Affordance Learning from Play for Sample-Efficient Policy Learning-Reference-Cited by-同舟云学术

Affordance Learning from Play for Sample-Efficient Policy Learning

Published:2022-05-23 Issue: Volume: Page:
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Container-title:2022 International Conference on Robotics and Automation (ICRA)
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Author:

Borja-Diaz Jessica¹,Mees Oier¹,Kalweit Gabriel¹,Hermann Lukas¹,Boedecker Joschka¹,Burgard Wolfram¹

Affiliation:

1. University of Freiburg,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9811522/9811357/09811889.pdf?arnumber=9811889

Reference36 articles.

1. Unseen object in-stance segmentation for robotic environments;xie;IEEE Transactions on Robotics (T-RO),2021

2. Grounded Human-Object Interaction Hotspots From Video

3. Using Object Affordances to Improve Object Recognition

4. Dexterous robotic grasping with object-centric visual affordances;mandikal;ICRA,2021

5. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor;haarnoja;International Conference on Machine Learning,0

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