Qingliang Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Qingliang Li has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Ban Wang
School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China; National Key Laboratory of Aircraft Configuration Design, Xi'an 710072, China
1 shared publication - Lingxia Mu
Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xian University of Technology, Xian, China
1 shared publication - Nan Feng
School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing, China
1 shared publication - Wenzhe Sun
Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an University of Technology, Xi’an 710048, China
1 shared publication - Xianghong Xue
Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an University of Technology, Xi’an 710048, China
1 shared publication - Youmin Zhang
Concordia University
1 shared publication
Latest Publications
- Open Access
A Vision-Based Autonomous Landing Guidance Strategy for a Micro-UAV by the Modified Camera View
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.
Open AccessA Vision-Based Autonomous Landing Guidance Strategy for a Micro-UAV by the Modified Camera View
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.