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Reinforcement learning framework for humanoid robot locomotion and skill acquisition, providing a full pipeline from simulation training to real-time deployment on T1/K1 hardware.
stars
30
forks
5
While the project has a modest star count, it addresses the complex 'sim-to-real' gap for specific humanoid hardware (T1/K1 robots). The inclusion of multi-format export for edge deployment (TFLite, JIT) and pre-trained models for walking/kicking demonstrates deep domain expertise. Frontier labs are unlikely to focus on these specific low-cost/competition humanoid platforms, providing the project a safe, specialized niche.
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