Traction Model

Traction modeling focuses on accurately predicting the interaction between a vehicle's wheels and the terrain, crucial for optimizing vehicle control and navigation, particularly in challenging off-road environments. Current research emphasizes developing probabilistic models, often employing neural networks and techniques like Kalman filtering, to capture the inherent uncertainty in traction parameters and improve the robustness of predictions. This improved understanding of traction dynamics is vital for enhancing the efficiency, safety, and autonomy of various vehicles, from mobile robots to autonomous cars, by enabling more reliable motion planning and control strategies.