履带式电动微耕机自动导航系统设计与试验

    Design and experiment of the automatic navigation system for tracked electric micro tillers

    • 摘要: 为提高微耕机智能化程度,满足日益增强的“以机代人”需求,该研究设计了一种适用于园艺环境的履带式自动导航电动微耕机。首先,以搭载ROS系统(robot operating system)的英伟达Jetson Orin Nano为主控,建立导航控制系统,并与电动微耕机底层通讯。其次,基于卡尔曼滤波法和扩展卡尔曼滤波法,根据粗差对扩展卡尔曼滤波状态估计的影响,提出改进抗差自适应扩展卡尔曼滤波法,以纠正单项错误和多个特殊误差,从而最大程度限制并降低粗差对北斗引导PVT(position、velocity、time)解算的负面影响,并提高定位精度和信号稳定程度。采用梭式路径规划方法开展导航试验并记录定位数据,对比不同定位数据处理方法xyz轴定位误差标准差。结果表明,本研究提出的改进抗差自适应扩展卡尔曼滤波法在提高定位精度和信号稳定性方面具有一定优势。以车速、耕深、旋耕刀转速为试验因素,以碎土率为评价指标,设计Box-Behnken试验;对试验结果进行方差分析,建立评价指标与试验因素的回归模型。以提高碎土率为寻优目标,对作业速度、耕深、旋耕刀转速进行寻优求解,获得较优参数组合为作业速度1.4 km/h,耕深6 cm,旋耕刀转速234 r/min。开展田间耕作试验,碎土率可达95.8%,表明履带式自动导航电动微耕机具有较优的作业质量,满足园艺环境的旋耕作业要求。

       

      Abstract: In order to improve the intelligent degree of the micro tiller and meet the increasing demand of "replacing people with machines", a crawler type automatic navigation electric micro tiller suitable for gardening environment was designed. First, the NVIDIA Jetson Orin nano equipped with the robot operating system (ROS) is used as the main control to establish the navigation control system and communicate with the bottom layer of the electric micro tiller. Secondly, based on Kalman filter and extended Kalman filter, according to the influence of gross error on extended Kalman filter state estimation, an improved robust adaptive extended Kalman filter is proposed to effectively correct single error and multiple special errors, so as to limit and reduce the negative impact of gross error on Beidou guidance PVT (position, velocity, time) solution to the greatest extent, and improve the positioning accuracy and signal stability. The shuttle path planning method was used to carry out the navigation test and record the positioning data, and the positioning error standard deviations of x, y, z axes corresponding to different positioning data processing methods were compared. The results show that the improved robust adaptive extended Kalman filter proposed in this study has certain advantages in improving the positioning accuracy and signal stability. The box Behnken test was designed with vehicle speed, tillage depth and rotary blade speed as test factors and soil fragmentation rate as evaluation index; The test results were analyzed by variance, and the regression model of evaluation index and test factors was established. In order to improve the broken soil rate as the optimization goal, the operation speed, tillage depth and rotary blade speed were optimized. The optimal parameter combination was obtained as operation speed 1.4 km/h tillage depth 6 cm and rotary blade speed 234 r/min. The field tillage experiment showed that the broken soil rate could reach 95.8%, which showed that the crawler type automatic navigation electric micro tiller had better operation quality and could meet the requirements of rotary tillage in horticultural environment.

       

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