Skip to main content

Research Repository

Advanced Search

Unmanned aerial vehicle visual simultaneous localization and mapping: a survey.

Tian, Y.; Yue, H.; Yang, B.; Ren, J.

Authors

Y. Tian

H. Yue

B. Yang



Abstract

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.

Citation

TIAN, Y., YUE, H., YANG, B. and REN, J. 2022. Unmanned aerial vehicle visual simultaneous localization and mapping: a survey. Journal of physics: conference series [online], 2278: proceedings of the 6th International conference on machine vision and information technology (CMVIT 2022), 25 February 2022, [virtual event], article number 012006. Available from: https://doi.org/10.1088/1742-6596/2278/1/012006

Presentation Conference Type Conference Paper (published)
Conference Name 6th International conference on machine vision and information technology 2022 (CMVIT 2022)
Acceptance Date May 13, 2022
Online Publication Date Jun 1, 2022
Publication Date Jun 1, 2022
Deposit Date May 28, 2024
Publicly Available Date May 28, 2024
Journal Journal of physics: conference series
Print ISSN 1742-6588
Electronic ISSN 1742-6596
Publisher IOP Publishing
Peer Reviewed Peer Reviewed
Volume 2278
Article Number 012006
DOI https://doi.org/10.1088/1742-6596/2278/1/012006
Keywords Robotics; Vision applications; Path planning; Unmanned aerial vehicles
Public URL https://rgu-repository.worktribe.com/output/2058623

Files




You might also like



Downloadable Citations