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Professor  Blair Thornton PhD

Professor of Marine Autonomy

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Ocean Perception

Blair Thornton is a Professor of Marine Autonomy within Engineering and Physical Sciences at the University of Southampton

Research Keywords: Marine Robotics, Computer Vision, Machine Learning, SLAM, Laser spectroscopy

Blair Thornton is a Professor of Marine Autonomy within Engineering and Physical Sciences at the University of Southampton. He currently holds an EPSRC innovation fellowship for Robotics and Artificial Intelligence systems for ocean research, and is a Co-Director of the FEPS In situ and Remote Intelligent Sensing Centre of Excellence (IRIS).

His research develops scalable methods for robotic seafloor survey through improved sensing and autonomy. He is dedicated to fielding systems in real environments and overcoming bottlenecks in the flow of information from data collection through to human insight.

After graduating from ship-science in 2002, Blair went on to complete his PhD in underwater robotics at Southampton in 2006. During his PhD, he spent 2 years at the URA laboratory, Institute of Industrial Science (IIS) at the University of Tokyo, Japan, and continued his research as a government funded postdoctoral fellow. In 2008, he was appointed Assistant Professor and was promoted to Associate Professor in 2012. He rejoined the University of Southampton in 2016. During this time, he has participated in more than 55 ocean research expeditions (30 of which as principal investigator) and spent over 500 days at sea.

He is an associate editor for the IEEE/Journal of Oceanic Engineering, IEEE/Robotics and Automation Letters, and a Guest Editor on the Field Robotics Journal Marine Robotics Special Issue. He was awarded the Okamura Kenji prize for outstanding contribution to marine technology in 2014 for his contribution to seafloor debris and radiation monitoring following the 2011 earthquake, tsunami and Fukushima nuclear disaster in the Tohoku region of Japan.

In 2019, he was awarded 2nd place in the Shell Ocean Discovery Xprize as a founding member of Team KUROSHIO.

Research interests

Autonomous robotic platforms allow detailed observations to be made over large areas in the ocean. For these systems to be useful, it is necessary to develop advanced sensing capabilities and methods to allow the robots to safely navigate and accurately localize themselves in complex, GPS denied environments. Once observations have been made, it’s necessary to interpret the large volumes of data that are gathered in an efficient and scalable way


Fig 1

Seafloor 3D visual reconstruction: Development of deep-sea imaging hardware and processing pipelines for calibration, localisation and 3D mapping of the seafloor with full-field uncertainty characterisation.

  • BioCam (NERC NE/P020887/1): Development of a deep-sea, high-altitude seafloor imaging system for monitoring seafloor ecological variables as part of the Oceanids Marine Sensor Capital program. This project is a collaboration with Sonardyne International Ltd, the National Oceanography Centre and the ACFR University of Sydney
  • AT-SEA (NERC NE/T010592/1): 3D visual survey of decommissioned seafloor infrastructure using a shore launched Autonomous Underwater Vehicle (Boaty McBoaface) as part of the INSITE program. This project is a collaboration with the National Oceanography Centre.
Fig 2

Automated interpretation of data: Development of AI methods for rapid scalable interpretation of seafloor imagery.

  • TechOceanS (EU H2020 101000858): Development of content aware compression, prioritization and transmission of marine imagery for near-realtime remote awareness of seafloor observations over the low communication bandwidths. This project is a consortium project led by the National Oceanography Centre.
Fig 3

Robotics: Development of low-cost, long endurance seafloor imaging floats and highly intelligent and manoeuvrable robotic imaging platform for visual survey of complex environments.

  • DriftCam (EPSRC Fellowship EP/S001182/1): Development of low-cost passive drifting seafloor imaging floats for multi-week endurance seafloor surveys. Challenges are around structuring surveys where you can only go with the flow, localization will low cost sensors, and ensuring failsafe surfacing. This project is in collaboration with Sonardyne International Limited.
  • Smarty200 (EPSRC EP/V035975/1): Core equipment grant for an INS equipped compact AUV for visual surveys of highly complex underwater environments and rapid acoustic and surface satellite communication. This project is in collaboration with Sonardyne International Limited and IQua robotics.
Fig 4

In situ laser spectroscopy: Development of laser spectroscopic methods (LIBS, Raman) and scintillation methods for in situ chemical analysis of marine sediments and particles.

  • RamaCam (NERC NE/R01227X/1) Combined holographic microscopy and Raman spectroscopy for visual and chemical classification of marine  particules. Part of a joint UK-Japan government SCICORP Marine sensor proof of concept program. This project is a collaboration with University of Aberdeen, IIS University of Tokyo and JAMSTEC in Japan.
Fig 5

For more information on research activities, please visit the ocean perception research website.

Research group

Maritime Engineering

Affiliate research groups

Ocean and Earth Science, In Situ and Remote Intelligent Sensing (IRIS), Ocean Perception Laboratory, Institute of Industrial Science, The University of Tokyo

Roles and responsibilities

  • Co-Director of the In Situ and Remote Intelligent Sensing (IRIS) FEPS Centre of Excellence – see trailer
  • Director of Research for the Department of Civil, Maritime and Environmental Engineering – see trailer
  • Deputy Head of Maritime Engineering Group


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SESS6072 Maritime Robotics (Lecturer) - video

SESS6070 Offshore Engineering & Analysis (Module Lead)

FEEG1003 ThermoFluids (Lab coordinator)

Professor Blair Thornton
Engineering, University of Southampton, Southampton Boldrewood Innovation Campus, Burgess Road, Southampton, SO16 7QF

Room Number : 176/3019

Professor Blair Thornton's personal home page
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