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IEEE Spectrum · October 12, 2026 · On the brief until October 26, 2026

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

RoboticsMechanical EngineeringBiomedical Engineering
THE AI ANGLE
Learning and adapting athletic movement styles from recorded video data

A framework decouples motion planning from tracking to help humanoid robots learn tennis movements from video and motion-capture data. The system trains tracking policies on randomized speeds to reduce errors during transfer from simulation to physical hardware. This gives engineers a tested method to deploy athletic motions on full-size humanoids without external motion-capture setups.

Summary written by AI Business Lens with an AI model from the article at content.knowledgehub.wiley.com. It is not the article, and the publisher has not reviewed it. For publishers.

THE TEACHING ANGLE
The balance between copying human movement style and maintaining reliable physical task execution presents a clear trade-off in humanoid control.

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