Traversability mapping in off-road environment using semantic segmentation

Autonomous driving in off-road environments is challenging as it does not have a definite terrain structure. Assessment of terrain traversability is the main factor in deciding the autonomous driving capability of the ground vehicle. Traversability in off-road environments is defined as the drivable track on the trails by different vehicles used in autonomous driving. It is very crucial for the autonomous ground vehicle (AGV) to avoid obstacles such as trees, boulders etc. while traversing through the trails. The goal of this research has three main objectives: a) collection of 2D camera data in the off-road / unstructured environment, b) annotation of 2D camera data depending on the vehicles’ ability to drive through the trails , and c) application of semantic segmentation algorithm on the labeled dataset to predict the trajectory based on the type of ground vehicle. Our models and labeled datasets will be publicly available.