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Found 4 papers, 1 papers with code
BridgeData V2: A Dataset for Robot Learning at Scale
By publicly sharing BridgeData V2 and our pre-trained models, we aim to accelerate research in scalable robot learning methods.
Giving Robots a Hand: Learning Generalizable Manipulation with Eye-in-Hand Human Video Demonstrations
Eye-in-hand cameras have shown promise in enabling greater sample efficiency and generalization in vision-based robotic manipulation.
NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis
Expert demonstrations are a rich source of supervision for training visual robotic manipulation policies, but imitation learning methods often require either a large number of demonstrations or expensive online expert supervision to learn reactive closed-loop behaviors.
Vision-Based Manipulators Need to Also See from Their Hands
We study how the choice of visual perspective affects learning and generalization in the context of physical manipulation from raw sensor observations.
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