A Novel Vehicle Localization System Using Vision Module for Heading Feedback

Traditional vehicle localization systems use GNSS signals for global localization or Lidar or vision based systems for Simultaneous Mapping and Localization (SLAM). However, the signals of GNSS might be contaminated or even blocked in areas where there are tall buildings or trees, especially for autonomous sweeper vehicles that usually work along the road. There are additional information that can be used to improve the accuracy and robustness of vehicle localization system when applied in autonomous sweeper vehicles. Thus, a novel vehicle localization system based on GNSS, vision, wheel speed and Inertial Measurement Unit (IMU) is proposed. When the vehicle works in areas where GNSS signals are good, accurate position information from GNSS is used. Besides, wheel speed and IMU information is fused to improve the output rate of position information. When the vehicle enters areas where GNSS signals are unavailable, the heading information from vision is used as measurement to estimate the heading angle of vehicle and then fused with wheel speed and IMU to estimate the position. Real vehicle experiments are conducted to validate the effectiveness of the proposed system.