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Monocular Vision Based Localization System using Hybrid Features from Ceiling Images for Robot Navigation in an Indoor Environment

Authors :
Jin-Ho Suh
Young-jin Hong
Seok Won Bang
Jungwon Kang
Christopher G. Atkeson
Myung Jin Chung
Jung-Woo Lee
Source :
The Journal of Korea Robotics Society. 6:197-209
Publication Year :
2011
Publisher :
The Korea Robotics Society, 2011.

Abstract

This paper presents a localization system using ceiling images in a large indoor environment. For a system with low cost and complexity, we propose a single camera based system that utilizes ceiling images acquired from a camera installed to point upwards. For reliable operation, we propose a method using hybrid features which include natural landmarks in a natural scene and artificial landmarks observable in an infrared ray domain. Compared with previous works utilizing only infrared based features, our method reduces the required number of artificial features as we exploit both natural and artificial features. In addition, compared with previous works using only natural scene, our method has an advantage in the convergence speed and robustness as an observation of an artificial feature provides a crucial clue for robot pose estimation. In an experiment with challenging situations in a real environment, our method was performed impressively in terms of the robustness and accuracy. To our knowledge, our method is the first ceiling vision based localization method using features from both visible and infrared rays domains. Our system can be easily utilized with a variety of service robot applications in a large indoor environment.

Details

ISSN :
19756291
Volume :
6
Database :
OpenAIRE
Journal :
The Journal of Korea Robotics Society
Accession number :
edsair.doi...........55f4506a5fea76f7094570a13c1bcc38
Full Text :
https://doi.org/10.7746/jkros.2011.6.3.197