Autonomous submersible, Arggonauts, uses Dell for remote data processing

Arggonauts, an autonomous submersible vehicle and one of the finalists in Shell’s Ocean Discovery XPrize competition, is using Dell workstations to survey the seabed.

The autonomous underwater vehicle aims to map 250km² of the ocean floor at a depth of 4,000 metres within 24 hours.

Given that undersea cables connect the internet across continents, and with the oil and gas industry looking to go deep, there is now a need for vehicles to explore the deepest areas of the sea, according to Gunnar Brink, lead for the Arggonauts project.

But exploring the depths of the sea in an unmanned submersible has many challenges. “People have seen the moon for thousands of years, but the sea is completely dark. As a scientist, it is a pity we know more about the moon than the sea floor, yet 70% of Earth is sea,” said Brink.

One of these challenges is that there is no data exchange in the deep sea. “No radio or light can go through 7km of water. This means that data transmission speeds are limited to 4kbps acoustic transmission,” said Brink.

And while it is possible to investigate the ocean floor at the surface, Brink said the results would be lower resolution than if a submersible collected a survey of the seabed. Another problem is that GPS does not work in deep water.

These facts mean that Arggonauts needs a way to communicate with a surface vehicle, but it also needs to process vast amounts of survey data quickly, by itself.

“Since it is so difficult to get information through seawater, GPS data is sent via acoustics to the sea floor,” said Brink. The data for the GPS location is sent as low-frequency sound, capable of travelling vast distances, just as the sound of whale song can travel through the deep ocean.

For local computation, Arggonauts uses Dell EMC’s customised workstation technology – the Precision 7910. Dell’s technology allows the Arggonauts team to control its remotely operated vehicles from the shore and capture subsea data images. The high-performance computing renders the images and translates the data into maps, while artificial intelligence (AI) is used to quickly classify images from the unstructured data.

By using the mobile workstation, Brink said teams are able to get feedback quicker, enabling 48 hours of data to be processed in seven hours.