基于GPS和机器视觉的组合导航定位方法

    Positioning method of integrated navigation based on GPS and machine vision

    • 摘要: 准确、可靠的位置信息是进行农业机械自动导航的前提。该文构建了一个基于GPS和机器视觉的多传感器组合导航定位系统。在此系统中,采用GPS获取导航车的绝对位置信息、航向角度和行驶速度;机器视觉通过图像处理获取导航基准线,并得到代表作物行特征的点;UKF(unscented kalman filter,无迹卡尔曼滤波)滤波器用来对上述传感器获取的信息进行滤波,并以电瓶车为平台,对滤波前后的定位效果进行对比。试验结果表明,使用UKF滤波后的定位精度和稳定性得到了改善,X方向和Y方向标准偏差分别为2.43、0.07 m,定位曲线得到了平滑,克服了使用单一传感器进行定位的弊端,能够满足自动导航系统的要求。

       

      Abstract: Accurate and reliable location information is the basis for the autonomous navigation of off-road vehicle. In this paper, a multi-sensor navigation positioning system, integrated with a RTK-GPS (Trimble AgGPS332/MS750) and a CCD camera (OK AC1310) was constructed. The RTK-GPS was used for obtaining the absolute position data, heading angle and speed of the vehicle; and the calibrated CCD camera was used for obtaining the baseline for navigation through the image processing and the feature points of crop rows. Based on the kinematics model of navigation vehicle, UKF filter was established to filter the information of the two sensors. An electric power vehicle was applied to the platform, and the position effects before and after filtering were compared. Experiments results showed that the standard deviations of X and Y were 2.44 m and 0.07 m separately with smoother location curves and the impact of jump points reduced after filtering by UKF. This multi-sensor navigation positioning system can overcome the disadvantages for using a single sensor and meet the requirements of the autonomous navigation system of off-road vehicles.

       

    /

    返回文章
    返回