Aleatoric and Epistemic Uncertainty Reduction for Vision-Based Landing System for Fixed-Wing Aircraft: VLS-FWA - Dheeraj Bharti; K. S. Venkatesh (IEEE Access)
Visual information plays a crucial role during the final approach and landing phases of an aircraft, serving as a complementary source for the navigation system. It provides additional guidance when radio navigation such as Instrument Landing System is unserviceable or compromised and enables a fully vision-based landing. The relative position and orientation of an aircraft can be derived from the features of the runway captured in images. However, conventional methods for detecting runways often suffer from high latency and low accuracy, making them inadequate and uncertain for ensuring a safe landing. In response to these limitations, this paper introduces a real-time runway detection model named Vision-based Landing System for Fixed-Winged Aircraft (VLS-FWA), which leverages deep convolutional neural networks in cascade. Moreover, predicted variance is also calculated and displayed in the pilot’s Head-Up Display (HUD) by employing methods to aid in the reduction of aleatoric and epistemic uncertainty in both real-world and synthetic scenes.