基于星基增强精密单点定位的农机自动导航系统开发与测试

    Development and test of auto-navigation system for agricultural machinery based on satellite-based precision single-point positioning

    • 摘要:
      目的  开发基于星基增强精密单点定位的农机自动导航系统。
      方法  以国产雷沃TX1204拖拉机为平台,采用国产星基增强定位板卡的输出数据作为农机位置反馈量,设计位速卡尔曼滤波器对定位数据进行滤波处理,开发预瞄跟随PID路径跟踪控制算法进行导航控制,整定不同行驶速度条件下的模型控制参数,采用地基增强RTK高精度定位接收机输出数据作为参考量,搭建农机自动导航测试系统并开展系统性能测试。
      结果  在直线跟踪误差方面,所开发的农机自动导航系统平均误差为−0.0009436 m,标准差为0.02452 m,最大误差绝对值为0.08472 m;在邻接行误差方面,平均误差为0.0007128 m,标准差为0.02986 m,最大误差绝对值为0.15444 m。这一精度可满足大部分农机自动导航作业需求。
      结论  将国产星基增强精密单点定位技术用于农机自动导航是可行的;本文设计的预瞄跟随PID路径跟踪控制模型和提出的不同速度条件下PID参数与前视距离的整定方法,提高了系统对不同速度的自适应能力。

       

      Abstract:
      Objective  To develop an automatic navigation system for agricultural machinery based on satellite-based precision single-point precision.
      Method  With the domestic Lovol TX1204 tractor as the platform, the output data of the domestic satellite-based precision single-point positioning board were used as the position feedback of the agricultural machinery, the position-velocity Kalman filter was designed to filter the positioning data, and the preview following PID path tracking control algorithm was developed. The model control parameters under different driving speed conditions were tuned, and the output data of the ground-based RTK high-precision positioning receiver were used as the references, the automatic navigation test system of agricultural machinery was built and the system performance test was carried out.
      Result  In terms of linear tracking error, the average error was −0.0009436 m, the standard deviation was 0.02452 m, and the absolute maximum error was 0.08472 m. In terms of adjacent line error, the average error was 0.0007128 m, the standard deviation was 0.02986 m, and the absolute maximum error was 0.15444 m, which could meet the needs of most agricultural machinery automatic driving operations.
      Conclusion  Domestic satellite-based precision single-point positioning technology can be used for agricultural machinery automatic navigation. The preview-following PID path tracking control model designed in this paper is valid and the proposed method for tuning PID parameters and foresight distance under different speed conditions provides a basis for improving the adaptive ability of this system to different speed conditions.

       

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