2022
Control of Rough Terrain Vehicles Using Deep Reinforcement Learning
RA-L 2022
We explore the potential to control terrain vehicles using deep reinforcement in scenarios where human operators and traditional control methods are inadequate. This letter presents a controller that perceives, plans, and successfully controls a 16-tonne forestry vehicle with two frame articulation