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    Tag: Isaac Gym

    Sep 14
    17 min read
    Deep Reinforcement Learning for Locomotion: How Humanoids Learn to Walk on Uneven Terrain

    For decades, the standard approach to bipedal locomotion was anchored in classical analytical mechanics: Zero Moment Point (ZMP) stability, Linear Inverted Pendulum Models (LIPM), and dynamic Model Predictive Control (MPC). Pioneered by platforms like Honda ASIMO and Boston Dynamics Atlas, these analytical controllers solved systems of differential equations to guarantee that the robot’s ground reaction […]