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About

Matthew Deans is a robotics and space exploration researcher whose work spans autonomous navigation, simultaneous localization and mapping (SLAM), and planetary rover systems. He has made foundational contributions to bearing-only SLAM, developing invariant filtering approaches and experimental benchmarks that established core techniques for robots navigating unknown environments using minimal sensor information — work that has collectively earned over 190 citations. His research evolved naturally toward planetary exploration, where he has applied these navigation principles to lunar and Mars mission contexts. His LunarNav crater-based localization system directly supports NASA's Artemis program, enabling autonomous rover navigation across tens of kilometers of lunar terrain. Deans has also been deeply involved in analog mission research, including the Pavilion Lake Research Project, which used underwater environments to prepare humans and robots for the operational demands of future deep-space exploration. His field testing of utility robots for lunar surface operations and robotic reconnaissance assessments reflect a practical, mission-driven approach to research. More recently, he has explored reinforcement learning techniques for sparse-reward robotic tasks. Across his career, Deans has consistently bridged theoretical robotics and real-world space exploration applications, making him a significant contributor to humanity's preparations for returning to the Moon and beyond.