navigate itself in the environment is a crucial step towards its autonomy. In this article a method for simultaneous localization an mapping (SLAM) of mobile robots in six degrees of freedom (6DOF) is presented. As an input, the method is using 3D range data acquired from a continuously inclined laser rangefinder. The localization and mapping task is equal to the registration of multiple 3D images into a common frame of reference. For this purpose, an extended version of the Iterative Closest Point (ICP) algorithm is being used. In order to accelerate the time-demanding 6DOF image registration, the method is modified in the following way: first, a 3DOF registration is performed using leveled maps extracted from the 3D data, followed by a robust 6DOF registration. The proposed method compared to a single phase 6DOF registration gives promising results in structured environments.