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Multi-UAV collaborative system with a feature fast matching algorithm

Multi-UAV collaborative system with a feature fast matching algorithm

作     者:Tian-miao WANG Yi-cheng ZHANG Jian-hong LIANG Yang CHEN Chao-lei WANG Tian-miao WANG;Yi-cheng ZHANG;Jian-hong LIANG;Yang CHEN;Chao-lei WANG

作者机构:School of Mechanical Engineering&AutomationBeihang UniversityBeijing 100191China School of Physics and Mechatronics EngineeringLongyan UniversityLongyan 364000China State Key Laboratory of Intelligent Manufacturing System TechnologyBeijing Institute of Electronic System EngineeringBeijing 100040China 

出 版 物:《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿(英文版))

年 卷 期:2020年第21卷第12期

页      面:1695-1712页

核心收录:

学科分类:081104[工学-模式识别与智能系统] 08[工学] 082503[工学-航空宇航制造工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

主  题:Multiple UAVs Collaboration Simultaneous localization and mapping(SLAM) Feature description and matching 

摘      要:We present a real-time monocular simultaneous localization and mapping(SLAM)system with a new distributed structure for multi-UAV collaboration *** system is different from other general SLAM systems in two aspects:First,it does not aim to build a global map,but to estimate the latest relative position between nearby vehicles;Second,there is no centralized structure in the proposed system,and each vehicle owns an individual metric map and an ego-motion estimator to obtain the relative position between its own map and the neighboring vehicles .To realize the above characteristics in real time,we demonstrate an innovative feature description and matching algorithm to avoid catastrophic expansion of feature point matching workload due to the increased number of *** on the hash and principal component analysis,the matching time complexity of this algorithm can be reduced from 0(logN)to 0(1).To evaluate the performance,the algorithm is verified on the acknowledged multi-view stereo benchmark dataset,and excellent results are ***,through the simulation and real flight experiments,this improved SLAM system with the proposed algorithm is validated.

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