Integrating AI Planning Semantics into SysML System Models for Automated PDDL File Generation

2025-06-07

AI Summary

This paper addresses the semantic gap between SysML system models and AI planning formalisms. We propose a model-driven integration method grounded in PDDL 3.1, enabling native embedding of PDDL semantics—namely types, predicates, functions, and actions—into SysML via reusable stereotypes and an extended profile, with OCL-based formal constraints ensuring syntactic consistency. The approach supports fully automated generation of syntactically and semantically compliant PDDL domain and problem files directly from SysML models. Our key contribution is the first systematic design of SysML stereotypes rigorously aligned with the PDDL 3.1 BNF grammar, establishing a standardized, verifiable semantic mapping bridge. Evaluated in an aerospace manufacturing robotics case study, the method successfully generated valid PDDL inputs that were processed by a state-of-the-art planner to yield optimized execution sequences, thereby demonstrating end-to-end automated transformation capability.

Technology Category

• Planning, Routing, and Scheduling: Model-Based Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Multiagent Systems: Multiagent Planning

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

This paper presents a SysML profile that enables the direct integration of planning semantics based on the Planning Domain Definition Language (PDDL) into system models. Reusable stereotypes are defined for key PDDL concepts such as types, predicates, functions and actions, while formal OCL constraints ensure syntactic consistency. The profile was derived from the Backus-Naur Form (BNF) definition of PDDL 3.1 to align with SysML modeling practices. A case study from aircraft manufacturing demonstrates the application of the profile: a robotic system with interchangeable end effectors is modeled and enriched to generate both domain and problem descriptions in PDDL format. These are used as input to a PDDL solver to derive optimized execution plans. The approach supports automated and model-based generation of planning descriptions and provides a reusable bridge between system modeling and AI planning in engineering design.

Problem

• Integrating AI planning semantics into SysML models
• Automating PDDL file generation for system models
• Bridging system modeling and AI planning in engineering

Innovation

• SysML profile integrates PDDL planning semantics
• Reusable stereotypes ensure syntactic consistency
• Automated PDDL generation bridges system modeling