A Terrain-Based Vehicle Localization Approach Robust to Braking

Terrain-based vehicle localization is a valuable alternative to GPS when the signal is blocked or dynamic occlusions exist. However, braking events can induce the slips and vibrations of the vehicle and, thus, increase the errors of terrain-based position estimations. This paper develops a terrain-based localization approach which is robust to braking events. First, the terrain map is generated and stored before localization, which includes distance measurements, terrain feature data, and the geographic locations. The terrain feature data are pitch differences to eliminate the accumulated error. Next, particle-filter-based and acceleration-considered vehicle localization is proposed for position estimation. It takes into account the influence of braking in the vehicle model and the inference process. Experimental results demonstrate the repeatability of pitch difference measurements and the robustness of the proposed approach in the cases of smooth driving and braking.