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About

Aaron Marburg is a leading researcher in autonomous underwater robotics, with a focus on subsea manipulation, sensor fusion, and perception for unstructured environments. His work bridges the gap between theoretical robotics and practical offshore applications, particularly through the development of resident subsea robotic systems—vehicles deployed autonomously from underwater infrastructure rather than manned ships. His most cited paper, "Resident Subsea Robotic Systems: A Review" (2020, 23 citations), provides a foundational overview of this emerging field. Marburg has made significant contributions to underwater manipulation, including the open-source WAVE (UnderWater Arm-Vehicle Emulator) framework (2024, 9 citations), which enables simulation and development of autonomous underwater vehicle manipulator systems (UVMS). He also developed an open-source tool for extrinsic calibration between optical cameras and imaging sonars (2021, 6 citations), a critical step for fusing visual and acoustic data in murky waters. More recently, his work on grasp selection under uncertainty—such as Clustered Grasp Volumes (2024) and PUGS (Perceptual Uncertainty for Grasp Selection, 2025)—addresses the challenge of reliable manipulation in adversarial, low-visibility conditions. Marburg’s research is essential for advancing fully autonomous subsea operations, from inspection to intervention.