Vision-Based UAV Landing with Guaranteed Reliability in Adverse Environment

Author:

Ge Zijian1,Jiang Jingjing1ORCID,Pugh Ewan2,Marshall Ben1ORCID,Yan Yunda3ORCID,Sun Liang4ORCID

Affiliation:

1. Department of Aeronautical and Automotive Engineering, Loughborough University, Leicester LE11 3TU, UK

2. Fuel and Landing Gear Flight Test Analysis, Airbus Operations Limited, Bristol BS34 7PA, UK

3. School of Engineering and Sustainable Development, De Montfort University, Leicester LE1 9BH, UK

4. School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing 100081, China

Abstract

Safe and accurate landing is crucial for Unmanned Aerial Vehicles (UAVs). However, it is a challenging task, especially when the altitude of the landing target is different from the ground and when the UAV is working in adverse environments, such as coasts where winds are usually strong and changing rapidly. UAVs controlled by traditional landing algorithms are unable to deal with sudden large disturbances, such as gusts, during the landing process. In this paper, a reliable vision-based landing strategy is proposed for UAV autonomous landing on a multi-level platform mounted on an Unmanned Ground Vehicle (UGV). With the proposed landing strategy, visual detection can be retrieved even with strong gusts and the UAV is able to achieve robust landing accuracy in a challenging platform with complex ground effects. The effectiveness of the landing algorithm is verified through real-world flight tests. Experimental results in farm fields demonstrate the proposed method’s accuracy and robustness to external disturbances (e.g., wind gusts).

Funder

Innovate UK

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A fast, lightweight deep learning vision pipeline for autonomous UAV landing support with added robustness;Engineering Applications of Artificial Intelligence;2024-05

2. Vision Based Landing Pad Detection for Autonomous Landing of Quadcopter;2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS);2024-04-18

3. A Novel Approach to Docking System for Autonomous Unmanned Aerial Vehicles;Lecture Notes in Networks and Systems;2024

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