AdaDexGrasp learns to fuse point clouds with finger-level tactile labels to generate, judge, and correct dexterous grasps, reporting 91%/82%/83% success on seen, unseen-object, and unseen-category sets in simulation.
In: 2014 IEEE International Conference on Robotics and Automation (ICRA)
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AdaDexGrasp: Adaptive Dexterous Grasping via 3D Visuo-Tactile Representation Fusion
AdaDexGrasp learns to fuse point clouds with finger-level tactile labels to generate, judge, and correct dexterous grasps, reporting 91%/82%/83% success on seen, unseen-object, and unseen-category sets in simulation.