We are excited to present our proprietary reinforcement learning algorithm, refined through extensive simulations and vast training data, enabling our full-scale humanoid robot, Adam, to master human-like locomotion. Unlike model-based gait control, our RL-driven approach grants Adam exceptional adaptability. On challenging terrains like uneven surfaces, Adam seamlessly adjusts stride, pace, and balance in real time, ensuring stable, natural movement while boosting efficiency and safety.The algorithm also delivers fluid, graceful motion with smooth joint coordination, minimizing mechanical wear, extending operational life, and significantly reducing energy use for enhanced endurance. Subscribe for updates on Adam’s journey.
