Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
ROBIO '09 Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics
Localization methods for a mobile robot in urban environments
IEEE Transactions on Robotics
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Intelligent vehicles require accurate localization relative to a map to ensure safe travel. GPS sensors are among the most useful sensors for outdoor localization, but they still suffer from noise due to weather conditions, tree cover, and surrounding buildings or other structures. In this paper, to improve localization accuracy when GPS fails, we propose a sequential state estimation method that fuses data from a GPS device, an electronic compass, a video camera, and wheel encoders using a particle filter. We process images from the camera using a color histogram-based method to identify the road and non-road regions in the field of view in front of the vehicle. In two experiments, in simulation and on a real vehicle, we demonstrate that, compared to a standard extended Kalman filter not using image data, our method significantly improves lateral localization error during periods of GPS inaccuracy.