Russia develops artillery shells that calculate the time of explosion

This type of bullet is equipped with artificial intelligence, can automatically calculate the explosion time to destroy the target most effectively,manufacturer NPO Pribor said.

The A-220M 57mm naval gun is the development platform for this smart ammunition. Photo: Sputnik

Russia's Rostec technology corporation has just introduced a smart artillery shell model manufactured by the NPO Pribor design bureau, the corporation's announcement said on October 17.

The appearance of the bullet is identical to that of a conventional bullet, the difference lies in the small-sized detonator equipped with artificial intelligence (AI). According to Mr. Sergey Rusakov, representative of Rostec, the AI ​​detonator will program the explosion time of the bullet before leaving the gun barrel. The explosion time is automatically calculated by the control computer based on parameters such as distance to the target, wind direction and air humidity.

When approaching the target, this type of fragmentation bullet will be detonated and shoot out thousands of small balls like a cloud capable of destroying enemy equipment, especially small devices such as flycams and unmanned aerial vehicles (UAVs).

AI bullets will be tested on the AU-220M smart cannon. Photo: Sputnik

Oleg Chizhevsky, chief engineer of NPO Pribor, said that the projectile design has been completed and will soon be tested in the field. Chizhevsky also believes in the potential of this project, saying that NPO Pribor's smart ammunition will be equipped with the Russian army in the near future.

Kurganets-25 vehicles will be equipped with AI artillery shells in the near future. Photo: Vitaly V. Kuzmin

In the first stage, this ammunition will be tested on the AU-220M Baikal 57 mm automatic gun module. This is the main weapon of the most modern Russian armored vehicles such as the Boomerang, Armata T-15 and Kurganets-25. Later, NPO Pribor will develop a line of 30 mm smart ammunition for older vehicles such as the BTR-82, BMP-2 and BMP-3.

According to VNE