Leveraging edge detection and neural networks for better UAV localization

arXiv:2404.06207v1 Announce Type: new
Abstract: We propose a novel method for geolocalizing Unmanned Aerial Vehicles (UAVs) in environments lacking Global Navigation Satellite Systems (GNSS). Current state-of-the-art techniques employ an offline-trained encoder to generate a vector representation (embedding) of the UAV's current view, which is then compared with pre-computed embeddings of geo-referenced images to determine the UAV's position. Here, we demonstrate that the performance of these methods can be significantly enhanced by preprocessing the images to extract their edges, which exhibit …

abstract aerial art arxiv cs.cv current detection edge embedding embeddings encoder environments generate global localization navigation networks neural networks novel offline representation satellite state systems type unmanned aerial vehicles vector vehicles view