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Home›News›ARL enters flying nodes research pact with RGU
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October 5, 2018 · about 7 years ago

ARL enters flying nodes research pact with RGU

ARL has entered into a collaboration with RGU on swarm technology research of a system for a swarm of autonomous underwater sensor flying nodes.

2 minutes read
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Autonomous Robotics (ARL) has entered into a collaboration with Robert Gordon University (RGU) on swarm technology research of a simultaneous, distributed, and scalable localization system for a swarm of autonomous underwater sensor flying nodes.

ARL said on Friday that the purpose of this research was to further enhance the capability of the flying node system and further reduce the cost and time for ocean bottom seismic surveys.

RGU is a Scottish university in Aberdeen, and its School of Engineering has a long track record of working in collaboration with industry.

The Swarm Technology research will be performed by Wai-keung Fung and Adham Sabra , who are with the Communications and Autonomous Systems Group within RGU’s School of Engineering, with results of the research expected within 12 months.

Dave Grant , ARL chairman, said: “ARL is working with RGU to research and create a practical localization system for the flying node system which will allow the flying nodes to operate in a swarm and move from their initial seabed position to a new seabed location.

“This Swarm Technology will be used to enhance the capability of the flying node system and provide even greater savings in cost and time for the offshore energy operators performing ocean bottom seismic surveys.

“I would also like to thank the Oil & Gas Innovation Centre (OGIC) for their support of this project. OGIC assists companies to find academic partners and provides funding for innovative projects which benefit the oil and gas industry.”

Fung, group lead of the communications and autonomous systems group at RGU, added: “This great opportunity enables our research group to apply AI algorithms for large-scale underwater swarm localization, which is one of the core research problems in underwater robotics and sensor networks.

“Localisation accuracy can be greatly improved by fusing estimates from multiple localization methods. This can enhance autonomous deployment and retrieval of underwater flying nodes for various subsea missions, including marine seismic surveys.”

It is worth reminding that ARL announced the completion of autonomous sea trials of a prototype ‘flying node’ autonomous underwater vehicle (AUV).

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