Title | Localization of Mobile Robots Using Odometry and an External Vision Sensor |
Publication Type | Journal Article |
Año de publicación | 2010 |
Autores | Pizarro, D, Mazo, M, Santiso, E, Marron, M, Jimenez, D, Cobreces, S, Losada-Gutiérrez, C |
Idioma de publicación | English |
Journal | Sensors |
Volumen | 10 |
Número | 4 |
Páginas | 3655-3680 |
Fecha de publicación | 04/2010 |
Editorial | MDPI - Open Access Publishing |
Rank in category | 11/58 |
JCR Category | INSTRUMENTS & INSTRUMENTATION |
Palabras clave | artificial vision, Intelligent spaces, robotics |
JCR Impact Factor | 1.821 |
ISSN | 1424-8220 |
URL | http://www.mdpi.com/1424-8220/10/4/3655/ |
DOI | 10.3390/s100403655 |
Abstract | This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields. |
Resumen | This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields. |
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sensors-10-03655.pdf | 3.01 MB |