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Robot Learning

Awesome MIT License LICENSE

Papers, datasets, applications, tutorials.

Widely used by top conferences and journals:


Better Publications on Top Journals:


Better Results of Great Research Institute:


The research result of Embodied AI and Foundation Models can be found in fm.

0. Survey

[2020] Automatic Curriculum Learning For Deep RL: A Short Survey

[2020] A Survey on Learning-Based Robotic Grasping

[2021] Robot Learning from Randomized Simulations: A Review

[2022] Guided reinforcement learning: A review and evaluation for efficient and effective real-world robotics

[2022] Automated Reinforcement Learning (AutoRL): A Survey and Open Problems

[2023] Transfer Learning in Robotics: An Upcoming Breakthrough? A Review of Promises and Challenges

[2024] Survey of Learning Approaches for Robotic In-Hand Manipulation

[2024] A Survey of Robotic Language Grounding: Tradeoffs Between Symbols and Embeddings

[2024] AI Robots and Humanoid AI: Review, Perspectives and Directions

[2024] Benchmarking Neural Radiance Fields for Autonomous Robots: An Overview

[2024] Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes

[2024] Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations

[2024] Neural Fields in Robotics: A Survey

🔈 If you would like some specific areas' survey, such as reinforcement learning,imitation learning, and etc, please click related links in part one.

1. Research Areas and Papers

🔈 There are just some pretty papers for beginners and interested figures.





2. Datasets, Benchmarks, and Simulators

Please see HERE for the popular robot learning datasets, benchmarks and simulator results.

3. Relevant Resources

Please see HERE for some awesome relevant resources, such as

  • Tutorials
  • Awesome URDF and MJCF
  • Awesome Toolkit
  • Awesome Papers' Repository of Robot Learning Relevant Areas

Absolutely, you could also acquire:

4. Contributing

If you are interested in contributing, please refer to HERE for instructions in contribution.


Copyright notice

[Notes]This Github repo can be used by following the corresponding licenses. I want to emphasis that it may contain some PDFs or thesis, which were downloaded by me and can only be used for academic purposes. The copyrights of these materials are owned by corresponding publishers or organizations. All this are for better adademic research. If any of the authors or publishers have concerns, please contact me to delete or replace them.

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