Year: 2025
Type: conference-paper
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.
Authors: Philipp G. Knestel, Luisa Mayershofer, Anne Köpken, Nesrine Batti, Florian S. Lay, Timo Bachmann, Sant Brinkman, Jörg Butterfaß, Emiel Den Exter, Tristan Ehlert, Werner Friedl, Thomas Gumpert, Xiaozhou Luo, Ajithkumar N. Manaparampil, Tai Mai, Antoin Raffin, Florian Schmidt, Annika Schmidt, Daniel Seidel, Lioba Schürmann, Nicole Wenzinger, Bernhard Weber, Alin Albu-Schäffer, Adrian S. Bauer, Daniel Leidner, Rute Luz, Peter Schmaus, Freek Stulp, Thomas Krüger, Samuel Bustamante, Neal Y. Lii
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7140076994