摘要
针对室外环境提出了一种基于低精度GPS的视觉导航方法.采用多传感器融合的方法解决道路和路口的导航问题.对于路口环境,通过对道路标志(如人行横道线)的检测,实现路口的初定位;基于全局地图信息,采用扩展卡尔曼滤波融合GPS和里程计信息,进行路口导航.真实环境下的实验结果表明该方法,具有良好的有效性和实时性.
This paper proposed a visual navigation method for outdoor environment based on low accuracy GPS.Outdoor environment consists of intersections and roads.The navigation methods for the neatly-structured environment are not suitable for the environment with intersections.Thus,this paper applies a multi-sensor fusion method to navigation in the road intersections and the common roads＇ situation.For the intersection issues,preliminary location is conducted by intersection detection（such as zebra crossing）.Then,based on world map,an extended Kalman filter（EKF） is used for fusing the GPS and odometer information to position in the intersections.The experimental results in the real situation prove that the method is efficient and can well satisfy the real-time request.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2011年第2期168-172,178,共6页
Journal of Shanghai Jiaotong University
基金
世博科技专项基金(10dz0581100)
教育部博士点基金(20070248097)
关键词
智能车
视觉导航
道路检测
扩展卡尔曼滤波
路口定位
intelligent vehicle
visual navigation
road detection
extended Kalman filter（EKF）
intersection location
