发表机构
University of Tokyo（东京大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出“Socratic Models-ChatGLM”算法，基于离线开源大语言模型与PyBullet平台实现机械臂多模态交互控制，可降低成本并解决复杂多步骤机械操作任务。
AI 中文摘要
大语言模型（LLMs）已通过人类与AI智能体之间的大量高级交互彻底变革了现代社会，然而包括ChatGPT在内的多数大语言模型并非友好开源，用户必须持续为这类AI服务支付大量费用。因此，在本地服务器部署开源大语言模型可被视为一种高效方法，用于设计和实现具有更低成本、更稳定免费使用体验的具身AI算法。受此普遍动机启发，我们原创性提出并实现了“Socratic Models-ChatGLM”，这是一种基于离线大语言模型、通过简易PyBullet平台实现的、用于机械臂多模态交互控制的高性能算法，甚至展现出解决复杂文本-图像集成多步骤长 horizon 机械操作任务的非凡潜力。
英文摘要
Large Language Models (LLMs) have significantly revolutionized the modern society with numerous advanced interactions between humans and AI agents, whereas the usage of most large language models including ChatGPT are not friendly open-sourced and must require the users paying a lot for such AI services continuously. Therefore, deploying open-sourced large language models on local servers can be considered as an efficient approach to design and implement creative embodied AI algorithms with lower cost and more stable free usage. Inspired by this ordinary motivation, we originally propose and implement the "Socratic Models-ChatGLM", which is a well-performed algorithm for multi-modal interactive control of robotic arm based on offline large language models via the facile PyBullet platform, even presents extraordinary potential to address complicated text-image integrated multi-step long-horizon robotic manipulation tasks.
CommentsThis research work has been accepted for poster presentation at ICRA 2026 MEI (Multimodal Embodied Interaction in Robots) Workshop. (Here is the workshop-version short paper.)
Journal refhttps://ieeexplore.ieee.org/abstract/document/11371765; 2025
