Author

Junli Ren

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Preprint Aug 2026

Towards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Tracking

This work proposes AdaPT, an Adaptive Motion Planning and Tracking framework that learns professional tennis serving and rally styles directly from broadcast videos, and improves tracking robustness by learning to track randomized execution speeds, while conditioning the planner on a learned motion-speed adapter to mitigate compounding errors.

Tao Huang, Ruofei Liu, Xuchen Tang et al. · 0 citations

Preprint Jul 2026

CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning

CLIFT: Closed-Loop Iterative Fine-Tuning is introduced, which turns deployment-time reward feedback into API-compatible supervised data and enables closed-loop policy improvement without accessing weights, gradients, likelihoods, or losses-pushing GROD to near-perfect success after two flywheel cycles, all without opening the model box.

Yuxin Chen, H. Srikanth, N. Jew et al. · 0 citations