A monocular visual measurement system for UAV probe-and-drogue autonomous aerial refueling
为 UAV probe-and-drogue 的一个单眼用的视觉测量系统自治天线 refueling作者机构:School of Automation Science and Electrical EngineeringBeijing University of Aeronautics and AstronauticsBeijingChina School of Aerospace EngineeringXiamen UniversityXiamenChina
出 版 物:《International Journal of Intelligent Computing and Cybernetics》 (智能计算与控制论国际期刊(英文))
年 卷 期:2018年第11卷第2期
页 面:166-180页
核心收录:
学科分类:08[工学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:This research is partially supported by National Natural Science Foundation of China under Grant No.61673327 Aeronautical Science Foundation of China under Grant No.20160168001
主 题:Unmanned aerial vehicle(UAV) Autonomous aerial refueling(AAR) Computer vision Pose estimation Random sample consensus(RANSAC)
摘 要:Purpose–The purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling(AAR)for unmanned aerial vehicle,which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time ***/methodology/approach–Methods and techniques for marker detection,feature matching and pose estimation have been designed and implemented in the visual measurement ***–The simple blob detection(SBD)method is adopted,which outperforms the Laplacian of Gaussian *** a novel noise-elimination algorithm is proposed for excluding the noise ***,a novel feature matching algorithm based on perspective transformation is *** experimental results indicated the rapidity and effectiveness of the proposed *** implications–The visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for ***/value–The SBD method is used to detect the features and a novel noise-elimination algorithm is ***,a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.