ForestTrav: Accurate, Efficient and Deployable Forest Traversability Estimation for Autonomous Ground Vehicles

Understand

Autonomous navigation in unstructured vegetated environments remains an open challenge.

• To successfully operate in these settings, ground vehicles must assess the traversability of the environment and determine which vegetation is pliable enough to push through.
• In this work, we propose a novel method that combines a high-fidelity and feature-rich 3D voxel representation while leveraging the structural context and sparseness of SCNN's to assess Traversability Estimation (TE) in densely vegetated environments.
• The proposed method is thoroughly evaluated on an accurately-labeled real-world data set that we provide to the community.