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Vision-Based Localization System Suited to Resident Underwater Vehicles.

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This study introduces a low-cost navigational marker for resident robotic vehicles, enhancing subsea localization accuracy for inspection, maintenance, and repair (IMR) operations. Offshore trials demonstrated its effectiveness in eliminating vehicle inertial navigation system (INS) drift near targets.

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Area of Science:

  • Robotics and Autonomous Systems
  • Ocean Engineering
  • Navigation and Control

Background:

  • Increasing demand for permanently deployed resident robotic vehicles in commercial inspection, maintenance, and repair (IMR) activities.
  • Challenges in maintaining accurate vehicle navigation, specifically Inertial Navigation System (INS) drift, when operating close to subsea targets.
  • Need for robust and cost-effective localization solutions for autonomous underwater vehicles (AUVs).

Purpose of the Study:

  • To present a novel, low-cost, and low-maintenance navigational marker system for subsea localization.
  • To demonstrate the system's capability to eliminate drift in a vehicle's INS solution near IMR targets.
  • To evaluate the system's performance and error propagation during offshore trials.

Main Methods:

  • Development and deployment of a fixed subsea localization marker system on resident field assets.
  • Integration of the marker system with on-vehicle machine vision algorithms for pose estimation.
  • Utilizing high-resolution world coordinate frame registration with a high refresh rate for accurate positioning.
  • Conducting offshore trials in the North Atlantic Ocean, comparing system performance against a commercial state-of-the-art INS in pure inertial mode.

Main Results:

  • Successful elimination of vehicle INS drift when in proximity to the navigational marker.
  • Demonstration of high-resolution pose estimation and world coordinate frame registration.
  • Evaluation of system performance, including position error propagation, during trials.
  • Analysis of the impact of intermittent visual position updates on Kalman filter and INS solutions.

Conclusions:

  • The developed subsea localization marker system effectively enhances the navigational accuracy of resident robotic vehicles for IMR tasks.
  • The system provides a reliable method for pose estimation and accurate coordinate frame registration, crucial for close-proximity operations.
  • Experimental results validate the system's performance and offer insights into error mitigation strategies for AUV navigation.