Data-Efficient Approach to Humanoid Control by Fine-Tuning a Pre-Trained GPT on Action Data

Recent advances in imitation learning have enabled robots to learn multiple tasks from large-scale datasets. However, developing a model for multi-tasking humanoid control faces significant challenges. Human kinematic data is available in open-source datasets for humanoid motion learning, but learni...

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Bibliographic Details
Main Authors: Siddharth Padmanabhan, Kazuki Miyazawa, Takato Horii, Takayuki Nagai
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/11000102/
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