基于双目摄像机的车道定位与导航技术研究

Dunyang Geng, Changsheng Ai, Lei Zheng, Zhengguang Qi, Zhiquan Feng, Jiebing Yan
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引用次数: 0

摘要

针对传统AGV单传感器不能满足室内外工况以及多传感器成本过高的问题,研究了一种基于双目摄像头的车道检测定位导航方法。在分析车道线方程系数变化的基础上,对几种动态滤波降噪方法进行了比较。结果表明,基于特征的车道线检测方法可以在多场景下准确提取车道线。卡尔曼滤波方法的方差比其他滤波方法至少小一个数量级,可以有效地提高系统的稳定性。根据车道线方程,得到了相对稳定的车身姿态偏差。提取的横摆角小于1度,横向偏差小于4 cm,为AGV车辆控制提供了依据
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Lane Location and Navigation Technology Based on Binocular Camera
Aiming at the problem that the traditional single sensor of AGV cannot meet the indoor and outdoor operating conditions and the cost of multi-sensor is too high, this paper studies a navigation method for lane detection and positioning based on binocular camera. Based on the analysis of lane line equation coefficient variation, several dynamic filtering noise reduction methods are compared. The results show that the lane line detection method based on feature can accurately extract the lane line in multi-scenario. The variance of Kalman filter method is at least one order of magnitude lower than that of other filtering methods, which can effectively improve the stability of the system. According to the lane line equation, a relatively stable body posture deviation is obtained. The extracted yaw angle is less than 1 degree and the lateral deviation is less than 4 cm, which provides a basis for AGV vehicle control
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