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Related Experiment Video

Updated: May 10, 2026

Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus SCUVA
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Autonomous Sea Floor Coverage with Constrained Input Autonomous Underwater Vehicles: Integrated Path Planning and

Athanasios K Gkesoulis1,2, Panagiotis Georgakis1,2, George C Karras2,3

  • 1Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece.

Sensors (Basel, Switzerland)
|February 26, 2025
PubMed
Summary

This study presents an integrated framework for autonomous underwater vehicles (AUVs) to achieve efficient seafloor coverage. The system combines optimal path planning and robust control for reliable underwater operations, including debris detection.

Keywords:
BlueROV2GazeboROSautonomous underwater vehiclescoverage path planninginput saturationrobust controlunderwater robotics

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Area of Science:

  • Robotics
  • Ocean Engineering
  • Control Systems

Background:

  • Autonomous underwater vehicles (AUVs) require sophisticated path planning and control for effective seafloor coverage in challenging environments.
  • Real-world operations face obstacles, disturbances, and physical limitations that necessitate integrated solutions.

Purpose of the Study:

  • To develop and validate a fully integrated framework for AUVs combining optimal coverage path planning and robust constrained control.
  • To enhance AUV capabilities for tasks like underwater debris detection through improved navigation and control.

Main Methods:

  • Implemented an optimal coverage path planning algorithm using a priori area information for maximal coverage, minimal turns, and obstacle avoidance.
  • Employed a reference modification technique for robust waypoint tracking under input constraints.
  • Validated the integrated framework using ROS, Gazebo, and ArduSub Software-in-the-Loop (SITL) on a BlueROV2 platform.

Main Results:

  • Demonstrated the synergistic effect between path planning and control strategies within the integrated framework.
  • Validated the framework's effectiveness and readiness for practical seafloor operations through high-fidelity simulations.

Conclusions:

  • The integrated path planning and control framework significantly enhances AUV performance for seafloor coverage tasks.
  • The developed system is robust and suitable for real-world applications such as underwater debris detection.