Monocular Vision for Mobile Robot Localization and Autonomous Navigation
International Journal of Computer Vision
3D Visual Odometry for Road Vehicles
Journal of Intelligent and Robotic Systems
Parametric correspondence and chamfer matching: two new techniques for image matching
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Real-time monocular visual odometry for on-road vehicles with 1-point RANSAC
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Efficient off-road localization using visually corrected odometry
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Appearance-Guided Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles
IEEE Transactions on Robotics
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This paper proposes a method for long-range vehicle localization using fusion of omnidirectional camera and Global Positioning System (GPS) in wide urban environments. The main contributions are twofold: first, the positions estimated by visual sensor overcome the motion blur effects. The motion constrains of successive frames are obtained accurately under various scene structures and conditions. Second, the cumulative errors of visual odometry system are solved completely based on the fusion of local (visual odometry) and global positioning system. The visual odometry can yield the correct local position at short distance of movements but it will accumulate errors overtime, on the contrary, the GPS can yields the correct global positions but the local positions may be drifted. Moreover, the signals received from satellites are affected by multi-path and forward diffraction then the position errors increase when vehicles move in dense building regions or jump/miss in tunnels. To utilize the advantages of two sensors, the position information should be evaluated before fusion by Extended Kalman Filter (EKF) framework. This multiple sensor system can also compensate each other in the case of losing one of two. The simulation results demonstrate the accuracy of vehicle positions in long-range movements.