Enhancing AUV 3D Obstacle Avoidance: A Novel Approach with Self-Supervised Network for Fusion of Forward-Looking Camera and Sonar Data

Yevgeni Gutnik, Izhak Fabian, Nir Zagdanski, Oren Gal, Tali Treibitz, Morel Groper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Autonomous underwater vehicles (AUVs) are typically programmed to follow routes based on predefined waypoints and depth profiles. However, in complex and unpredictable environments-such as coral reefs, offshore structures, or ship-wrecks-AUVs can encounter unexpected obstacles that pose risks to both the vehicle and its surroundings. To navigate and avoid unexpected obstacles, AUVs operating in such environments are often equipped with forward-looking sonars (FLS). However, standard FLS sensors are typically limited in resolution and can only provide 2D information on bearing and range, restricting their effectiveness in facilitating navigation in complex environments. Vision cameras, on the other hand, offer high-resolution data with bearing and elevation information, but when using a single-camera setup, they cannot reliably provide distance information. This study introduces a comprehensive framework for the fusion of forward-looking camera (FLC) and FLS data, using a projection of FLS data into the FLC frame and incorporating data from a trained self-supervised network.

Original languageEnglish
Title of host publicationOCEANS 2024 - Halifax, OCEANS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331540081
StatePublished - 2024
EventOCEANS 2024 - Halifax, OCEANS 2024 - Halifax, Canada
Duration: 23 Sep 202426 Sep 2024

Publication series

NameOceans Conference Record (IEEE)
ISSN (Print)0197-7385

Conference

ConferenceOCEANS 2024 - Halifax, OCEANS 2024
Country/TerritoryCanada
CityHalifax
Period23/09/2426/09/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • Autonomous underwater vehicles (AUVs)
  • forward-looking sonar
  • obstacle avoidance
  • sensor fusion
  • underwater image processing
  • underwater navigation

ASJC Scopus subject areas

  • Oceanography
  • Ocean Engineering

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