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Research on visual autonomous navigation indoor for unmanned aerial vehicle

  • Yang Zhang (张 洋)
  • Qiang Lü (吕 强)
  • Huican Lin (林辉灿)
  • Jianye Ma (马建业)
Article
  • 120 Downloads

Abstract

The aim of this paper is to study visual autonomous navigation of unmanned aerial vehicle (UAV) in indoor global positioning system (GPS) denied environment. The UAV platform of the autonomous navigation flight control system is designed and built. The principle of visual localization and mapping algorithm is studied. According to the characteristics of UAV platform, the visual localization is designed and improved. Experimental results demonstrate that the UAV platform can realize the tasks of autonomous localization, navigation and mapping based on visual in unknown environments.

Key words

unmanned aerial vehicle (UAV) visual localization autonomous navigation robot operating system 

CLC number

TP 242 

Document code

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References

  1. [1]
    CHEN X L, TANG Q, CHE J, et al. Localization and control of quadrotor aircraft based on indoor vision [J]. Ordnance Industry Automation, 2012, 31(5): 61–64 (in Chinese).Google Scholar
  2. [2]
    KRAJNíK T, VONášEK V, FISER D, et al. ARdrone as a platform for robotic research and education [C]//Research and Education in Robotics-EUROBOT 2011. Berlin: Springer, 2011: 172–186.CrossRefGoogle Scholar
  3. [3]
    ENGEL J, STURM J, CREMERS D. Camera-based navigation of a low-cost quadrocopter [C]//2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). [s.l.]: IEEE, 2012: 2815–2821.CrossRefGoogle Scholar
  4. [4]
    FORSTER C, PIZZOLI M, SCARAMUZZA D. SVO: Fast semi-direct monocular visual odometry [C]//2014 IEEE International Conference on Robotics and Automation (ICRA). [s.l.]: IEEE, 2014: 15–22CrossRefGoogle Scholar
  5. [5]
    ZHANG J W, ZHANG L W, YING H, et al. Open source robot operating system: ROS [M]. Beijing: Science Press, 2012: 128–139 (in Chinese).Google Scholar
  6. [6]
    MUR-ARTAL R, MONTIEL J M M, TARDOS J D. ORB-SLAM: A versatile and accurate monocular SLAM system [J]. IEEE Transactions on Robotics, 2015, 31(5): 1147–1163.CrossRefGoogle Scholar
  7. [7]
    HARTLEY R, ZISSERMAN A. Multiple view geometry in computer vision [M]. London: Cambridge University Press, 2003.MATHGoogle Scholar
  8. [8]
    NèGRE A, PRADALIER C, DUNBABIN M. Robust vision-based underwater homing using selfsimilar landmarks [J]. Journal of Field Robotics, 2008, 25(6/7): 360–377.CrossRefMATHGoogle Scholar
  9. [9]
    KüMMERLE R, GRISETTI G, STRASDAT H, et al. g2o: A general framework for graph optimization [C]//2011 IEEE International Conference on Robotics and Automation (ICRA). [s.l.]: IEEE, 2011: 3607–3613.CrossRefGoogle Scholar

Copyright information

© Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Yang Zhang (张 洋)
    • 1
  • Qiang Lü (吕 强)
    • 1
  • Huican Lin (林辉灿)
    • 1
  • Jianye Ma (马建业)
    • 1
  1. 1.Department of Control EngineeringAcademy of Armored Forces EngineeringBeijingChina

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