6DoF Monte Carlo Localization in a 3D world with Laser Range Finders

In mobile robotics, localization plays a key role in every task assigned to a robot. This report describes the probabilistic module we developed to solve the localization problem in our autonomous driving vehicle. Our method uses a complete 6DoF approach within a 3D motion model, in order to correctly integrate the error caused by dead reckoning. Furthermore, the description of the environment is a 3D voxel representation. We base on particle filtering, in the localization process. An ad-hoc simulation environment has been developed, for testing the effectiveness of the motion model. Finally, we performed some field experiments, to demonstrate that our approach consistently locates the 6DoF position of the vehicle along the driven path on the test site