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Synapse
March 21, 2026QRU Quaderns de Recerca en Urbanisme0 citationsOpen Access

Detect and follow a custom object, using OBSEA underwater crawler

AFAhmad FalahzadehabarghoueeDTDaniel TomaMCMarc Nogueras Cervera

Key Points

  • This research aims to enhance the tracking capabilities of underwater crawlers for monitoring marine environments.
  • Utilized OBSEA underwater crawler for detection and tracking tasks
  • Prepared a custom dataset for training
  • Employed YOLO for model training
  • Implemented an algorithm for object tracking
  • Successfully detected and tracked a custom object in a controlled laboratory setting
  • Increased surveillance efficiency of underwater observatories
  • Demonstrated feasibility of automated tracking, potentially reducing operational costs

Abstract

The strategic advancement of monitoring protocols relies on cabled marine observatories for obtaining real-time multiparametric biological and environmental data. The integration of docked mobile platforms, such as underwater crawlers, proves beneficial, extending the surveillance radius of underwater observatories and enhancing their overall performance and functionality. Normally, underwater crawlers are controlled manually, resulting in considerable time and cost expenditures for both crawler operation and monitoring seabed species. To overcome this challenge, the OBSEA Underwater crawler was employed to detect and track a custom object in the laboratory environment. The detection process involved the preparation of a dataset, training a model with YOLO, and finally utilizing an algorithm to track the custom object.

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Cite This Study

Falahzadehabarghouee et al. (2024) studied this question.

synapsesocial.com/papers/69be35386e48c4981c673442https://doi.org/10.5821/iwp.2024.23.14124
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Autonomous movement of obsea underwater crawler for monitoring underwater environments2025
  2. 2Tele-operated ecological monitoring at the seafloor observatory (OBSEA)2021
  3. 3Automatic system for 3D photogrammetry of small artificial biotopes using the crawler remote operating vehicle at OBSEA observatory2023
  4. 4Research on a Lightweight Algorithm for Seabed Organism Detection Based on Deep Learning2026 · 1 citations
  5. 53D Detection and Tracking of a Moving Object by an Autonomous Underwater Vehicle With a Multibeam Imaging Sonar: Toward Continuous Observation of Marine Life2024 · 8 citations