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Found 3 papers, 2 papers with code
The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation
We employ our method to learn challenging multi-object robot manipulation tasks from wrist camera observations and demonstrate superior utility for policy learning compared to other representation learning techniques.
Self-Supervised Learning of Multi-Object Keypoints for Robotic Manipulation
In recent years, policy learning methods using either reinforcement or imitation have made significant progress.
MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning
We define a parameterised collection of fast-to-run toy environments in OpenAI Gym by varying these dimensions and propose to use these to understand agents better.
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