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Verti-WM: A Physics-Aided Exteroceptive World Model for Off-Road Reinforcement Learning
Reinforcement learning for off-road navigation requires extensive vehicle-terrain interaction data, which are costly to collect in high-fidelity simulation. World models offer a promising alternative by replacing simulator roll-outs during policy optimization. However, an off-road world model must c
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