MarineLLM-PDDL: Generation of Planning Domains for Marine Vessels Using Past Incident Response Plans
- Mahya Mohammadi Kashani,
- ,
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Research
Peer-reviewOpen access
Abstract
Testing the hardware and software of marine vessels in field trials is a necessity to avoid technical and environmental catastrophes. Conducting tests with large vessels is costly. Multiple realistic domain descriptions based on past missions could increase the value of simulation tests, reducing the need for expensive field tests. In this paper, we generate scenarios from unstructured Incident Response Plan (IRP) documents using Large Language Models (LLMs), converting them to standard structured planning programs. The two synthesized marine test-domain datasets contain approximately 90% parsable, 75% solvable, and 57% correct planning programs.
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Research
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 307-313 (7 pages)Publication milestones
- Accepted/In press - 24/02/2025
- Published - 2025
Publication status
Published - 2025
Place of publication
Springer ChamVolume
36Publisher
Springer, United States, GermanyBook series
- Book series name: European Robotics Forum
ISBN (Print)
978-3-031-89470-1ISBN (Electronic)
978-3-031-89471-8Publication IDs
- Scopus: 105006477259
Host publication title
Springer Proceedings in Advanced Robotics Publication metrics
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Access to documents
Related Event
Title
Conference on European Robotics Forum
Event type
ConferenceDegree of recognition
International eventDate
25/03/2025 - 27/03/2025Location
Kultur- & Kongresszentrum LiederhalleStuttgartGermany
