A keypoint-based 6-DoF grasp network trained end-to-end with a probabilistic PnP layer and a confidence map beats prior KGN variants on grasp success rate in simulation and on a small real-robot test.
Sg-bot: Object rearrangement via coarse-to-fine robotic imagination on scene graphs,
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KGN-Pro: Keypoint-Based Grasp Prediction through Probabilistic 2D-3D Correspondence Learning
A keypoint-based 6-DoF grasp network trained end-to-end with a probabilistic PnP layer and a confidence map beats prior KGN variants on grasp success rate in simulation and on a small real-robot test.