Unmanned aerial vehicle visual Simultaneous Localization and Mapping: a survey

Y Tian, H Yue, B Yang, J Ren

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)
12 Downloads (Pure)


Simultaneous Localization and Mapping (SLAM) has been widely applied in robotics and other vision applications, such as navigation and path planning for unmanned aerial vehicles (UAVs). UAV navigation can be regarded as the process of robot planning to reach the target location safely and quickly. In order to complete the predetermined task, the drone must fully understand its state, including position, navigation speed, heading, starting point, and target position. With the rapid development of computer vision technology, vision-based navigation has become a powerful tool for autonomous navigation. A visual sensor can provide a wealth of online environmental information, has high sensitivity, strong anti-interference ability, and is suitable for perceiving dynamic environments. Most visual sensors are passive sensors, which prevent sensing systems from being detected. Compared with traditional sensors such as global positioning system (GPS), laser lightning, and ultrasonic sensors, visual SLAM can obtain rich visual information such as color, texture and depth. In this paper, a survey is provided on the development of relevant techniques of visual SLAM, visual odometry, image stabilization and image denoising with applications to UAVs. By analyzing the existing development, some future perspectives are briefed.
Original languageEnglish
Article number012006
Number of pages6
JournalJournal of Physics: Conference Series
Publication statusPublished - 2 Jun 2022
EventThe 6th International Conference on Machine Vision and Information Technology - Haikou, Haikou, China
Duration: 24 Feb 202226 Feb 2022
Conference number: 6


  • Simultaneous Localization and Mapping
  • unmanned aerial vehicles
  • autonomous navigation


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