AgiBot adopts CHINGMU optical motion capture systems to support humanoid robot training and performance optimization. With sub-millimeter spatial accuracy and precise pose measurement, the system captures full-body joint motion and end-effector trajectories, enabling fine-grained motion tuning and in-depth analysis of complex actions.

Through CHINGMU's system, AgiBot efficiently acquires high-quality training datasets. In controlled experimental environments, multiple task scenarios and dynamic interactions are simulated, with synchronized recording of multi-modal motion data. The structured datasets directly support algorithm training and model learning.

This approach enables precise eva1uation of gait, motion planning, and stability, while accelerating continuous learning and performance evolution of humanoid robots.