NealAI: A RAG-based Chat Assistant Supporting Command of a Robotic Team from the ISS

We introduce NealAI, the first AI chat assistant to support astronauts with question answering during a space telerobotics experiment. In the Surface Avatar mission, an ISS crew member controlled a heterogeneous team of four robots in a simulated Martian environment. NealAI uses a Retrieval-Augmented Generation (RAG) approach, enabling a Large Language Model (LLM) to dynamically retrieve relevant context about the experiment and its robots, and deliver accurate, context-aware responses. To adhere to privacy requirements and computational costs, NealAI is based on a single small-scale LLM running locally. We assessed NealAI’s performance in different evaluations, including a preliminary experiment with an ISS crew member teleoperating the robots, as well as a set of offline tests to evaluate the LLM context selection, the response correctness, and when (and why) hallucinations occur. Results demonstrate the feasibility and limitations of using a small-scale LLM on a RAG-based chat assistant during a space telerobotic experiment. Finally, we report some conclusions and lessons learned.

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Published
2025-12-01
DOI
https://doi.org/10.1109/isparo66239.2025.11436289
Primary Topic
Space Exploration and Technology
Type
article
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article

NealAI: A RAG-based Chat Assistant Supporting Command of a Robotic Team from the ISS

Florian Schmidt, Neal Y. Lii, Werner Friedl, Freek Stulp et al.
Space Exploration and Technology
article

NealAI: A RAG-based Chat Assistant Supporting Command of a Robotic Team from the ISS

Florian Schmidt, Neal Y. Lii, Werner Friedl, Freek Stulp, Bernhard Weber, Peter Schmaus, Tai Mai, Timo Bachmann, Annika Schmidt, Rute Luz, Thomas Krüger, J. Butterfaß, Daniel Seidel, Xiaozhou Luo, Thomas Gumpert, Emiel den Exter, Adrian S. Bauer, Florian Lay, Daniel Leidner, Nesrine Batti, Lioba Schürmann, Samuel Bustamante, Luisa Mayershofer, Tristan Ehlert, Alin Albu-Schäffer, Sant Brinkman, Nicole Wenzinger, Philipp Knestel, Antoin Raffin, Anne Köpken, Ajithkumar N. Manaparampil
article en

Abstract

We introduce NealAI, the first AI chat assistant to support astronauts with question answering during a space telerobotics experiment. In the Surface Avatar mission, an ISS crew member controlled a heterogeneous team of four robots in a simulated Martian environment. NealAI uses a Retrieval-Augmented Generation (RAG) approach, enabling a Large Language Model (LLM) to dynamically retrieve relevant context about the experiment and its robots, and deliver accurate, context-aware responses. To adhere to privacy requirements and computational costs, NealAI is based on a single small-scale LLM running locally. We assessed NealAI’s performance in different evaluations, including a preliminary experiment with an ISS crew member teleoperating the robots, as well as a set of offline tests to evaluate the LLM context selection, the response correctness, and when (and why) hallucinations occur. Results demonstrate the feasibility and limitations of using a small-scale LLM on a RAG-based chat assistant during a space telerobotic experiment. Finally, we report some conclusions and lessons learned.

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), European Space Research and Technology Centre (NL)
Openalex Percentile: Top 8%
Space Exploration and Technology
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