Monocular visual estimation for autonomous aircraft landing guidance in unknown structured scenes
Peer-Reviewed Publication
Updates every hour. Last Updated: 17-Jul-2025 21:11 ET (18-Jul-2025 01:11 GMT/UTC)
The flourishing development of the ‘low-altitude economy’ has not only enriched the aircraft industry but also expanded the application prospects of aircraft. However, this growth has also raised higher demands for the safety and intelligence levels of these aircraft. In emergency situations involving mechanical failures, adverse weather conditions, or strong interference, it is crucial for aircraft to autonomously select a suitable landing region and land safely. This can maximize the safety of both the aircraft and its occupants while minimizing economic losses. However, there is a lack of effective technical solutions for autonomous landing guidance under emergency conditions. This research focuses on this application and proposes a new monocular vision-based measurement method for autonomous aircraft landing guidance in unknown structured environments. The method enables the aircraft to autonomously select a suitable landing region and accurately measure the relative 6D pose (3D rotation and 3D translation) between the aircraft and the landing region, providing a reliable foundation for autonomous landing guidance.
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