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Related Experiment Videos

Pose Estimation of Unmanned Underwater Vehicles Using Augmented Reality Marker-Based Simulations.

Nirmalajyothi Narisetty1, Sirisha Potluri2, P Aurchana3

  • 1Department of Computer Science and Engineering, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Bowrampet; nirmala.narisetty@gmail.com.

Journal of Visualized Experiments : Jove
|July 6, 2026
PubMed
Summary

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Modeling and Similitude01:12

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

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This summary is machine-generated.

This study developed a simulation framework for Unmanned Underwater Vehicle (UUV) pose estimation using monocular vision. The system achieved stable performance in controlled settings but struggled with hydrodynamic disturbances, highlighting the need for advanced control strategies.

Area of Science:

  • Robotics
  • Computer Vision
  • Control Systems

Background:

  • Accurate pose estimation is crucial for Unmanned Underwater Vehicle (UUV) navigation.
  • Monocular vision systems offer a cost-effective solution but face challenges in underwater environments.
  • Integrating perception and control is essential for robust UUV operation.

Purpose of the Study:

  • To present a simulation-based framework for UUV pose estimation using monocular vision.
  • To evaluate the performance of a Perspective-n-Point (PnP) algorithm and a Proportional-Integral-Derivative (PID) controller in a ROS-Gazebo environment.
  • To assess the system's robustness against hydrodynamic disturbances.

Main Methods:

  • Utilized the RexRov2 UUV model in ROS-Gazebo with ArUco_ROS for marker detection.

Related Experiment Videos

  • Employed a Perspective-n-Point (PnP) algorithm for pose estimation.
  • Implemented a PID controller for motion regulation based on visual features.

    • Main Results:

    • Achieved stable and accurate pose estimation under nominal conditions, with close agreement to ground truth.
    • Demonstrated smooth trajectory tracking in controlled simulated environments.
    • Observed significant deviations and instability in tracking performance under increased hydrodynamic disturbances.

    Conclusions:

    • The proposed framework is a valuable tool for testing underwater navigation and perception-control integration.
    • Classical PID control demonstrates limitations in nonlinear underwater environments with disturbances.
    • Further research into robust control strategies is necessary for reliable UUV operation in challenging conditions.