Abstract
Accurate localization of moving sensors is essential for many fields, such as robot navigation and urban mapping. In this paper, we present a framework for GPS-supported visual Simultaneous Localization and Mapping with Bundle Adjustment (BA-SLAM) using a rigorous sensor model in a panoramic camera. The rigorous model does not cause system errors, thus representing an improvement over the widely used ideal sensor model. The proposed SLAM does not require additional restrictions, such as loop closing, or additional sensors, such as expensive inertial measurement units. In this paper, the problems of the ideal sensor model for a panoramic camera are analysed, and a rigorous sensor model is established. GPS data are then introduced for global optimization and georeferencing. Using the rigorous sensor model with the geometric observation equations of BA, a GPS-supported BA-SLAM approach that combines ray observations and GPS observations is then established. Finally, our method is applied to a set of vehicle-borne panoramic images captured from a campus environment, and several ground control points (GCP) are used to check the localization accuracy. The results demonstrated that our method can reach an accuracy of several centimetres.
Highlights
Imagery from mono or stereo cameras has been the main data source for many applied science fields, such as robotics, computer vision and photogrammetry
We study a GPS-supported bundle adjustment (BA)-SimultaneousLocalization And Mapping (SLAM) method in which a 6DoF model is embedded, a rigorous sensor model is applied as the geometric projection model, and GPS data are combined with ray observations as additional restrictions for global optimisation and georeferencing
The effects of GPS on BA-SLAM should be carefully evaluated if too few GPS observations are obtained or there is insufficient accuracy due to multipath effects
Summary
Imagery from mono or stereo cameras has been the main data source for many applied science fields, such as robotics, computer vision and photogrammetry. The applications of SLAM with panoramic cameras should be studied theoretically because they use a different sensor model than mono/stereo cameras. An ideal geometric sensor model of a panoramic camera has one projection centre, and all of the light beams satisfy co-linearity conditions or a pin-hole model and project the real world onto a spherical surface. This is a perspective transformation but is not projected onto a plane as in a mono/stereo camera. Kaess and Dellaert used a multi-camera rig (panoramic camera) for SLAM with an ideal spherical sensor model [8].
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