// Workers AI · dad joke modeDoes BlueROV2 have friends? It's underwater, so it's a blue lone.
 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]
Design and architecture
[edit]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]
Applications
[edit]
Academic research
[edit]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]
Industrial use
[edit]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]
See also
[edit]External links
[edit]References
[edit]- 1 2 3 Rojer, Jim; Binnerts, Bas; Maat, Danny (20 December 2022). "Subsea autonomous navigation capabilities for small-sized underwater vehicles: Towards affordable high-end solutions to direct ROVs". Hydro International.
- 1 2 3 Mogg, Trevor (23 June 2016). "This underwater drone lets you explore the deep blue without getting wet". Digital Trends. Retrieved 14 February 2026.
- 1 2 Whittaker, Ashley (2024). "BlueROV2 R4". The Official Raspberry Pi Handbook 2025. Raspberry Pi Press. p. 182. ISBN 9781916868267.
- 1 2 3 4 5 Hambling, David (19 September 2016). "What Drones Did for the Sky, Robot Subs Are About to Do for the Sea". Popular Mechanics.
- 1 2 3 Bräunl, Thomas (2022). Embedded Robotics: From Mobile Robots to Autonomous Vehicles with Raspberry Pi and Arduino. Springer Nature Singapore. p. 244. ISBN 978-981-16-0804-9.
- ↑ "Low-Cost, Open-Source Hovering Autonomous Underwater Vehicle (HAUV) for Marine Robotics Research based on the BlueROV2". 2020 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV). St. John's, Newfoundland and Labrador, Canada: IEEE. 2020. doi:10.1109/AUV50043.2020.9267913.
- ↑ von Benzon, Malte; Sørensen, Fredrik Fogh; Uth, Esben; Jouffroy, Jerome; Liniger, Jesper; Pedersen, Simon (2022). "An Open-Source Benchmark Simulator: Control of a BlueROV2 Underwater Robot". Journal of Marine Science and Engineering. 10 (12) 1898. MDPI. doi:10.3390/jmse10121898.
- ↑ Safa, Ali; Aman, Waqas; Al-Zawqari, Ali; Al-Kuwari, Saif (2025). "Benchmarking Online Object Trackers for Underwater Robot Position Locking Applications". IEEE Journal of Oceanic Engineering. 50 (4). IEEE: 2770–2781. doi:10.1109/JOE.2025.3590074.
- ↑ Qiao, Chen; Zhou, Huiyu; Wu, Lianghong; Zhou, Yimin, eds. (2022). Intelligent Control and Applications for Robotics. Frontiers Media SA. p. 53. ISBN 978-2-8325-0095-8.
