Research project

HEIF 2021/22 Knowledge exchange of subsea laser visual mapping hardware and data processing methods and application to environmental monitoring

Project overview

This technology transfer collaboration investigated crossovers between the hardware and data processing methods used by BioCam and Voyis imaging systems, and investigated whether the Voyis commercial imaging units mounted on < 100 kg class compact AUVs like the UoS Smarty 200 platform can contribute to coastal conservation. The following was investigated:
• How sharing of real-time processing methods developed by Voyis and UoS/Sonardyne can improve data acquisition of the respective systems (e.g. fast laser acquisition, accurate colour correction)
• How UoS in situ calibration methods can be applied to Voyis imaging hardware for whole-map uncertainty characterisation
• How UoS rapid post-processing methods can be applied to combine Voyis laser bathymetry with strobed imagery based on Sonardyne doppler aided inertial navigation .
• Automated interpretation of Voyis imagery using UoS machine learning methods for rapid scene understanding
• Demonstrate coastal conservation application using the <100kg class compact hover-capable UoS Smarty 200 AUV

Staff

Lead researchers

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.
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Other researchers

Mr Adrian Bodenmann

Senior Research Fellow

Research interests

  • High-resolution visual seafloor mapping for benthic habitat mapping and subsea infrastructure monitoring
  • Remote awareness for autonomous offshore mapping operations
  • Uncertainty characterisation in digital 3D reconstructions
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Collaborating research institutes, centres and groups

Research outputs