Visual SLAM of unmanned aerial vehicle: a survey

Yikun Tian, Binchao Yang, Hong Yue, Jinchang Ren

Research output: Contribution to conferencePosterpeer-review

5 Downloads (Pure)


We summarize the research on UAV based path planning using SLAM with environmental perception and understanding. Simultaneous Localization and Mapping (SLAM) aims to realize environmental perception and understanding in an unfamiliar environment to complete self positioning and path planning of robotics. Localization and mapping are the basic needs of humans and mobile devices, where humans can perceive their movements and the environments through multimodal sensing, relying on the awareness of the location to navigate in a complex three dimensional space.

A complete SLAM system consists of four parts (i) the front end tracking, tracking, (ii) the back end optimization, optimization, (iii) the loop detection, and (iv) the map reconstruction, where visual odometry is one of the challenging and open topics in the vSLAM system for determining the position and orientation of robots by analyzing the captured images from the associated cameras.

There are a huge number of applications with various sensing equipment, single or binocular cameras based on SLAM. Benefiting from new visual sensing equipment, powerful data processing and high flexibility, SLAM can now be implemented in a simpler and low cost system structure.
Original languageEnglish
Publication statusPublished - 24 Feb 2022
EventThe 6th International Conference on Machine Vision and Information Technology - Haikou, Haikou, China
Duration: 24 Feb 202226 Feb 2022
Conference number: 6


ConferenceThe 6th International Conference on Machine Vision and Information Technology
Abbreviated titleCMVIT2022
Internet address


  • Unmanned Aerial Vehicle (UAV)
  • drones
  • simultaneous localization and mapping (SLAM) problem
  • vSLAM


Dive into the research topics of 'Visual SLAM of unmanned aerial vehicle: a survey'. Together they form a unique fingerprint.

Cite this