This page features a video demonstrating the process of training a Unitree G1 humanoid robot to walk using reinforcement learning techniques. The training employs mjlab and the Proximal Policy Optimization (PPO) algorithm to enable the robot to walk both indoors and outdoors. Additional resources related to neural networks and community engagement, such as memberships and social media links, are also mentioned.
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