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This work was supported in part by the National Natural Science Foundation of China under Grant T2388101, in part by the Huawei Industry-University Cooperation Project under Grant TC20250106029, and in part by the Pre-research Task (No. SKLRS202408B) of the State Key Laboratory of Robotics and Systems, Harbin Institute of Technology
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Training on a new multi-object dataset with explicit modeling of grasp offsets and pre-grasp configurations enables an end-to-end network to achieve significantly improved dexterous grasping performance in simulation and on a real robot.
Finally, a method exists to create 3D human-scene interaction models from casual captures that are stable enough for use in physics simulations and deployment on real-world robots.
