ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Humanoid Robotics
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1581110
From Text to Motion: Grounding GPT-4 in a Humanoid Robot "Alter3"
Provisionally accepted
- 1The University of Tokyo, Bunkyo, Japan
- 2Alternative Machine Inc., Tokyo, Japan
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This paper introduces Alter3, a humanoid robot that demonstrates spontaneous motion generation through the integration of GPT-4, a cutting-edge Large Language Model (LLM). This integration overcomes the challenge of applying LLMs to direct robot control, which typically struggles with the hardware-specific nuances of robotic operation. By translating linguistic descriptions of human actions into robotic movements via programming, Alter3 can autonomously perform a diverse range of actions, such as adopting a "selfie" pose or simulating a "ghost." This approach not only shows Alter3's few-shot learning capabilities but also its adaptability to verbal feedback for pose adjustments without manual fine-tuning. This research advances the field of humanoid robotics by bridging linguistic concepts with physical embodiment and opens new avenues for exploring spontaneity in humanoid robots.
Keywords: humanoid robot, Large language models, Motion generation, embodiment, agency
Received: 21 Feb 2025; Accepted: 01 May 2025.
Copyright: © 2025 Yoshida, Masumori and Ikegami. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Takahide Yoshida, The University of Tokyo, Bunkyo, Japan
Atsushi Masumori, The University of Tokyo, Bunkyo, Japan
Takashi Ikegami, The University of Tokyo, Bunkyo, Japan
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