Good news! I have not had time yet to read this new research paper by Pieter Abbeel and his collaborators, but Pieter Abbeel is a well known and highly cited researcher in the field.
"... Building on these advances, we present a Framework for Efficient Robotic Manipulation (FERM) that utilizes data augmentation and unsupervised learning to achieve extremely sample-efficient training of robotic manipulation policies with sparse rewards. We show that, given only 10 demonstrations, a single robotic arm can learn sparse-reward manipulation policies from pixels, such as reaching, picking, moving, pulling a large object, flipping a switch, and opening a drawer in just 15-50 minutes of real-world training time. ..."
Here is the link to the respective research paper:
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