Learning to Play Like a Pro: Adaptive Motion Planning and Tracking for Humanoid Robots

<img src="https://spectrum.ieee.org/media-library/noitom-robotics-logo-with-stylized-nr-on-transparent-background.png?id=68382463&width=980"/><br/><br/><p>This White Paper provides roboticists and control engineers with a comprehensive overview of how motion planning and motion tracking can be decoupled to preserve professional athletic style in humanoid robots, and why adaptive, speed-aware control is essential for closing the gap between simulation and real-world deployment.</p><p><strong>What you will learn about: </strong></p><ul><li>Why combining a professional athlete’s motion style with reliable task performance remains an open challenge in humanoid ball-sports robotics, and how separating a high-level planner from a low-level tracker addresses this trade-off.</li><li>How motion data extracted from broadcast video and motion-capture recordings can be reconstructed, retargeted, and physically corrected into reference motions a humanoid robot can safely track.</li><li>Why the sim-to-real transition introduces compounding tracking errors, and how training a tracker on randomized execution speeds, paired with a learned motion-speed adapter in the planner, improves robustness on physical hardware.</li><li>How this adaptive framework was validated across two humanoid platforms, including full-size, in-the-wild serving performed without any motion-capture system.</li></ul><div><span><a href="https://content.knowledgehub.wiley.com/learning-to-play-like-a-pro-adaptive-motion-planning-and-tracking-for-humanoid-robots/" target="_blank">Download this free whitepaper now!</a></span></div>