BlueROV2 is a modular remotely operated underwater vehicle (ROV) developed by the American marine robotics company Blue Robotics. It was released in 2016 as a l
BlueROV2 operating with ArduSub control software | |
| Class overview | |
|---|---|
| Name | BlueROV2 |
| Builders | Blue Robotics |
| Built | 2016 |
| General characteristics | |
| Type | Remotely operated underwater vehicle (ROV) |
| Displacement | 12 kg (26 lb)[1] |
| Length | 45 cm (18 in)[1] |
| Depth | Up to 100 m (330 ft) (standard) [2]; up to 300 m (980 ft) (extended) [3] |
| Installed power | Lithium-ion battery |
| Propulsion | Six or eight thrusters (vectored configuration) |
| Notes | Tethered control via surface computer/tablet |
BlueROV2 is a modular remotely operated underwater vehicle (ROV) developed by the American marine robotics company Blue Robotics. It was released in 2016 as a low-cost platform with open-source control software for underwater research, inspection, and educational applications.[4][2]
BlueROV2 has been used as an open-source platform in academic marine robotics research and has been described, alongside OpenROV, as part of a shift toward lower-cost underwater vehicles for researchers, small organizations, and hobbyists.[4][5]
BlueROV2 is built around a modular frame that supports integration of cameras, sonar, robotic grippers, and additional scientific instruments.[4]
The vehicle is configured with six thrusters to enable maneuvering in all directions.[5] It is controlled via a tether connected to a surface computer or tablet running open-source control software.[2]
The onboard electronics are based on a Raspberry Pi, which serves as the main controller and is typically connected to a front-facing camera, with support for additional sensors such as an inertial measurement unit (IMU).[5][3]

In 2020–2025, the platform has been used in academic research to develop low-cost autonomous underwater systems, including open-source hardware and software extensions for vision-based SLAM, dynamic simulation models, and experimental benchmarking of machine-learning methods for vision-based position locking in real-world underwater environments.[6][7][8]
The BlueROV2 has also been adopted in marine science and underwater archaeology, where it is used for underwater observation, documentation, and environmental data collection.[4][9]
BlueROV2 has been used in aquaculture and offshore infrastructure inspection, including the monitoring of shellfish beds, fish stocks, anchors, and subsea installations.[4] It has also been employed in the development and testing of autonomous navigation and sensor-fusion systems for small underwater vehicles.[1]
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