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Saturday, June 15, 2019

Learning from Camera Feeds

Technically interesting.  Learning by seeing, like we do.

Model-Based Reinforcement Learning from Pixels with Structured Latent Variable Models

By Marvin Zhang and Sharad Vikram  in Bair
Imagine a robot trying to learn how to stack blocks and push objects using visual inputs from a camera feed. In order to minimize cost and safety concerns, we want our robot to learn these skills with minimal interaction time, but efficient learning from complex sensory inputs such as images is difficult. This work introduces SOLAR, a new model-based reinforcement learning (RL) method that can learn skills – including manipulation tasks on a real Sawyer robot arm – directly from visual inputs with under an hour of interaction. To our knowledge, SOLAR is the most efficient RL method for solving real world image-based robotics tasks.  ... "

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