A Vision-Based Autonomous Landing Guidance Strategy for a Micro-UAV by the Modified Camera View

Author:

Mu Lingxia1,Li Qingliang1,Wang Ban2ORCID,Zhang Youmin3ORCID,Feng Nan4,Xue Xianghong1,Sun Wenzhe1

Affiliation:

1. Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an University of Technology, Xi’an 710048, China

2. School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, China

3. Department of Mechanical, Industrial & Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, Canada

4. School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing 100083, China

Abstract

Autonomous landing is one of the key technologies for unmanned aerial vehicles (UAVs) which can improve task flexibility in various fields. In this paper, a vision-based autonomous landing strategy is proposed for a quadrotor micro-UAV based on a novel camera view angle conversion method, fast landing marker detection, and an autonomous guidance approach. The front-view camera of the micro-UAV video is first modified by a new strategy to obtain a top-down view. By this means, the landing marker can be captured by the onboard camera of the micro-UAV and is then detected by the YOLOv5 algorithm in real time. The central coordinate of the landing marker is estimated and used to generate the guidance commands for the flight controller. After that, the guidance commands are sent by the ground station to perform the landing task of the UAV. Finally, the flight experiments using DJI Tello UAV are conducted outdoors and indoors, respectively. The original UAV platform is modified using the proposed camera view angle-changing strategy so that the top-down view can be achieved for performing the landing mission. The experimental results show that the proposed landing marker detection algorithm and landing guidance strategy can complete the autonomous landing task of the micro-UAV efficiently.

Funder

National Natural Science Foundation of China

Young Talent Fund of University Association for Science and Technology in Shaanxi

Industry-University-Research Innovation Foundation for the Chinese Ministry of Education

China Postdoctoral Science Foundation

Natural Sciences and Engineering Research Council of Canada

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering

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