从文本到动作:在仿人机器人Alter3中接地GPT-4。

IF 2.9 Q2 ROBOTICS
Frontiers in Robotics and AI Pub Date : 2025-05-27 eCollection Date: 2025-01-01 DOI:10.3389/frobt.2025.1581110
Takahide Yoshida, Atsushi Masumori, Takashi Ikegami
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引用次数: 0

摘要

本文介绍了一种名为Alter3的仿人机器人,该机器人通过集成尖端的大语言模型(LLM) GPT-4来演示自发运动生成。这种集成克服了将llm应用于直接机器人控制的挑战,后者通常与机器人操作中特定硬件的细微差别作斗争。通过编程将人类行为的语言描述转换为机器人动作,Alter3可以自主执行各种各样的动作,比如采取“自拍”姿势或模拟“鬼魂”。这种方法不仅显示了Alter3的少量镜头学习能力,而且还显示了它对口头反馈的适应性,无需手动微调即可进行姿势调整。该研究通过将语言概念与物理体现相结合,推动了仿人机器人领域的发展,为探索仿人机器人的自发性开辟了新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From text to motion: grounding GPT-4 in a humanoid robot "Alter3".

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.

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来源期刊
CiteScore
6.50
自引率
5.90%
发文量
355
审稿时长
14 weeks
期刊介绍: Frontiers in Robotics and AI publishes rigorously peer-reviewed research covering all theory and applications of robotics, technology, and artificial intelligence, from biomedical to space robotics.
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