Sebastien Origer

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About

Sebastien Origer is an emerging researcher at the forefront of autonomous spacecraft guidance, navigation, and control, with a particular focus on the application of neural networks and machine learning to complex space mission scenarios. His most recognized work, "Optimality principles in spacecraft neural guidance and control" (2024), has already garnered 21 citations in a remarkably short time, underscoring the timeliness and significance of his contributions to the field. This review synthesizes cutting-edge advances in training end-to-end neural architectures capable of autonomously managing interplanetary transfers, planetary landings, and close-proximity operations — tasks traditionally requiring intensive ground-based computation. A central insight of Origer's research is that neural models can successfully internalize and replicate the mathematical principles of optimal control, effectively encoding mission-critical decision-making within compact, onboard systems. This paradigm shift has profound implications for deep-space exploration, where communication delays make real-time ground control impractical. Origer's work bridges classical astrodynamics and modern artificial intelligence, positioning him as a notable voice in next-generation spacecraft autonomy and inspiring a growing community of researchers working at this exciting interdisciplinary frontier.