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Guidance and Navigation for UAV Airborne Docking

Abstract

Unmanned aerial vehicle (UAV) capability is currently limited by the amount of energy that can be stored onboard. Airborne docking, for mid-air refueling, is a viable solution that has been implemented with manned aircraft for decades, but has yet to be achieved with their unmanned counterparts. The prohibitive challenge is the highly accurate and reliable relative positioning performance that is necessary to dock with a small target, in the air, amidst external disturbances. This paper presents a complete solution to airborne docking, which includes vision-aided unscented Kalman filters for leader-relative navigation and docking appendage motion estimation; and guidance that is suitable for all phases of the mission. The work concludes by demonstrating the proposed algorithms in what is thought to be the first UAV airborne docking.

🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning
🧭 Keyword Pioneer — relative navigation
🐣 Hot Topic Early Bird — motion estimation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio