Patrick Suwinski
Papers
2
Total Citations
6
H-Index
2
About
Patrick Suwinski is pioneering the use of artificial intelligence for autonomous navigation in the most challenging environments imaginable—the irregular, unstructured surfaces of asteroids and comets. His research focuses squarely on developing AI-driven systems for future robotic space missions, where traditional navigation fails. Suwinski’s major contributions include the creation of novel vision-based landing site detection methods. In his most-cited work (2024, 4 citations), he demonstrated how Vision Transformers and nested Convolutional Neural Networks (CNNs) can identify safe landing zones on planetary bodies in real-time. To overcome the scarcity of training data from these remote environments, he also developed a comprehensive AI-Development-Framework (AIDF) that generates both 2D and 3D synthetic data, establishing a complete workflow for training and validating neural networks for unstructured terrain (2024, 2 citations). Though early in his career, Suwinski’s work is foundational for the next generation of hovering exploration robots, promising to unlock autonomous exploration of our solar system’s most mysterious and rugged worlds.
Research Focus
Key Achievements
Top Papers
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- 2