Multimodal Sensor Fusion for UXO Classification and Remediation

Abstract

Despite the ubiquity of robotic systems in deep-ocean intervention, such approaches have limited impact in shallow-water UXO remediation, due in large part to the relatively crude and non-dextrous nature of the current state of the art in tele-operated manipulation. Computer-assisted or -controlled approaches over great promise for addressing the fundamental issues in subsea tele-operation, allowing safe and effective execution of UXO remediation tasks; however, such computer assistance requires accurate digital models of the UXO in place on the seabed. While terrestrial research can rely on a variety of structured light and LiDAR-based sensors to generate such models in near realtime, no such turnkey solutions exist for subsea application, particularly for operation in the shallow, turbid waters where UXO remediation is of highest priority. This program examines the use of visible light stereo cameras and a high frequency forward-looking sonar, combined with platform motion, to construct and update 3D reconstructions of UXO on the sea floor.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2020
Accession Number
AD1169364

Entities

People

  • Aaron Marburg

Organizations

  • University of Washington

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Cameras
  • Computer Stereo Vision
  • Computer Vision
  • Data Sets
  • Deep Oceans
  • Detection
  • Detectors
  • Inertial Navigation
  • Inertial Navigation Systems
  • Navigation
  • Physics Laboratories
  • Seabed
  • Sensor Fusion
  • Simultaneous Localization And Mapping
  • Three Dimensional
  • Unexploded Ammunition
  • Visible Spectra

Readers

  • Acoustical Oceanography.
  • Military/Explosive Ordnance Disposal (EOD) Technology
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks
  • Autonomy