Hybrid Camera Array-Based UAV Auto-Landing on Moving UGV in GPS-Denied Environment

• Published in: Remote sensing (Basel, Switzerland) Vol. 10; no. 11; p. 1829
• Main Authors: Yang, Tao, Ren, Qiang, Zhang, Fangbing, Xie, Bolin, Ren, Hailei, Li, Jing, Zhang, Yanning
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2018
• Subjects: Algorithms; Arrays; Cameras; Computer simulation; Control algorithms; Control stability; Deep learning; Field of view; Fisheye views; Global positioning systems; GPS; GPS-denied environment; hybrid camera array; Hybrid systems; International conferences; Kalman filters; Landing aids; Lenses; Localization; Methods; Motion compensation; Motion simulation; Motion stability; moving UGV; Nonlinear control; Qualitative analysis; R&D; Remote sensing; Research & development; Sensors; Signal processing; State estimation; UAV autonomous landing; Unmanned aerial vehicles; Unmanned ground vehicles; Vision systems; United States > US; China
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs10111829

With the rapid development of Unmanned Aerial Vehicle (UAV) systems, the autonomous landing of a UAV on a moving Unmanned Ground Vehicle (UGV) has received extensive attention as a key technology. At present, this technology is confronted with such problems as operating in GPS-denied environments, a low accuracy of target location, the poor precision of the relative motion estimation, delayed control responses, slow processing speeds, and poor stability. To address these issues, we present a hybrid camera array-based autonomous landing UAV that can land on a moving UGV in a GPS-denied environment. We first built a UAV autonomous landing system with a hybrid camera array comprising a fisheye lens camera and a stereo camera. Then, we integrated a wide Field of View (FOV) and depth imaging for locating the UGV accurately. In addition, we employed a state estimation algorithm based on motion compensation for establishing the motion state of the ground moving UGV, including its actual motion direction and speed. Thereafter, according to the characteristics of the designed system, we derived a nonlinear controller based on the UGV motion state to ensure that the UGV and UAV maintain the same motion state, which allows autonomous landing. Finally, to evaluate the performance of the proposed system, we carried out a large number of simulations in AirSim and conducted real-world experiments. Through the qualitative and quantitative analyses of the experimental results, as well as the analysis of the time performance, we verified that the autonomous landing performance of the system in the GPS-denied environment is effective and robust.