Abstract
Low-cost Global Navigation Satellite System (GNSS) receivers and monocular cameras are widely used in daily activities. The complementary nature of these two devices is ideal for outdoor navigation. In this paper, we investigate the integration of GNSS and monocular camera measurements in a simultaneous localization and mapping system. The proposed system first aligns the coordinates between two sensors. Subsequently, the measurements are fused by an optimization-based scheme. Our system can function in real-time and obtain the absolute position, scale, and attitude of the vehicle. It achieves a high accuracy without a preset map and also has the capability to work with a preset map. The system can easily be extended to create other forms of maps or for other types of cameras. Experimental results on a popular public dataset are presented to validate the performance of the proposed system.
Highlights
Localization of a device in an unknown environment is critical in many fields
ORB-SLAM system, we propose big bundle adjustment and global BA threads to utilize
For the Global Navigation Satellite System (GNSS) and visual information fusion, to improve the performance of a system running on low-cost devices, we present an optimization-based scheme
Summary
Navigation Satellite System (GNSS) receivers and visual simultaneous localization and mapping (visual-SLAM) systems are popular navigation solutions. In the simplest SLAM systems, a monocular camera is used to determine the ego-motion and build a map. This system does not rely on any external equipment and can work effectively in GNSS-denied environments. With recent SLAM approaches [1,2,3], very high localization and mapping accuracy can be obtained for a medium-length trajectory. SLAM systems are often used in autonomous navigation [4], path planning [5], environment reconstruction [6], scene understanding [7], and so on
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