RLinf v0.3, a large-scale reinforcement learning infrastructure project for embodied AI, has been released by Wuwenxiong (Wuwenxiong) in collaboration with Tsinghua University. This new version enhances the platform's capabilities across five dimensions: models, algorithms, real robots, simulation, and systems. It aims to lower development barriers, improve training efficiency, and increase deployment flexibility for embodied AI, enabling robots to learn and evolve continuously in real-world environments. The update includes support for six new embodied models, expanded algorithm coverage from imitation learning to real-world RL, and improved real-robot support with new data collection methods and hardware integrations. AI
IMPACT This release aims to accelerate embodied AI development by providing a more comprehensive and flexible platform for training and deploying robots in real-world scenarios.
RANK_REASON This is a release of a research infrastructure project for embodied AI, not a frontier model release. [lever_c_demoted from research: ic=1 ai=1.0]
- Baidu Smart Cloud
- Embodied AI
- NVIDIA
- PyTorch
- Reinforcement Learning
- RLinf
- Tsinghua University
- Wuwenxiong
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