基于虚拟雷达和两级神经网络的割草机路径跟踪算法

Path Tracking Algorithm for Mower Based on Virtual Radar and Two⁃level Neural Network

为提高果园内小型双电机驱动履带式割草机恶劣路面下路径跟踪精度,提出了一种基于虚拟雷达路径感知和两级深度神经网络的路径跟踪控制算法。首先搭建了两级串联的人工深度神经网络,一级深度神经网络通过虚拟雷达路径感知算法,计算得到履带式割草机与目标路径的相对位置关系。二级深度神经网络根据履带式割草机跟踪偏差、航向角、横向偏差影响因子、折算履带滑转率以及履带式割草机与目标路径的相对位置关系,计算得到两侧驱动电机的控制转速,实现路径跟踪控制。在灌溉翻浆的果园路面,开展了履带式割草机U形路径跟踪实车试验,当车速分别为0.4、0.8 m/s时,该算法路径跟踪的最大横向偏差分别为0.064、0.072 m,平均横向偏差分别为0.026、0.033 m。与传统的纯追踪控制算法相比,最大横向偏差分别减小31.18%、20.88%,平均横向偏差减小35.00%、29.79%。基于虚拟雷达和两级深度神经网络的路径跟踪控制算法可有效提升履带式割草机在恶劣路面下的路径跟踪精度。

In order to improve the path tracking accuracy of small dual⁃motor driven crawler mower in orchard under severe road conditions,a path tracking control algorithm based on virtual radar path perception and two⁃level deep neural network was proposed.Firstly,a two⁃level serial artificial deep neural network was built,and the first⁃level deep neural network calculated the relative position relationship between the crawler mower and the target path through the virtual radar path sensing algorithm.The control speed of driving motors on both sides was calculated according to tracking deviation,heading angle,influence factor of lateral deviation,factor of converted track slip rate and relative position relationship between crawler mower and target path,and path tracking control was realized by second⁃level deep neural network.The U⁃shaped path tracking tests of crawler mower were carried out on orchard road surface after irrigation.When the vehicle speeds were 0.4 m/s and 0.8 m/s,the maximum lateral deviations of path tracking algorithm were 0.064 m and 0.072 m,and the average lateral deviations were 0.026 m and 0.033 m,respectively.Compared with the traditional pure tracking control algorithm,the maximum lateral deviations at the test speed of 0.4 m/s and 0.8 m/s were reduced by 31.18%and 20.88%,respectively,and the average lateral deviations were reduced by 35.00%and 29.79%,respectively.The path tracking control algorithm combining virtual radar and two⁃level deep neural network can effectively improve the track tracking accuracy of crawler mower on bad road surface.