Research on Unmanned Vehicle Road Condition Recognition and Classification Based on Sensors and BP Neural Networks
AO Xiang
WANG Liming
ZHAO Yonghui
LUAN Chaokun
MA Zhiyang
Abstract：To ensure the stable operation of unmanned vehicles in complex unstructured road environments,it is necessary to accurately identify the real-time road conditions in which the unmanned vehicles are driving.To meet this requirement,this article provides a detailed introduction to a new method.Firstly,the onboard gyroscope sensor and motor encoder are used to capture real-time motion data of the unmanned vehicle,including but not limited to key indicators such as vehicle speed and angle.Then,the raw data is subjected to feature processing to extract key features that are helpful for road condition recognition.Then,the raw data is subjected to feature processing to extract key features that are helpful for road condition recognition.During the experimental phase,validation is conducted using unmanned vehicles equipped with ROS operating systems and Matlab.The experimental results show that the road recognition method proposed in this study is effective and accurate,providing good support for subsequent stability control.
Keywords：unstructured roadBP neural networkvehicle sensorrecognize
Publication Date：2024-09-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 42-47 )