Accurate localization is a key task in map based autonomous driving. While in many cases high precision differential GPS is used, more and more vision based methods gain popularity to improve positioning in GNSS denied environments and to avoid high costs in high quality GNSS receivers. However, to generate a globally referenced map, satellite based methods are still important, even in vision based mapping algorithms. In this paper we present a method for integrating locally accurate visual odometry obtained from an onboard stereo camera system with satellite observations of a low cost GNSS receiver. To account for a low number of visible satellites we directly incorporate pseudorange measurements for sensor data fusion. Hence, we present a low cost satellite and camera based positioning system and evaluate it for the usage as part of an inner city mapping system.
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Schreiber et al. (2016) studied this question.
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