Generative AI for automated task modelling and task allocation in human robot collaborative applications

IF 3.2 3区 工程技术 Q2 ENGINEERING, INDUSTRIAL
Nikos Dimitropoulos, Michalis Kaipis, Stavros Giartzas, George Michalos (2)
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引用次数: 0

Abstract

Task modelling and assignments generation is a complex and time-consuming activity despite the availability of modern CAx and planning tools. This paper proposes an AI based framework using Large Multi-Modal Models and a Digital Twin to automatically create task models, sequences and assignment plans through the processing of video streams involving visual and audio cues on the recorded resources, tools, and tasks. The same LMMs perform the task-to-resource allocation considering metrics such as human factors and resource workload. A case study on the assembly of white goods showcases reduction in manual planning, enhanced resources utilization and improved human-robot collaborative applications.
人-机器人协作应用中自动任务建模和任务分配的生成式人工智能
尽管有现代CAx和规划工具,任务建模和任务生成仍然是一项复杂且耗时的活动。本文提出了一个基于人工智能的框架,使用大型多模态模型和数字孪生,通过处理涉及录制资源、工具和任务的视觉和音频线索的视频流,自动创建任务模型、序列和分配计划。相同的lmm执行任务到资源的分配,考虑诸如人为因素和资源工作负载之类的指标。一个关于白色家电组装的案例研究展示了人工规划的减少、资源利用率的提高和人机协作应用的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cirp Annals-Manufacturing Technology
Cirp Annals-Manufacturing Technology 工程技术-工程:工业
CiteScore
7.50
自引率
9.80%
发文量
137
审稿时长
13.5 months
期刊介绍: CIRP, The International Academy for Production Engineering, was founded in 1951 to promote, by scientific research, the development of all aspects of manufacturing technology covering the optimization, control and management of processes, machines and systems. This biannual ISI cited journal contains approximately 140 refereed technical and keynote papers. Subject areas covered include: Assembly, Cutting, Design, Electro-Physical and Chemical Processes, Forming, Abrasive processes, Surfaces, Machines, Production Systems and Organizations, Precision Engineering and Metrology, Life-Cycle Engineering, Microsystems Technology (MST), Nanotechnology.
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