# From Capability Models to Automated Planning: An AAS-Native Approach for Automatic PDDL Generation

arXiv: https://arxiv.org/abs/2606.02167 · HTML: https://mlsanity.com/paper/2606.02167/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 40 references that are in the map.
- First posted on arXiv 1 Jun 2026.

## Builds on (most cited first, 10 of 10)

- [LLMs as Planning Formalizers: A Survey for Leveraging Large Language Models to Construct Automated Planning Models](https://mlsanity.com/paper/2503.18971/) (2025)
- [A Reference Model for Common Understanding of Capabilities and Skills in Manufacturing](https://mlsanity.com/paper/2209.09632/) (2022)
- [A Research Agenda for AI Planning in the Field of Flexible Production Systems](https://mlsanity.com/paper/2112.15484/) (2021)
- [Flexible Production Systems: Automated Generation of Operations Plans Based on ISA-95 and PDDL](https://mlsanity.com/paper/1911.05481/) (2019)
- [On the Use of Large Language Models to Generate Capability Ontologies](https://mlsanity.com/paper/2404.17524/) (2024)
- [Model-based Workflow for the Automated Generation of PDDL Descriptions](https://mlsanity.com/paper/2408.08145/) (2024)
- [Toward a Mapping of Capability and Skill Models using Asset Administration Shells and Ontologies](https://mlsanity.com/paper/2307.00827/) (2023)
- [Integrating AI Planning Semantics into SysML System Models for Automated PDDL File Generation](https://mlsanity.com/paper/2506.06714/) (2025)
- [A Mapping Approach to Convert MTPs into a Capability and Skill Ontology](https://mlsanity.com/paper/2205.01382/) (2022)
- [Bridging Engineering and AI Planning through Model-Based Knowledge Transformation for the Validation of Automated Production System Variants](https://mlsanity.com/paper/2509.12091/) (2025)

## Abstract (arXiv)

Engineers designing production systems need to verify that a given layout supports all required production sequences. Automated planning techniques can answer such questions, but formulating the required planning problems in the Planning Domain Definition Language (PDDL) demands specialized expertise that production engineers typically lack. Asset Administration Shells (AAS) have emerged as the standardized Digital Twin for industrial assets in Industry 4.0. We show that AAS capability models, structured using four established Industry 4.0 standards (VDI 3682 for process descriptions, IEC 61360-1 for semantic property qualification, IDTA 02011 for type hierarchies, and IDTA 02016 for instance descriptions), contain sufficient information to generate complete PDDL problems automatically. Unlike prior work that introduced PDDL-specific submodels, our approach derives all planning elements from domain-level descriptions of resource functions, so-called capabilities, allowing engineers to model capabilities without any exposure to PDDL syntax or planning concepts. Our extraction algorithm transforms distributed Multi-AAS architectures into complete PDDL planning problems. We validate the approach on AAS models of a laboratory production system, comparing four layout variants using optimal planning to demonstrate how engineers can systematically explore design trade-offs by modifying the AAS model and regenerating the planning domain