Dynamic Resolution Terrain Estimation for Autonomous (Dirt) Road Driving Fusing LiDAR and Vision

Abstract

For autonomous driving on rural or dirt roads-neither urban nor off-road - a large terrain area needs to be estimated at high spatial resolution. However, available computing time is very limited. Since different areas of the ground surface require different minimum resolution, we propose a dynamic resolution terrain estimation.Based on support points, accumulated measurements are spatially smoothed to a continuous terrain model using maximum a posteriori estimation. Splitting the terrain into tiles, we dynamically adjust the support point resolution of single tiles, depending on their accuracy in areas of interest. Areas of interest are determined by fusing information on probable road areas from LiDAR and vision preprocessing steps.As demonstrated in real-world examples, our approach can model the terrain almost as accurately as if all tiles had the highest resolution, but with much less computational effort.