Papyrus Models Repository

This repository shares a Papyrus/UML model created for research connecting MBSE, ConOps, and AI planning in autonomous robotic exploration.

The main value of the repository is the ontology embodied in the model: a structured way to represent operational capabilities, functional behavior, physical architecture, and resource-related quantities in one traceable model. The AI-planning connection is an important application of that ontology, but the ontology itself is the reusable core.

If you are new to the repository, start with the Ontology Guide. It explains the vocabulary and traceability logic that make the model reusable for similar MBSE and ConOps problems.

What problem this model solves

Operational studies for autonomous missions are often fragmented across:

• mission goals and ConOps descriptions,
• functional analyses,
• physical architecture models,
• resource calculations,
• planning or decision-making models.

This repository shows one way to keep those views connected in a single Papyrus model so that a user can trace:

• mission goals to functional behavior,
• functional behavior to use cases,
• use cases to actors and components,
• components to resource expressions,
• and those model elements to planner-oriented reasoning.

Who this repository is for

This repository is intended for:

• MBSE practitioners building early mission or system models for autonomous exploration systems,
• researchers linking Papyrus/UML models to AI-planning representations such as HDDL,
• engineers looking for an ontology-first starting point for rover, lander, hopper, or other planetary exploration studies,
• readers of the related thesis and papers who want a concrete model snapshot to inspect and reuse.

What is in this repository

• the Papyrus model that captures the ontology and traceability structure,
• documentation that explains how to read and reuse the ontology,
• companion diagrams for understanding the model without opening Papyrus first.

Main files:

• Parametric System Model/Parametric System Model_toshare.uml
  • the semantic model content: packages, activities, use cases, components, relationships, and expressions.
• Parametric System Model/Parametric System Model_toshare.notation
  • the diagram layout information used by Papyrus.
• Parametric System Model/Parametric System Model_toshare.di
  • Papyrus diagram/model metadata.
• Parametric System Model/Parametric System Model_toshare_en_US.properties
  • Papyrus language properties file.
• docs/ontology-guide.md
  • the main ontology note for understanding the model.
• docs/ai-planning-mapping.md
  • how the ontology can be mapped to AI-planning concepts.
• docs/worked-example.md
  • a concrete example showing a full trace from mission goal to planner-relevant behavior.
• docs/assets/
  • portable companion diagrams summarizing the model as PNG, SVG, and PDF.

This repository does not contain the Papyrus-to-HDDL translation tool. That workflow is maintained separately in the public repository:

• MBSE-to-HDDL-HIST-for-Robotic-Operations
  • https://github.com/JasmineRimani/MBSE-to-HDDL-HIST-for-Robotic-Operations

How to open the model in Papyrus

To inspect the model, use Eclipse Papyrus:

1. Install Papyrus from the Eclipse Papyrus project: https://www.eclipse.org/papyrus/
2. Keep the four model files together in the same folder:
   • .uml
   • .notation
   • .di
   • .properties
3. Open the file Parametric System Model/Parametric System Model_toshare.di in Papyrus.
4. If Papyrus asks to migrate the model to a newer version, work on a copy first.

If your Papyrus setup expects a workspace project, create a new project, copy the four files into it, and then open the .di file.

Where to start in the model

For a first read, use this order:

1. GeneralModelStructure
   • high-level package view of the ontology.
2. OperationalCapabilities
   • the operational/use-case vocabulary.
3. Functional Flow
   • the mission behavior and decision logic.
4. UseCaseLinkedComponents-MobilityExample
   • a concrete trace from function to component and numerical assumptions.

In the Model Explorer, inspect these packages first:

1. GenericExplorationSystem / Functional Architecture
2. GenericExplorationSystem / Physical Architecture
3. GenericExplorationSystem / Physical Architecture / NumericalSpecification
4. GenericExplorationSystem / Planning Module Software
5. Data Classes

Documentation map

• Ontology Guide
• AI-Planning Mapping
• Worked Example

Portable companion diagrams:

• General Model Structure Summary
• Operational Capabilities Summary
• Functional Flow Summary
• Mobility Trace Example Summary

Recommended reading order:

1. Ontology Guide
2. Worked Example
3. AI-Planning Mapping
4. The Papyrus model itself

Related repositories

This repository focuses on the ontology, the Papyrus model, and the traceability across mission, functional, physical, and resource views.

The separate public repository below focuses on the downstream translation workflow from Papyrus MBSE models to HDDL:

• MBSE-to-HDDL-HIST-for-Robotic-Operations
  • public repository: https://github.com/JasmineRimani/MBSE-to-HDDL-HIST-for-Robotic-Operations

Together, the two repositories can be read as:

• this repository for the ontology, model structure, and traceability logic,
• the translation repository for the downstream planner-oriented transformation workflow.

Scope and limitations

This repository is a research snapshot, not a packaged software toolchain.

• The ontology is represented through Papyrus/UML model structure, names, relationships, and parametric expressions.
• This repository does not include a Papyrus plugin, a custom Papyrus profile, or the Papyrus-to-HDDL translation implementation itself.
• The numerical values in the model are illustrative starting assumptions and should be adapted for any new mission.
• The planning-oriented interpretation is documented here so users can reuse the ontology even if they adopt a different planner or decision architecture.

Related publications and citation trail

The following references provide the research context for this repository and the related translation workflow.

• Rimani, J. (2023). Application of AI planning and MBSE to the Study and Optimization of ConOps for Autonomous Robotic Space Exploration Systems. PhD thesis, Politecnico di Torino. Handle: https://hdl.handle.net/20.500.14242/69712
• Rimani, J., Viola, N., and Lizy-Destrez, S. (2023). "Simulating Operational Concepts for Autonomous Robotic Space Exploration Systems: A Framework for Early Design Validation." Aerospace, 10(5), 408. https://doi.org/10.3390/aerospace10050408
• Rimani, J., Viola, N., and Lizy-Destrez, S. (2021). "Application of a hierarchical task planner to a lunar lava tube analogue robotic mission." In Proceedings of the International Astronautical Congress (IAC 2021), Dubai. Handle: https://hdl.handle.net/11583/2935111
• Rimani, J., Lesire, C., Lizy-Destrez, S., and Viola, N. (2021). "Application of MBSE to model Hierarchical AI Planning problems in HDDL." In ICAPS 2021 Workshop on Knowledge Engineering for Planning and Scheduling (KEPS 2021). Handle: https://hdl.handle.net/11583/2918312

If you cite this repository in a paper or report, it is usually helpful to cite both:

• this Papyrus model repository for the ontology and traceability structure,
• the most relevant publication above for the scientific context.