3D mapping based VSLAM for UAVs

Author

Li, Xiaodong ; Aouf, Nabil ; Nemra, Abdelkrim

Author_Institution

Dept. of Inf. & Syst. Eng., Cranfield Univ., Shrivenham, UK

fYear

2012

fDate

3-6 July 2012

Firstpage

348

Lastpage

352

Abstract

This paper addresses 3D texture mapping in Visual Simultaneous Localization And Mapping (VSLAM) for Unmanned Aerial Vehicle (UAV) applications. Landmark selection strategy based on feature detection methods such as Scale Invariant Feature Transform (SIFT) and Speed Up Robust Features (SURF) is adopted. The selected features are combined with additionally chosen features that are well distributed across the stereo views and refined by RANSAC in order to provide well visualized views for navigation. Experimental results are provided to demonstrate the effectiveness of our 3D mapping strategy.

Keywords

SLAM (robots); aerospace computing; autonomous aerial vehicles; feature extraction; image texture; iterative methods; robot vision; stereo image processing; 3D mapping based VSLAM; 3D texture mapping; RANSAC; SIFT; SURF; UAV; feature detection methods; feature selection; landmark selection strategy; random sample consensus; scale invariant feature transform; speed up robust features; stereo views; unmanned aerial vehicle; visual simultaneous localization and mapping; visualized views; Cameras; Estimation; Feature extraction; Solid modeling; Surface texture; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Control & Automation (MED), 2012 20th Mediterranean Conference on

Conference_Location

Barcelona

Print_ISBN

978-1-4673-2530-1

Electronic_ISBN

978-1-4673-2529-5

Type

conf

DOI

10.1109/MED.2012.6265662

Filename

6265662