ST. PETERSBURG, December 2. /TASS/. Scientists of the St. Petersburg Federal Research Center (the Russian Academy of Sciences), together with the Kant Baltic Federal University and the R-Sensor Company, developed a prototype of an unmanned aerial vehicle with an integrated seismic sensor and a ground-penetrating system. The product may be used for geological assessment in hard-to-reach areas as it gives tighter contact with the soil and reliable seismic data registration, press service of the St. Petersburg Institute of Physics and Technology (the Russian Academy of Sciences) told TASS.
"We have developed a UAV prototype with a built-in seismic sensor and a ground-penetrating system. This design provided tighter contact with the surface and high-quality registration of seismic data. It also eliminates the problem where a drone is searching, targeting and capturing a freestanding sensor. After taking measurements, the drone returns to the operator on its own. The prototype has passed tests in real conditions in the Leningrad Region. In the future, it will be possible to use it much further north - in the harsh Arctic conditions for geological assessment, including on ice areas," the press service quoted Anton Saveliev, head of the Laboratory of Autonomous Robotic Systems, as saying.
Presently, specialists are using wired measuring systems in seismic exploration. To perform these works, it is necessary to bring to the site and accommodate hundreds of specialists far from big settlements, in areas lacking reliable transport and information infrastructures, and often in harsh climatic conditions.
During work on the project, scientists developed a drone design and a system that provides autonomous work and coordination with other types of drones, the press service continued, adding the work was supported by a grant from the Russian Science Foundation.
"During the fundamental research, specialists created unique methods and models of seismic data processing, and made prototypes of sensors and special UAVs. They have formed a huge scientific reserve for training neural models to classify types of territories, using the positioning method and searching for optimal zones for embedding the sensor on the UAV," the press service quoted the Center's Project Manager, Director of the St. Petersburg Institute of Physics and Technology (the Russian Academy of Sciences) Andrey Ronzhin as saying.