Traversability Analysis for Off-Road Vehicles using Stereo and Radar Data

Accurate and robust environmental perception is a critical requirement to address unsolved issues in the context of outdoor navigation, including safe interaction with living beings, obstacle detection, cooperation with other vehicles, mapping, and situation awareness in general. Aim of this paper is the development of perception algorithms to enhance the automatic understanding of the environment and develop advanced driving assistance systems for off-road vehicles. Specifically, the problem of terrain traversability assessment is addressed. Two strategies are presented. One exploits stereo data to segment drivable ground using a self-learning approach, without explicitly dealing with the obstacle detection issue, whereas the other one features a radar-stereo integrated system to detect and characterize obstacles. The paper details both methods and presents experimental results, obtained with a vehicle operating in rural and agricultural contexts.