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Research project

DriftCam - Mapping in the Background: Scalable capabilities using low-cost passive robotic systems for seafloor imaging

Project overview

This fellowship will develop a simple approach to collect large volumes of seafloor visual imagery using fleets of low-cost, passively-drifting underwater robots. Based on the concept of the Lagrangian imaging float outlined in Roman et al., 2011 [1], this fellowship will investigate how seafloor visual observations can scale to enable several orders of magnitude larger regions of the seafloor to be surveyed at significantly lower costs and reduced effort than is possible with today's RAI systems. To achieve this, novel methods will be developed to increase the endurance of these platforms from several hours to several weeks, and enable the location of each platform in the fleet to be determined in a globally consistent way. The images obtained will be packaged into 3D visual seafloor reconstructions along the trajectories taken by the platforms as they drift on near bottom currents. This will provide valuable data for a range of scientific studies and statutory monitoring applications. While the trajectories cannot be precisely targeted, sacrificing the ability to follow predefined track lines allows for a significant reduction in power consumption and can eliminate the need for the expensive sensors and acoustic tracking needed for real-time localisation of RAI systems in the GPS deprived underwater environment. Furthermore, the increased mission duration eliminates the need for daily deployment and recovery using expensive crewed research vessels that put humans in high-risk situations and rapidly exceed the cost of even the most expensive robotic platforms. To demonstrate this concept, this fellowship will develop a fleet of low-cost platforms that can maintain a desired altitude while obtaining 3D images of the seafloor. Each platform will cost < £5k and have an endurance of several weeks. Novel methods to reduce energy consumption will be developed. This includes a buoyancy control system that can achieve neutral buoyancy at any depth even in regions where the density of seawater is not precisely known. An intelligent, low-power 3D imaging system will be developed together with a hybrid altitude and illumination control system that minimises energy consumption. This will adapt both the frequency at which images are acquired and the strength of illumination used in order maintain a high-quality of data while minimising the amount of energy needed to control the platform's altitude. In order to determine the location of the seafloor images, a novel approach that combines; matched features between sequential images to estimate the motion between acquisitions; seafloor depth observations of all members in the fleet; information available about the terrain and the physics of regional scale flow, will be used to determine the most likely trajectories of each platform. The concepts developed in this research will be demonstrated through a series of experiments carried out under controlled conditions and during field trials using a small fleet of passive drifters that will be deployed at sea. [1] C Roman et al., Lagrangian floats as seafloor imaging platforms, Continental Shelf Research 31, 1592-1598 (2011)


Lead researcher

Professor Blair Thornton

Professor of Marine Autonomy

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. For more information on research activities, please visit the Ocean Perception research website.
  • 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 SydneyAT-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. Automated interpretation of data: Development of AI methods for rapid scalable interpretation of seafloor imagery.
Connect with Blair

Collaborating research institutes, centres and groups

Research outputs

Miquel Massot-Campos, Francisco Bonin-Font, Eric Guerrero-Font, Antoni Martorell-Torres, Miguel Martin Abadal, Caterina Muntaner-Gonzalez, Bo Miquel Nordfeldt-Fiol, Gabriel Oliver-Codina, Jose Cappelletto & Blair Thornton, 2023, Estuarine, Coastal and Shelf Science, 291
Type: article