arXiv:2509.12091cs.AI2025-09被引 1

将工程模型转化为可规划的智能系统,自动验证产线方案优劣

Bridging Engineering and AI Planning through Model-Based Knowledge Transformation for the Validation of Automated Production System Variants

  • 基于SysML模型自动生成PDDL规划文件,嵌入预条件与约束
  • 案例显示可快速评估飞机装配产线不同配置的可行性与效率
  • 适合智能制造领域需自动化验证系统方案的研究者使用

基于模型的系统工程(MBSE)中的工程模型包含系统结构与行为的详细信息,但通常缺乏与资源可用性、时间约束相关的符号化规划语义(如前提、效果、约束)。这限制了对特定系统变体能否完成任务及其执行效率的评估。为此,本文提出一种模型驱动方法,在基于SysML的工程模型中实现符号化规划构件的指定与自动生成。通过专用SysML资料档引入可复用的构造型(stereotypes),将核心规划元素集成到现有模型结构中,并由算法生成符合规划领域定义语言(PDDL)规范的域文件和问题文件。相比以往依赖人工转换或外部能力模型的方法,该方法支持原生集成并保持工程与规划工件的一致性。在飞机装配场景的案例研究中,展示了如何为现有工程模型注入规划语义,并通过该工作流生成一致的规划文件。生成的规划文件使系统变体可通过AI规划进行验证。

原文摘要 · Abstract (English)

Engineering models created in Model-Based Systems Engineering (MBSE) environments contain detailed information about system structure and behavior. However, they typically lack symbolic planning semantics such as preconditions, effects, and constraints related to resource availability and timing. This limits their ability to evaluate whether a given system variant can fulfill specific tasks and how efficiently it performs compared to alternatives. To address this gap, this paper presents a model-driven method that enables the specification and automated generation of symbolic planning artifacts within SysML-based engineering models. A dedicated SysML profile introduces reusable stereotypes for core planning constructs. These are integrated into existing model structures and processed by an algorithm that generates a valid domain file and a corresponding problem file in Planning Domain Definition Language (PDDL). In contrast to previous approaches that rely on manual transformations or external capability models, the method supports native integration and maintains consistency between engineering and planning artifacts. The applicability of the method is demonstrated through a case study from aircraft assembly. The example illustrates how existing engineering models are enriched with planning semantics and how the proposed workflow is applied to generate consistent planning artifacts from these models. The generated planning artifacts enable the validation of system variants through AI planning.

系统工程智能规划产线验证模型驱动

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