Title :
Autonomous visual self-localization in completely unknown environment
Author :
Sadeghi-Tehran, Pouria ; Behera, Sasmita ; Angelov, Plamen ; Andreu, Javier
Author_Institution :
InfoLab21, Lancaster Univ., Lancaster, UK
Abstract :
In this paper, a novel approach to visual self-localization in an unknown environment is presented. The proposed method makes possible the recognition of new landmark without using GPS or any other communication links or pre-training. An image-based self-localization technique is used to automatically label landmarks that are detected in real-time using a computationally efficient and recursive algorithm. Real-time experiments are carried in outdoor environment at Lancaster University using a real mobile robot Pioneer 3DX in order to build a map the local environment without using any communication links. The presented experimental results in real situations show the effectiveness of the proposed method.
Keywords :
image recognition; mobile robots; robot vision; Pioneer 3DX mobile robot; autonomous visual self-localization; image-based self-localization technique; landmark labeling; landmark recognition; local environment mapping; recursive algorithm; Fires; Global Positioning System; Humans; KDE; KDE Cauchy Kernel; autonomous navigation; mobile robot; visual-based landmarks;
Conference_Titel :
Evolving and Adaptive Intelligent Systems (EAIS), 2012 IEEE Conference on
Conference_Location :
Madrid
Print_ISBN :
978-1-4673-1728-3
Electronic_ISBN :
978-1-4673-1726-9
DOI :
10.1109/EAIS.2012.6232811