학술논문

Mobile robot localization using panoramic vision and combinations of feature region detectors
Document Type
Conference
Source
2008 IEEE International Conference on Robotics and Automation Robotics and Automation, 2008. ICRA 2008. IEEE International Conference on. :538-543 May, 2008
Subject
Robotics and Control Systems
Computing and Processing
Signal Processing and Analysis
Mobile robots
Computer vision
Detectors
Robot kinematics
Robot localization
Feature extraction
Fingerprint recognition
Robotics and automation
USA Councils
Image databases
Affine Regions Detectors
Harris Affine
Hessian Affine
MSER
SIFT
GLOH
Topological Localization
Language
ISSN
1050-4729
Abstract
This paper presents a vision-based approach for mobile robot localization. The environmental model is topological. The new approach uses a constellation of different types of affine covariant regions to characterize a place. This type of representation permits a reliable and distinctive environment modeling. The performance of the proposed approach is evaluated using a database of panoramic images from different rooms. Additionally, we compare different combinations of complementary feature region detectors to find the one that achieves the best results. Our experimental results show promising results for this new localization method. Additionally, similarly to what happens with single detectors, different combinations exhibit different strengths and weaknesses depending on the situation, suggesting that a context-aware method to combine the different detectors would improve the localization results.