Swarm Intelligence UAV Project

Swarm Intelligence UAV (Unmanned Aerial Vehicle) systems are advanced autonomous systems capable of autonomous navigation, adapting to environmental conditions, making decisions, and collectively executing missions as a swarm. These systems successfully perform advanced functions such as real-time object detection, classification, recognition, and tracking through deep learning-based computer vision techniques.

Thanks to the developed proprietary swarm intelligence software, UAVs within the swarm can navigate without colliding with each other, be divided according to mission or payload type, and perform area scanning. It is possible to add or remove UAVs from the swarm system in real time.

With its ability for inter-swarm task sharing and target-specific task allocation, the swarm intelligence can autonomously assign different types of UAVs to different target groups. For example, depending on whether the target is a human or a vehicle, the appropriate UAV with the right type of munition is selected autonomously within the swarm.

The swarm system can include different types of UAVs tailored to the mission, thus enhancing mission success. Within the framework of the saturation attack concept, the swarm system allows a large number of UAVs to be used simultaneously and in coordination in target areas.

To enhance the operational resilience of Swarm Drone Operation against electronic warfare threats, KARGU platforms have been integrated with anti-jam technology and KERKES (GNSS denied navigation) system. These integrations provide robust resistance against GPS jamming and spoofing attempts. In environments where GNSS signals are degraded or completely unavailable, swarm autonomy is preserved, and navigation and mission execution continue seamlessly.

These capabilities are integrated into our company’s proprietary algorithms, software, and platforms and have been successfully transformed into operational advantages.

Capabilities

• Swarm Intelligence Algorithms
• Saturation Attack Concept
• Distributed Control Architecture
• Robust Inter-Swarm Communication Infrastructure
• Autonomous formation control
• Collision avoidance
• Real-time target detection and classification
• Task allocation based on payload type
• Target prioritization and task assignment
• CRPA enhanced navigation
• GNSS denied navigation with KERKES integration
• Swarm division and reunion
• Real-time swarm attachment/detachment