Simulated Mobile Self-Location Using 3D Range Sensing and an A-Priori Map

Self-location is a critical component of unmanned ground vehicle operation. While GPS has met this need for many applications, there are others, indoors and outdoors, where GPS is not available or reliable. This paper discusses the investigation of a method to self-locate using an onboard 3D range sensor, when a 3D map of the environment is available. We have examined the performance in terms of what is needed for data coverage and terrain types. Localization is accomplished through surface fitting. Surface fitting is an important component of Simultaneous Localization and Mapping (SLAM) for 3D terrains. Three environments were chosen for testing, including a hilly desert scene, an indoor corridor scene, and a forest scene. A simulated 3D range sensor was used to scan models corresponding to these three environments. Various parameters were modified to identify strong and weak points in the scheme.