Simulation results for localization and mapping algorithms

Abstract

The main goal of this research was to use simulation to compare the performances of three simultaneous localization and mapping (SLAM) algorithms and show the superiority of one algorithm's performance over the performance of the other two algorithms. The superior algorithm from the simulation experiments may be used to test an unmanned ground vehicle's (UGV's) capability to explore the complex subterranean environment for various Department of Defense (DOD) missions. Using simulation shows the performance of these algorithms and aids in the development of a robotic platform that has the capability to perform the localization and mapping of subterranean environments in a cost effect manner. Simulation, using the robotic simulator STAGE, provided a platform to implement multiple algorithms easily in multiple topologies and to compare the performance of three algorithms: CoreSLAM, Gmapping, and HectorSLAM, in a cost effective manner without an actual robot.