SimToolReal: An Object-Centric Policy for Zero-Shot Dexterous Tool Manipulation
SimToolReal trains a single general-purpose reinforcement learning policy in simulation to manipulate diverse tools toward random goals. This learned skill, focusing on reaching any pose, is then transferred to novel real-world tools using vision models. The method avoids task-specific training and reward tuning, enabling zero-shot dexterous tool manipulation across different objects and tasks.