HyDRA Scorpion: A Cost-effective and Modular ROV for Real-Time Underwater Inspection, Intervention, and Object Detection

2026-05-09

AI Summary

This study addresses the limited accessibility of underwater operations due to the high cost of commercial remotely operated vehicles (ROVs) and insufficient integration of intelligent perception and manipulation capabilities. To overcome these challenges, this work proposes a low-cost, modular ROV designed for local fabrication, which uniquely integrates AI-driven real-time object detection (achieving an mAP of 0.89), 3D ranging and mapping, a four-degree-of-freedom thruster system, and a dual-function, 360° tangle-free manipulator—all on an affordable platform. The system has successfully passed pressure testing at 4 bar (equivalent to approximately 305 meters depth) and demonstrates positioning accuracy within ±0.15 meters. This tight coupling of intelligent perception and precise intervention significantly enhances the operational capability and accessibility of small-scale ROVs.

Abstract

A Remotely Operated Vehicle (ROV) is a tethered underwater robot used for tasks like inspection and intervention. While essential tools for underwater science, the high cost of commercial ROVs and a persistent gap between mechanically capable platforms and those with integrated intelligence create a significant barrier to access. HyDRA Scorpion differs from conventional systems by addressing these challenges, integrating an advanced, AI-driven perception stack with in-situ measurement capabilities onto a low-cost, locally manufacturable platform. The system combines 4-DoF maneuverability, dual manipulators, and a custom pressure-tested housing. Experimental results validate the system's robustness and performance. Leak-free operation was confirmed through prolonged pressure testing of the electronics housing to 4 bar, equivalent to the pressure of a 304.8-meter water depth approximately in a simulated environment, with no moisture ingress detected. The vehicle also demonstrated stable station-keeping, maintaining its position within a tight tolerance of $\(\pm\)0.15$ meters under external disturbances. The onboard AI module achieved underwater object detection mean Average Precision (mAP) of 0.89 with real-time inference, length and 3D-mapping based distance measurement. Also, 4-DoF manipulator arm can grip and maintain dual-function manipulator feature which support 360 degree tangle-free rotation.

Problem

• Remotely Operated Vehicle
• cost barrier
• integrated intelligence
• underwater inspection
• object detection

Innovation

• AI-driven perception
• low-cost ROV
• real-time underwater object detection
• modular underwater robot
• in-situ measurement