AI Assistants for Spaceflight Procedures: Combining Generative Pre-Trained Transformer and Retrieval-Augmented Generation on Knowledge Graphs With Augmented Reality Cues

Fuente: arXiv
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Auteurs principaux: Bensch, Oliver, Bensch, Leonie, Nilsson, Tommy, Saling, Florian, Bewer, Bernd, Jentzsch, Sophie, Hecking, Tobias, Kutz, J. Nathan
Format: Preprint
Publié: 2024
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author Bensch, Oliver
Bensch, Leonie
Nilsson, Tommy
Saling, Florian
Bewer, Bernd
Jentzsch, Sophie
Hecking, Tobias
Kutz, J. Nathan
author_facet Bensch, Oliver
Bensch, Leonie
Nilsson, Tommy
Saling, Florian
Bewer, Bernd
Jentzsch, Sophie
Hecking, Tobias
Kutz, J. Nathan
contents This paper describes the capabilities and potential of the intelligent personal assistant (IPA) CORE (Checklist Organizer for Research and Exploration), designed to support astronauts during procedures onboard the International Space Station (ISS), the Lunar Gateway station, and beyond. We reflect on the importance of a reliable and flexible assistant capable of offline operation and highlight the usefulness of audiovisual interaction using augmented reality elements to intuitively display checklist information. We argue that current approaches to the design of IPAs in space operations fall short of meeting these criteria. Therefore, we propose CORE as an assistant that combines Knowledge Graphs (KGs), Retrieval-Augmented Generation (RAG) for a Generative Pre-Trained Transformer (GPT), and Augmented Reality (AR) elements to ensure an intuitive understanding of procedure steps, reliability, offline availability, and flexibility in terms of response style and procedure updates.
format Preprint
id arxiv_https___arxiv_org_abs_2409_14206
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AI Assistants for Spaceflight Procedures: Combining Generative Pre-Trained Transformer and Retrieval-Augmented Generation on Knowledge Graphs With Augmented Reality Cues
Bensch, Oliver
Bensch, Leonie
Nilsson, Tommy
Saling, Florian
Bewer, Bernd
Jentzsch, Sophie
Hecking, Tobias
Kutz, J. Nathan
Artificial Intelligence
Human-Computer Interaction
68T01, 68T20, 68T30, 68T50, 68T05,
I.2; H.5
This paper describes the capabilities and potential of the intelligent personal assistant (IPA) CORE (Checklist Organizer for Research and Exploration), designed to support astronauts during procedures onboard the International Space Station (ISS), the Lunar Gateway station, and beyond. We reflect on the importance of a reliable and flexible assistant capable of offline operation and highlight the usefulness of audiovisual interaction using augmented reality elements to intuitively display checklist information. We argue that current approaches to the design of IPAs in space operations fall short of meeting these criteria. Therefore, we propose CORE as an assistant that combines Knowledge Graphs (KGs), Retrieval-Augmented Generation (RAG) for a Generative Pre-Trained Transformer (GPT), and Augmented Reality (AR) elements to ensure an intuitive understanding of procedure steps, reliability, offline availability, and flexibility in terms of response style and procedure updates.
title AI Assistants for Spaceflight Procedures: Combining Generative Pre-Trained Transformer and Retrieval-Augmented Generation on Knowledge Graphs With Augmented Reality Cues
topic Artificial Intelligence
Human-Computer Interaction
68T01, 68T20, 68T30, 68T50, 68T05,
I.2; H.5
url https://arxiv.org/abs/2409.14206