News Release

Unmanned and unbothered: autonomous intelligent oceanic exploration is upon us

Taking advantage of the innovations in automated machinery, researchers are using autonomous and unmanned technologies to explore the deep blue sea

Peer-Reviewed Publication

Ocean-Land-Atmosphere Research (OLAR)

Intelligent Swift Ocean Observing System (ISOOS)

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A schematic of ISOOS.

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Credit: W. Xu, J. L. Li, Y. P. Li, H. F. Chen, S. Q. Yang, J. B. Zeng, Y. H. Wang. Networks of Unmanned Underwater Vehicles for Ocean Exploration: Advances and Prospects. Science and Technology Foresight, 2022, 1(2): 60-78.

The ocean has always been a force to be reckoned with when it comes to understanding and traversing its seemingly limitless blue waters. Past innovations such as deep-sea submersibles and ocean-observing satellites have helped illuminate some wonders of the ocean though many questions still remain. These questions are closer to being answered thanks to the development of the Intelligent Swift Ocean Observing System (ISOOS). Using this system, targeted regions of the ocean can be mapped in a three-dimensional method allowing for more data to be gathered in a safer, quicker and more efficient method than existing technologies can achieve.

 

Researchers published their results in Ocean-Land-Atmosphere Research on Sep. 9, 2023.

 

“The basic idea is, using a smart carrier as the mobile system base and control center, to build a cross-domain network of several tens of UAVs [unmanned aerial vehicles], USVs [unmanned surface vessels] and AUVs [autonomous underwater vehicles] for fast, simultaneous, 3-dimensional observation of any targeted regions,” said Chao Dong, researcher and author of the study.

 

This “crew” of unmanned vessels and vehicles is on-trend with the innovations being made in intelligent autonomous machines which are attractive thanks to their adaptability and flexibility, to name just a couple of qualities. Notably, ISOOS can be key in understanding the role of submesoscale eddies, which are essentially circular currents of water that go against the general ocean current (whirlpools) and happen to be less than 100 kilometers wide. There is not much known about these eddies right now since they are subject to high variability in space and time. Therefore, a fast scan in the areas they tend to occur can do much more for understanding their occurrences and role in global ocean dynamics than is possible now with existing methods.

 

Another feat that ISOOS can achieve is ocean floor mapping. Typically this is very time-consuming and expensive, but with the concerted efforts of USVs and AUVs the efficiency in mapping the ocean floor can be increased significantly. For example, a notable recent attempt using AUVs and USVs was the search for the suspected crash of flight MH370. Though no indications of wreckage were found, using the AUVs and USVs 125,000 square kilometers (or 48,262 square miles) of the sea floor was mapped in just under 5 months.  

 

“In the future, we will try to use ISOOS fulfilling the tasks that are either impossible to approach or inefficient to complete with any existing technologies,” said Dake Chen, corresponding author and researcher.  

 

ISOOS opens up many more avenues of exploration and scientific research when humans do not have to directly be involved in manning the crafts, and instead can be operating or observing the missions remotely. The coordinated efforts of vessels and vehicles used in ISOOS can save countless hours of effort, materials, costs and hardship.  

 

ISOOS also has the potential to be used for searching for wreckage from ships or aircraft, as well as capturing time and space-sensitive oceanic phenomena that would otherwise remain unstudied if traditional methods were employed.

 

Chao Dong, Dake Chen, Dongxiao Wang, Tao Lian, Shilu Dai, Yunfei Zhang and Ce Zheng from the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai), with Dake Chen and Tao Lian also from the Second Institute of Oceanography, Ministry of Natural Resources and Chao Dong and Ce Zheng from the Key Laboratory of Marine Environmental Survey Technology and Application, Ministry of Natural Resources, Dongxiao Wang from the School of Marine Science at Sun Yat-sen University, Shilu Dai from the School of Automation Science and Engineering at the South China University of Technology, Yunfei Zhang from the Zhuhai Yunzhou Intelligence Technology Co. Ltd., Wen Xu from the Zhejiang Provincial Key Laboratory of Ocean Observation-Imaging Testbed at the Ocean Academy of Zhejiang University contributed to this research.

 

The National Natural Science Foundation of China supported this research.


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