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

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.

What you will learn about: 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.

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.

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. How this adaptive framework was validated across two humanoid platforms, including full-size, in-the-wild serving performed without any motion-capture system.