The Autonomous Navigation System empowers the HORNET UGV and other unmanned vehicles to navigate harsh environments using neural networks and machine learning for terrain segmentation and object recognition. By fusing sensor data from cameras, LiDAR, IMU, and SLAM technology, the system provides waypoint-based driving with real-time obstacle avoidance and route re-planning, even in GNSS-denied areas. It adjusts routes dynamically and reacts to unexpected situations without requiring prior terrain mapping, ensuring reliability in challenging conditions.

Model training takes place in a virtual environment, leveraging digital twin of the UGV alongside realistic simulations of physics and sensor data to prepare for unpredictable scenarios. A user-friendly Ground Control Station (GCS) enables reliable path planning and integration with other drone units, including UGVs and UAVs, offering a versatile solution for autonomous navigation and seamless coordination across multiple platforms.

LPP concurrently develops a similar autonomous system for UAVs, utilizing visual navigation and optical tracking to ensure jamming-proof operation.