[论文] Large language model and reinforcement learning based autonomous const...

论文概要

研究领域: ML
作者: Yifei Xiao, Huasheng Lin, T.Y. Yang
发布时间: 2026-10-22
arXiv: 2610.26899

中文摘要

由于全球人口快速增长，传统建筑方法正逐渐无法满足当前的住房需求。机器学习算法的进步促使研究者探索其在建筑行业的应用，以实现更智能、更高效的建造过程。特别是近年来大语言模型的兴起，为从传统建筑向智能建造的转型提供了更多可能。本研究提出了一种基于大语言模型和强化学习的自主建造方法。我们开发了一种改进的软演员-评论家（soft actor-critic）强化学习算法，根据建造任务为移动式起重机规划动作。利用机器人运动学和控制算法确保强化学习算法生成的动作可以被起重机执行。此外，我们还开发了定制的嵌入模型，根据用户兴趣从施工环境中提取信息。然后使用大语言模型ChatGPT 5来更新施工进度、向控制系统提供安全信息并生成施工进度报告。通过多个全尺寸挡土墙建造实验验证了所提方法的可行性。

原文摘要

Due to the rapid growth of the global population, traditional construction methods are gradually unable to meet the current housing demand. The advancement of machine learning algorithms has encouraged researchers to explore their applications in the construction industry, leading to more intelligent and efficient building processes. In particular, the rise of large language models in recent years has provided more possibilities for the transformation from traditional construction to smart construction. In this study, a large language model and reinforcement learning based autonomous construction method is proposed. An enhanced soft actor-critic reinforcement learning algorithm is developed to plan actions for a mobile crane according to construction tasks. Robot kinematics and control alg...

自动采集于 2026-10-22

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