Volume IV-2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 145-152, 2018
https://doi.org/10.5194/isprs-annals-IV-2-145-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 145-152, 2018
https://doi.org/10.5194/isprs-annals-IV-2-145-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  28 May 2018

28 May 2018

LOCALIZATION AND MAPPING USING A NON-CENTRAL CATADIOPTRIC CAMERA SYSTEM

M. Khurana and C. Armenakis M. Khurana and C. Armenakis
  • Geomatics Engineering, GeoICT Lab Department of Earth and Space Science and Engineering Lassonde School of Engineering, York University, Toronto, Canada

Keywords: Catadioptric cameras, robotic mapping, localization, mapping

Abstract. This work details the development of an indoor navigation and mapping system using a non-central catadioptric omnidirectional camera and its implementation for mobile applications. Omnidirectional catadioptric cameras find their use in navigation and mapping of robotic platforms, owing to their wide field of view. Having a wider field of view, or rather a potential 360° field of view, allows the system to “see and move” more freely in the navigation space. A catadioptric camera system is a low cost system which consists of a mirror and a camera. Any perspective camera can be used. A platform was constructed in order to combine the mirror and a camera to build a catadioptric system. A calibration method was developed in order to obtain the relative position and orientation between the two components so that they can be considered as one monolithic system. The mathematical model for localizing the system was determined using conditions based on the reflective properties of the mirror. The obtained platform positions were then used to map the environment using epipolar geometry. Experiments were performed to test the mathematical models and the achieved location and mapping accuracies of the system. An iterative process of positioning and mapping was applied to determine object coordinates of an indoor environment while navigating the mobile platform. Camera localization and 3D coordinates of object points obtained decimetre level accuracies.