Towards a Reliable Offline Personal AI Assistant for Long Duration Spaceflight
Oliver Bensch, Leonie Bensch, Tommy Nilsson, Florian Saling, Wafa M., Sadri, Carsten Hartmann, Tobias Hecking, J. Nathan Kutz

TL;DR
This paper proposes an integrated AI system combining GPT, RAG, Knowledge Graphs, and AR to enhance autonomous, safe, and efficient data access and decision-making for astronauts during long-duration space missions.
Contribution
It introduces a novel AI framework that combines multiple advanced technologies to improve astronaut autonomy and safety in space exploration.
Findings
Enhanced data accessibility through Knowledge Graphs
Improved safety with integrated AI and AR interfaces
Potential for increased autonomy in space missions
Abstract
As humanity prepares for new missions to the Moon and Mars, astronauts will need to operate with greater autonomy, given the communication delays that make real-time support from Earth difficult. For instance, messages between Mars and Earth can take up to 24 minutes, making quick responses impossible. This limitation poses a challenge for astronauts who must rely on in-situ tools to access the large volume of data from spacecraft sensors, rovers, and satellites, data that is often fragmented and difficult to use. To bridge this gap, systems like the Mars Exploration Telemetry-Driven Information System (METIS) are being developed. METIS is an AI assistant designed to handle routine tasks, monitor spacecraft systems, and detect anomalies, all while reducing the reliance on mission control. Current Generative Pretrained Transformer (GPT) Models, while powerful, struggle in safety-critical…
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Taxonomy
TopicsSpace Exploration and Technology · Space Satellite Systems and Control · Inertial Sensor and Navigation
MethodsAttention Is All You Need · Linear Layer · Layer Normalization · Residual Connection · Position-Wise Feed-Forward Layer · Dense Connections · Softmax · Multi-Head Attention · Adam · Dropout
