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Found 4 papers, 1 papers with code
SAGCI-System: Towards Sample-Efficient, Generalizable, Compositional, and Incremental Robot Learning
We apply our system to perform articulated object manipulation tasks, both in the simulation and the real world.
SuctionNet-1Billion: A Large-Scale Benchmark for Suction Grasping
Meanwhile, we propose a method to predict numerous suction poses from an RGB-D image of a cluttered scene and demonstrate our superiority against several previous methods.
UKPGAN: A General Self-Supervised Keypoint Detector
Keypoint detection is an essential component for the object registration and alignment.
Suction Grasp Region Prediction using Self-supervised Learning for Object Picking in Dense Clutter
This paper focuses on robotic picking tasks in cluttered scenario.
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