基于大型语言模型的可重新配置的生产线切换任务规划框架
Jinliang Hou1, Li Yan2, Hua Qiang3
1Xi'an Technological University, Xi'an, China. houjinliang@st.xatu.edu.cn.
Scientific reports
|December 17, 2025
概括
本研究介绍了使用大型语言模型 (LLM) 对可重新配置的生产线的自动切换任务规划框架. 基于LLM的系统提高了效率,并减少了生产线更换中的错误.
科学领域:
- 机器人和自动化 机器人和自动化
- 人工智能的人工智能
- 制造系统工程 制造系统工程
背景情况:
- 在可重新配置的生产线中,手动更换会导致低效率和高错误率.
- 自动化这些操作对于提高制造业的灵活性和生产率至关重要.
研究的目的:
- 为可重新配置的生产线提出一个自动切换任务规划框架.
- 利用大型语言模型 (LLM) 来解释用户指令和控制机器人.
主要方法:
- 一个整合知识图,高级任务计划器和低级任务计划器的框架.
- 基于LLM的解释语义指令来分解任务并生成技能序列.
- 基于技能的模块化编程,具有四层控制架构.
主要成果:
- 通过单机器人和实际生产线实验来证明框架的正确性.
- 成功控制了一个制造的交换机器人来执行自动交换任务.
- 验证了框架解释用户指令和执行自动更换的能力.
结论:
- 拟议的基于LLM的框架有效地解决了手动切换操作中的挑战.
- 在可重新配置的生产线中实现自动切换任务,提高效率和准确性.
- 为更智能和自主制造系统铺平了道路.
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