Dexterous manipulationExpert
PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation
PointWAM is a preprint describing a 3D world action model for dexterous robotic manipulation. It represents the scene and hands as 3D point trajectories in a shared space-time frame, and is pretrained on 1.15 million human demonstration episodes before fine-tuning on robot data. On ten DexJoCo tasks it reaches 69.0% average success, 11.7 points above GR00T N1.6, and on a real humanoid it beats robot-pretrained VLAs by up to 25 points on square-peg insertion.