Kalin Norman

Papers

Total Citations

156

H-Index

About

Norman Kalin is a robotics researcher specializing in underwater autonomy, state estimation, and marine robotic perception. His work addresses some of the most persistent challenges in subsea robotics, where GPS is unavailable, visibility is limited, and field testing is costly and logistically demanding. Kalin's most influential contribution, "Invariant Extended Kalman Filtering for Underwater Navigation" (2021, 91 citations), demonstrates how Lie Group theory can dramatically improve the accuracy of localization and uncertainty estimation for underwater robots — a foundational advance for reliable autonomous navigation in unstructured ocean environments. Complementing this, he has been a principal force behind HoloOcean, an open-source, high-fidelity underwater simulator built on Unreal Engine 4. His papers introducing HoloOcean's sonar simulation capabilities (2022, 33 citations) and its full-featured marine robotics platform (2024, 25 citations) have provided the research community with an accessible testbed that reduces reliance on expensive field trials. His work on AcTag (2023, 7 citations) further extends underwater perception by introducing novel opti-acoustic fiducial markers that enable accurate localization and object tracking using imaging sonar and cameras. Across his body of work, Kalin has meaningfully lowered the barriers to developing and validating underwater robotic systems.