GraspIT provides ~316k annotated RGBD frames with ~2.3M slip-test-validated 6-DoF grasp candidates and a bidirectional sim-to-real registration pipeline, all released as open-source Docker containers.
Effi- cient grasping from RGBD images: Learning using a new rectangle representation
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GraspIT: A Dataset Bridging the Sim-to-Real gap and back for Validated Grasping SE(3) Pose Generation
GraspIT provides ~316k annotated RGBD frames with ~2.3M slip-test-validated 6-DoF grasp candidates and a bidirectional sim-to-real registration pipeline, all released as open-source Docker containers.