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Dr Miguel F Massot-Campos MEng, PhD

Senior Research Fellow

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Miguel Massot is a Senior Research Fellow within Engineering and the Physical Sciences at the University of Southampton. He currently works on underwater robotics, seafloor mapping and imaging techniques for a better understanding of our oceans in Ocean Perception research group.

We know more about the surface of the Moon and about Mars than we do about the sea floor.

He graduated in 2011 from the Polytechnic University of Barcelona with an MEng degree in Industrial Engineering. In 2013, he graduated with an MSc in Information Technologies from the University of the Balearic Islands and PhD in 2019. His PhD thesis focused on underwater laser 3D reconstruction.

He is a field robotics researcher with more than eighty days spent at sea doing field experiments whilst collaborating with other universities and 3rd parties on state-of-the-art research and work-class underwater robots. His research focuses on improving the imaging capabilities in ocean exploration and situational awareness.

In 2018, he was appointed as a research fellow on a project about scalable underwater mapping and drifters called DriftCam, and in 2021 as senior research fellow for the project TechOceanS.

For more information on research activities, please visit the Ocean Perception website.

Consistent underwater laser bathymetry

The accuracy of a bathymetric map is dependent on the accuracy of the navigation solution used. The image resolution of an underwater imaging survey has decreased from decimetres to millimetres in the past years. However, localisation sensors still have the same sensing uncertainty in the scale of meters. In this research, Miguel proposed methods to improve laser-based bathymetric maps using probabilistic approaches.

Consistent underwater laser bathymetry
Consistent underwater laser bathymetry

Scalable underwater robotics

Robotic seafloor imaging is becoming increasingly recognised as a necessary component of environmental baseline and infrastructure impact assessment surveys. To enable massive scalability, the project “Mapping in the background” will build Driftcams, or imaging floats. These platforms are energetically efficient as they do not propel themselves laterally, instead drifting passively on currents near the seafloor. Actuators are only used to dive and maintain a constant altitude during their observations. The reliance on crewed vessels with expert operators and facilities for energy replenishment can be reduced, making these platforms suitable for deployment in large numbers. In this research, Miguel studied how to deploy these drifters to target a specific location of the seafloor, and how to achieve fail-safe neutral buoyancy at depth.


Remote awareness

To make imaging in marine applications scalable, there is a need to eliminate reliance on tethering and/or recovery for data extraction; and developed end-to-end automated workflows (both training and analysis) for information extraction that are robust to different targets and instrument specifications. The project “TechOceanS” will make use of AI-driven image processing and transmission to bridge information from underwater robots to shore and back.

Remote Awareness
Remote Awareness

Research Projects

"Mapping in the background" will build a fleet of ultra-low cost passive underwater robotic platforms, or DriftCams, capable of building massive digital maps of the seafloor using underwater currents to drift along near the seabed.


“TechOceanS” will develop nine innovative technologies and methods for deep sea sensing, sample collection and on-board analysis, and AI-driven image processing and transmission.

Research group

Maritime Engineering

Affiliate research groups

Ocean Perception, Systems, Robotics & Vision, University of the Balearic Islands

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Book Chapters



Individual Project

FEEG3003 Ship Science Co-supervisor

Maritime Robotics

SESS6072 Ship Science Lecturing

At Ocean Perception we are devoted to bridging the practical and theoretical state of the art in support of marine science.

To address bottlenecks found at research cruises, where data processing happens offline and understanding is achieved months, even years after a cruise, we developed oplab_pipeline. This software deals with ROV or AUV raw imagery and navigation data to generate post-processed geo-localised, colour-corrected imagery that can be generated on the ship.

This data can be fed to unsupervised clustering pipelines or to online databases for further processing.

Dr Miguel F Massot-Campos
Engineering, University of Southampton, Southampton Boldrewood Innovation Campus, Burgess Road, Southampton, SO16 7QF

Room Number : 176/3037/B1

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