Umesh Neettiyath
The University of Tokyo, Indian Institute of Technology Madras
Papers
5
Total Citations
45
H-Index
3
About
Umesh Neettiyath is a marine robotics researcher whose work sits at the intersection of autonomous underwater systems and deep-sea mineral resource assessment. He has made significant contributions to the development of robotic survey methodologies for mapping cobalt-rich manganese crust deposits — rare and economically valuable minerals found on seamounts at depths exceeding 800 meters. His most cited work (26 citations) established foundational methods for regional-scale estimation of manganese crust distribution using autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs), combining camera systems, multibeam sonar, and sub-bottom acoustic sensors to produce detailed seafloor maps. Building on this, Neettiyath has advanced multirobot, multimodal survey frameworks that dramatically expand coverage efficiency across large underwater areas. His more recent research explores machine learning-based seafloor classification from acoustic probe data, reducing reliance on labor-intensive visual confirmation methods. Earlier work on AUV formation control using state estimation reflects his broader expertise in underwater robot coordination. With a growing citation record across deep-sea sensing, data processing, and autonomous marine systems, Neettiyath's research is helping lay the technical groundwork for responsible deep-sea resource exploration.
Research Focus
Key Achievements
Top Papers
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