Papers

11

Total Citations

268

H-Index

9

About

Marc Hildebrandt is a pioneering researcher in underwater robotics and autonomous systems, whose work spans deep-sea exploration, AI-driven navigation, and robotic manipulation. Based at the German Research Center for Artificial Intelligence (DFKI), Hildebrandt has built a distinguished career tackling some of the most technically demanding environments on — and beyond — Earth. His most cited work, a 2022 review on AI for underwater robotics (63 citations), synthesizes cutting-edge advances in machine learning, perception, and control for subsea vehicles, reflecting his broad command of the field. Equally influential is his 2016 contribution on next-generation benthic deep-sea research (61 citations), which helped reframe how scientists approach untethered deep-ocean exploration. His early foundational work on computer-based and hydraulic manipulator control (2008–2009) established more precise, accessible alternatives to traditional master-slave systems, reducing the need for specialized on-site operators. Perhaps most strikingly, Hildebrandt has extended his expertise beyond Earth's oceans — his 2020 paper on exploring Enceladus' subsurface ocean (28 citations) and his 2013 under-ice system design demonstrate a remarkable vision connecting deep-sea technology to astrobiology and planetary exploration. With contributions to marine mining robotics and innovative docking systems, his cumulative impact marks him as a defining voice in autonomous ocean systems research.

Research Focus

Key Achievements

9
H-Index
11
Papers
268
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Recent Advances in AI for Navigation and Control of Underwater Robots
63 citations · 2022
📈 Most Prolific Year: 2009 (3 Papers)
🤝 Key Collaborators: 43
🏛 Institutions: German Research Centre for Artificial Intelligence, University of Bremen, Robotics Research (United States)

Top Papers

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    Design of an autonomous under-ice exploration system
    20 citations · 2013
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    Combining cameras, magnetometers and machine-learning into a close-range localization system for docking and homing
    10 citations · 2017
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago