Vehicle Terrain Interaction

Vehicle terrain interaction research focuses on accurately modeling and predicting how vehicles, particularly wheeled robots, behave on uneven or unstructured terrain, aiming to improve autonomous navigation and control. Current efforts concentrate on developing data-driven models, often employing machine learning techniques like neural networks and model predictive control, to estimate traversability and predict 6-DoF vehicle dynamics in challenging environments. This work is crucial for advancing autonomous off-road navigation in applications ranging from planetary exploration to high-speed off-road driving, improving safety and efficiency through more accurate and robust vehicle-terrain interaction models.