An Improved Vision-Based Algorithm for Unmanned Aerial Vehicles Autonomous Landing

被引：9
|
作者：
Zhao, Yunji [1 ]
Pei, Hailong [1 ]
机构：
[1] S China Univ Technol, Coll Automat Sci & Engn, Guangzhou 510641, Guangdong, Peoples R China
来源：
2012 INTERNATIONAL CONFERENCE ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING (ICMPBE2012) | 2012年 / 33卷
关键词：
autonomous landing; camshaft; color histogram; SURF;
D O I：
10.1016/j.phpro.2012.05.157
中图分类号：
Q6 [生物物理学];
学科分类号：
071011 ;
摘要：
In vision-based autonomous landing system of UAV, the efficiency of target detecting and tracking will directly affect the control system. The improved algorithm of SURF(Speed Up Robust Features) will resolve the problem which is the inefficiency of the SURF algorithm in the autonomous landing system. The improved algorithm is composed of three steps: first, detect the region of the target using the Camshift; second, detect the feature points in the region of the above acquired using the SURF algorithm; third, do the matching between the template target and the region of target in frame. The results of experiment and theoretical analysis testify the efficiency of the algorithm. (C) 2012 Published by Elsevier B.V. Selection and/or peer review under resposibility of ICMPBE International Committee
引用
收藏
页码：935 / 941
页数：7
相关论文
共 50 条
  • [1] An Improved Vision-Based Algorithm for Unmanned Aerial Vehicles Autonomous Landing
    Zhao, Yunji
    Pei, Hailong
    Wang, Shidi
    2010 INTERNATIONAL COLLOQUIUM ON COMPUTING, COMMUNICATION, CONTROL, AND MANAGEMENT (CCCM2010), VOL II, 2010, : 84 - 87
  • [2] Vision-based Autonomous Landing of Unmanned Aerial Vehicles
    Hu Jiaxin
    Guo Yanning
    Feng Zhen
    Guo Yuqing
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 3464 - 3469
  • [3] A vision-based system for autonomous vertical landing of unmanned aerial vehicles
    Wubben, Jamie
    Fabra, Francisco
    Calafate, Carlos T.
    Krzeszowski, Tomasz
    Marquez-Barja, Johann M.
    Cano, Juan-Carlos
    Manzoni, Pietro
    2019 IEEE/ACM 23RD INTERNATIONAL SYMPOSIUM ON DISTRIBUTED SIMULATION AND REAL TIME APPLICATIONS (DS-RT), 2019, : 188 - 194
  • [4] A hierarchical vision-based localization of rotor unmanned aerial vehicles for autonomous landing
    Yuan, Haiwen
    Xiao, Changshi
    Xiu, Supu
    Zhan, Wenqiang
    Ye, Zhenyi
    Zhang, Fan
    Zhou, Chunhui
    Wen, Yuanqiao
    Li, Qiliang
    INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2018, 14 (09):
  • [5] Vision-Based Autonomous Landing for Unmanned Aerial and Ground Vehicles Cooperative Systems
    Niu, Guanchong
    Yang, Qingkai
    Gao, Yunfan
    Pun, Man-On
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (03) : 6234 - 6241
  • [6] Vision-based autonomous landing of an unmanned aerial vehicle
    Saripalli, S
    Montgomery, JF
    Sukhatme, GS
    2002 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS I-IV, PROCEEDINGS, 2002, : 2799 - 2804
  • [7] Vision-based algorithm for autonomous aerial landing
    Morando, A. E. S.
    Santos, M. Ferreira
    Castillo, P.
    Correa-Victorino, A.
    2024 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS, ICUAS, 2024, : 652 - 657
  • [8] Vision-based Autonomous Landing for Rotorcraft Unmanned Aerial Vehicle
    Bu, Chaovan
    Ai, Yunfeng
    Du, Huajun
    2016 IEEE INTERNATIONAL CONFERENCE ON VEHICULAR ELECTRONICS AND SAFETY (ICVES), 2016, : 77 - 82
  • [9] Autonomous Vision-Based Aerial Grasping for Rotorcraft Unmanned Aerial Vehicles
    Lin, Lishan
    Yang, Yuji
    Cheng, Hui
    Chen, Xuechen
    SENSORS, 2019, 19 (15)
  • [10] Vision-Based Autonomous Object Tracking for Unmanned Aerial Vehicles
    Apon, Mateusz
    Nikonowicz, Arkadiusz
    Ambroziak, Leszek
    Kondratiuk, Miroslaw
    Burzynski, Piotr
    Kuczynski, Adam
    MECHATRONICS SYSTEMS AND MATERIALS 2018, 2018, 2029
12345