Vision-based pose estimation for indoor navigation of unmanned micro aerial vehicle based on the 3D model of environment

被引：4

作者：

Buyval, Alexander ^{[1
]}

Gavrilenkov, Mikhail ^{[1
]}

机构：

[1] Bryansk State Tech Univ, Dept Comp Sci, Bryansk, Russia

来源：

2015 INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING, AUTOMATION AND CONTROL SYSTEMS (MEACS) | 2015年

关键词：

visual localization of UMAV; particle filter; ROS; Gazebo; VISUAL LOCALIZATION;

D O I：

10.1109/meacs.2015.7414857

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

The main function of unmanned micro aerial vehicle (UMAV) is localization. If the robot knows where it is, it will be able to create a correct route and to complete it task. An indoor environment doesn't allow using GPS/GLONASS sensors on robots. Also other sensors like LIDAR and ultrasonic ranges has its own disadvantages. In this paper we suggest to use monocular camera as main sensor. The image from camera is used to extract edges and then to compare them with edges from known 3D model of environment. To estimate a final hypothesis about robot localization we used a particle filter. Finally, we have developed our localization system as ROS based subsystem and used the Gazebo simulator for testing.

引用

页数：4

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