Cognitive Terrain Flight Assistance

Fast and low-altitude flight capability is essential for helicopters, particularly when evading traditional air defense systems based on ground radar. Flight speeds that reach or exceed 100 knots at altitudes below 100 feet are difficult for radar systems to detect and are often used by helicopter pilots for this purpose. Recent advances in vehicle autonomy for Uncrewed Aerial Vehicles (UAVs) now suggest the potential for semi-autonomous flight at much higher speeds—up to 200 knots or more—at altitudes significantly lower than 100 feet, potentially as low as 20 feet above ground level (AGL). Such performance would be incredibly challenging, if not impossible, for a human pilot to achieve under normal conditions, especially in visually degraded environments such as smoke, fog, dust, low light, or direct sunlight. However, a vehicle capable of maintaining 200 mph at just 20 feet AGL while autonomously avoiding obstacles would be nearly impossible to target using conventional air defense systems. This capability would make attack, cargo, and personnel carrier helicopters vastly more effective in future battlefields where UAVs, counter-UAV systems, and traditional radar-based defenses are all in play. We propose developing a cognitive terrain flight assistance system for helicopter pilots to meet this operational need. This system will utilize reinforcement learning (RL) within simulation environments that feature high-fidelity digital replicas of terrain generated from satellite, aerial, and ground imagery. The primary sensing modalities will be onboard cameras and inertial measurement units (IMUs). However, when available, the system can also integrate data from off-the-shelf active sensors such as LiDAR or RADAR. Critically, the system will operate without reliance on GPS, enabling long-range, autonomous navigation using only onboard sensors. In Phase I, Tycho AI will capture high-fidelity terrain (?15 km x 15 km, varied relief) designated by the government and integrate it into a simulation environment for cognitive learning preparation. This forms the foundation for Phase II and transition to the Army MAS 6.3 program.