Abstract:
Here, you will find details on how to model, design, and control an Autonomous Underwater ROV used for inspection and exploration. In contrast to the common ROVs, which need human operators, this system is created for autonomous operations where the advanced algorithms of navigation, control, and perception are included. The research elaborates on the dynamic model that takes into account hydrodynamic forces, added mass effects, buoyancy, and external disturbances mentioned above, which serve as a foundation for the reliable mooring control strategies for stability and precise maneuvers. One of the outstanding contributions made is the incorporation of an autonomous guidance mechanism that utilizes sensor fusion with vision-based perception and inertial navigation for real-time obstacle avoidance and target monitoring. The ROV is designed for enclosed and congested underwater environments and therefore, is appropriate for ship hull inspection, pipe monitoring, and environmental checks. Image processing with the techniques of machine learning enhances the recognition of objects, identifying anomalies to collect data for maintenance and research. Simulation and experimental validation show that the proposed control methodologies are effective in realizing autonomous navigation and stability and accuracy in underwater inspection. This study continues the development of autonomous underwater systems, making the exploration of submerged structures and environments safer and more efficient.
