Russia (bbabo.net), - A team of Nizhny Novgorod scientists has developed a prototype and received a patent for a contactless automatic refueling system for unmanned aerial vehicles (UAVs).
Attempts to create such systems are being made in many countries. But the Nizhny Novgorod development is distinguished by the accuracy of coordination of the drone with the gas station and contactless charging. The system makes it possible to get by with a minimum of refinement of the UAV, which significantly reduces the energy consumption, the cost of the system in comparison with analogues and does not affect the flight performance of the UAV.
“The UAV is charged wirelessly using an air transformer, where energy from the primary circuit of the landing site is transferred to the secondary circuit of the device by means of a magnetic field,” said Associate Professor of the Department of Neurotechnology at the Institute of Biology and Biomedicine of the N.I. Lobachevsky Sergey Stasenko. - Our invention eliminates the shortcomings of the prototypes due to the original design of an autonomous gas station and a landing control algorithm based on our own developments in the field of artificial intelligence systems and fluorescence imaging systems.
The control module is designed to communicate with the UAV, and the platform is in the form of an autonomous station powered by solar energy. The drone landing site on the platform is marked with markings. A UV camera is installed on the platform. The power module includes a rechargeable battery and coils to create an alternating magnetic field for contactless refueling.
The UAV enters the visibility zone using a standard navigation system based on GPS / GLONASS. Then, using a radio channel, the drone searches for the local area network of the autonomous station, turns on the ultraviolet radiation source, and transmits its coordinates to the station.
The aircraft is equipped with a computing module that includes a markup recognition algorithm. It is a pre-trained neural network, which allows minimal use of UAV computing capabilities.
Research work was carried out on the basis of the laboratory of advanced methods for analyzing multidimensional data at UNN within the framework of the mega-grant "Scalable networks of artificial intelligence systems for analyzing data of growing dimension".
The team of researchers, in addition to Sergey Stasenko, also includes Alexander Telnykh, a researcher at the Federal Research Center "Institute of Applied Physics of the Russian Academy of Sciences" (IPF RAS), Irina Nuidel, a senior researcher at the IAP RAS, and Olga Shemagina, a researcher at the IAP RAS.
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