Abstract
Global Navigation Satellite System (GNSS) provides accurate positioning data for vehicular navigation in open outdoor environment. In an indoor environment, Light Detection and Ranging (LIDAR) Simultaneous Localization and Mapping (SLAM) establishes a two-dimensional map and provides positioning data. However, LIDAR can only provide relative positioning data and it cannot directly provide the latitude and longitude of the current position. As a consequence, GNSS/Inertial Navigation System (INS) integrated navigation could be employed in outdoors, while the indoors part makes use of INS/LIDAR integrated navigation and the corresponding switching navigation will make the indoor and outdoor positioning consistent. In addition, when the vehicle enters the garage, the GNSS signal will be blurred for a while and then disappeared. Ambiguous GNSS satellite signals will lead to the continuous distortion or overall drift of the positioning trajectory in the indoor condition. Therefore, an INS/LIDAR seamless integrated navigation algorithm and a switching algorithm based on vehicle navigation system are designed. According to the experimental data, the positioning accuracy of the INS/LIDAR navigation algorithm in the simulated environmental experiment is 50% higher than that of the Dead Reckoning (DR) algorithm. Besides, the switching algorithm developed based on the INS/LIDAR integrated navigation algorithm can achieve 80% success rate in navigation mode switching.
Highlights
In recent years, various navigation sensors and algorithms have emerged with the vigorous development of navigation technology
Global Navigation Satellite System (GNSS) satellite positioning in the outdoor environment is the best solution for navigation system, but due to the weak penetration of GNSS satellite signals, vehicles cannot receive GNSS satellite signals in the indoor garage
Due to the complex structure of the actual passenger vehicle and the confidentiality of the internal information in the vehicle control system for safety, the odometer information inside the vehicle cannot be required by the public
Summary
Various navigation sensors and algorithms have emerged with the vigorous development of navigation technology. The Gmapping SLAM and Karto SLAM mapping navigation algorithm need to rely on the vehicle position data, which stems from the vehicle odometer in wheels. According to the different applicable environments of vehicles and pedestrians, the application of the INS/LIDAR for indoor navigation and positioning. First of all, this paper combines the outdoor World Geodetic System–1984 Coordinate (WGS-84) geographic coordinate system of the GNSS with the indoor relative coordinate system of the LIDAR to complement the lack of vehicle positioning signals in the garage. The indoor and outdoor navigation switching algorithm is used to solve the problem of GNSS positioning error increased at the entrance of the garage, so that the vehicular navigation and positioning trajectory smoothly transitions [18]. This paper compares the Hector SLAM/INS navigation algorithm based on Kalman filtering with the inertial navigation Dead Reckoning (DR) algorithm to verify the accuracy and robustness of the proposed system
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