Paper Info
Title
Path Tracking Control of Field Information-Collecting Robot Based on Improved Convolutional Neural Network Algorithm.
Abstract
Due to the narrow row spacing of corn, the lack of light in the field caused by the blocking of branches, leaves and weeds in the middle and late stages of corn growth, it is generally difficult for machinery to move between rows and also impossible to observe the corn growth in real time. To solve the problem, a robot for corn interlines information collection thus is designed. First, the mathematical model of the robot is established using the designed control system. Second, an improved convolutional neural network model is proposed for training and learning, and the driving path is fitted by detecting and identifying corn rhizomes. Next, a multi-body dynamics simulation software, RecurDyn/track, is used to establish a dynamic model of the robot movement in soft soil conditions, and a control system is developed in MATLAB/SIMULINK for joint simulation experiments. Simulation results show that the method for controlling a sliding-mode variable structure can achieve better control results. Finally, experiments on the ground and in a simulated field environment show that the robot for field information collection based on the method developed runs stably and shows little deviation. The robot can be well applied for field plant protection, the control of corn diseases and insect pests, and the realization of human-machine separation.
Year
DOI
Venue
2020
10.3390/s20030797
SENSORS
Keywords
Field
DocType
information collection robot,control,machine vision,corn rows,path tracking
Row,Simulation software,MATLAB,Machine vision,Convolutional neural network,Control engineering,Electronic engineering,Control system,Engineering,Robot,Path tracking
Journal
Volume
Issue
ISSN
20
3
1424-8220
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Yili Gu100.34
Zhiqiang Li200.34
Zhen Zhang300.34
Junjie Li43012.76
Liqing Chen500.34