Although current systems still operate within what drone operators call a “reasonable impact radius”—meaning a tank or trench is likely to be hit, though not necessarily at its most vulnerable point—ongoing AI advancements and refinements in onboard hardware promise to narrow this margin considerably.
Case Study 8: VGI-9, an Autonomous Navigation System
As drone manufacturers shared with CSIS, VGI-9 is one of the most widely used targeting systems. It transforms an FPV drone into a semiautonomous weapons system capable of locking on the target and striking even moving targets at speeds of up to 80 km/h with precision.
First, the system requires a secure PIN code to activate the targeting function before each mission. Consequently, adversaries capturing the drone without the code cannot use its targeting capabilities. Once the drone is airborne, the pilot guides it to the operational zone while observing a real-time video feed with an enlarged picture in the corner of the screen to facilitate precise target identification.
The system continuously monitors EW threats. The on-screen interface provides real-time feedback on signal interference through received signal strength (RSS) and signal-to-noise ratio (SNR) indications. If enemy jamming is present, the SNR value drops close to or below zero, indicating that the drone connection is heavily disrupted.
To counteract this, the drone is equipped with a cruise control mode. If the drone encounters a disruption, the operator maintains a steady altitude and activates cruise control. As the name suggests, once engaged, the mode locks the drone’s altitude, speed, and direction, allowing it to continue its flight path even in areas with severe signal jamming. This fail-safe ensures the drone does not crash due to signal loss but instead bypasses jamming zones and remains operational beyond them, where the enemy forces or precious equipment can be located. This feature alone significantly increases the chances of mission success.
As the drone approaches the target area, the pilot searches for the target. Once the target is visually confirmed, the pilot activates the target lock-on function. At this point, control transitions from manual flight to autonomous engagement. The drone’s onboard system locks on to the selected point and begins its final descent toward the target without requiring further input from the pilot. If communication is still available, the pilot retains limited ability to make microadjustments. Using the right control stick, the pilot can slightly adjust the drone’s trajectory to ensure an optimal strike (e.g., the least-armored portion of an enemy tank).
In a fully autonomous strike, the system ensures the drone stays on course, even without pilot intervention. The drone’s onboard AI handles the last moments of navigation, ensuring the maximum probability of a successful hit.
The current state of this technology has limitations. The system significantly enhances effectiveness against large, high-value targets like tanks and artillery, but its precision is limited when targeting specific parts of a vehicle. While it ensures the drone reaches the target, it does not guarantee a strike on an exact point, such as a vulnerable section of a tank, to destroy the target completely, though disabling the target remains feasible.
Case Study 9: Autonomous Navigation from The Fourth Law
Yaroslav Azhnyuk, founder of the company The Fourth Law, told CSIS that his company’s goal is to develop an AI-enabled guidance system for UAVs that allows them to operate in fully autonomous mode. The Fourth Law developed a module for FPV drones—an inexpensive yet powerful electronic component that includes a camera and a small computer board with software that costs around $50 to $100. This module may be installed on any of the most common configurations of FPV drones, whether 7 or 10 inch, between the two mounting rails where the drone’s front camera is usually placed. This technology is already operational and in serial production, integrated with dozens of manufacturers, and these systems are actively in use on the front line.
The demonstration made to CSIS showed an FPV feed with added zoom and an active “target seeker,” illustrating how analog video, despite its poor resolution, remains widely used for its low cost and reliability. Once the pilot identifies a moving truck within the zoomed area, flipping a single switch encases the target in a red square and hands control over to the onboard AI. Two algorithms then work together: one continuously tracks the target’s movement, while the other manages the drone’s complex flight mechanics. A separate neural network refines the target’s boundaries in real time, ensuring precise engagement despite the vehicle’s ongoing motion.
Company representatives told CSIS that The Fourth Law will soon introduce last-mile guidance for fixed-wing drones, allowing greater flight range, overcoming radio horizon limitations, and extending the operational distance by 48–96 km. However, the last-mile guidance system is just the first step in the company’s five-step road map to full autonomy.
The second stage is the development of autonomous last-mile bombing. The process works like the current system, but instead of crashing into the target, the drone drops a bomb. This autonomous payload release system is already being tested in a lab. A computer can execute a drop with far greater precision than a human, even from complex maneuvers that a human pilot could not perform in time. After bombing is finished, the pilot regains control, bringing the drone back instead of losing it after every mission.
A third crucial technology is also undergoing testing. Automatic targeting uses neural networks to identify and track targets autonomously. The team has successfully optimized object recognition using neural networks to run efficiently on very inexpensive hardware.
By combining all three technologies, the company hopes pilots need only launch the drone and assign a waypoint on the map. The drone would take off, fly to the target, execute the drop, return, and land—all in complete radio silence and full autonomy, without requiring pilot intervention.
As a fourth step, the system will be able to navigate without GPS, using preloaded maps, onboard sensors, and optical navigation, ensuring mission success even in GPS-denied areas.
The fifth stage of development involves automating takeoff and landing processes for both copter and fixed-wing drones, a critical advancement for the autonomous engagement of airborne threats such as enemy FPV drones. For instance, in a scenario in which troops are positioned in a trench under attack by enemy FPV drones, several sentry drones could be deployed in front of the trench and equipped with cameras to scan the sky. Upon detecting an incoming enemy FPV drone, these sentry drones could launch autonomously, either colliding with the threat or detonating nearby, thereby neutralizing the danger and safeguarding allied forces.
In many ways, The Fourth Law’s road map to full autonomy reflects the general approach Ukrainian companies take in developing autonomous capabilities.
Case Study 10: Ukrainian Long-Range-Strike Drones
Among the many military systems Ukraine is enhancing with AI capabilities are one-way attack drones (OWA-UAVs). While these kamikaze drones are used everywhere along the front line, long-range-strike drones with some elements of autonomy represent a particularly interesting case. These drones are developed exclusively in Ukraine and have seen widespread use across various Ukrainian agencies. Their effectiveness and fast evolution demonstrate their ability to reach nearly any strategically significant target inside Russia, carrying enough explosives to destroy critical infrastructure, including factories, buildings, and airfields, along with the aircraft stationed there.
Autonomous navigation has become an indispensable feature of long-range-strike drones, as flying long distances into enemy territory requires overcoming the enemy’s air defense and a 60 km-wide strip of EW systems along the border. While official sources in Ukraine refuse to comment on the technology they use, an industry representative revealed in an interview with CSIS that some of these advanced drones leverage basic AI technology for navigation and antijamming capabilities. An onboard computer allows the drones to navigate in EW environments and follow the preplanned flight route, often developed using large amounts of intelligence data collected by Ukraine or shared by allies.