| The ways to clean heaped snow on speedways, highways and urban streets in winter has been the research focus around the world over the years. Snow-cleaning work bears close relation to a series of issues such as social production, people's daily lives, traffic safety and environmental protection in northern cities. With social development and the ever-increasing level of mechanical technology, people are pressed for an efficient and roboticized device to sweep snow in place of the conventional snow-cleaning method.This research was conducted through the multifunction snow remover project sponsored by the State Economic and Trade Commission. Based on the road detection information obtained by GPR(ground penetration radar), the study is carried out on the automatic control system for the snow-remover's shovel to effect the detecting of road snow thickness and fulfill the shovel's automatic obstacle-avoiding function. The specific work involves:(1)The forward model of the snow road with obstacles is established by using GprMaxV2.0 software and applying the basic principles of the electromagnetic wave theory. The detection echo data obtained from the simulated model is calculated. In light of the variant properties of the GPR electromagnetic wave at different medium interfaces, the echo data from the simulation is given a detailed analysis to explore the road surface information pattern from the radar echo data.(2)The GPR is employed to carry out grouped detection experiments on the snow-heaping road surface to collect the echo data. The collected data are entered into the MATLAB software for analysis; the correlation coefficient method is selected as the control algorithm considering the difference among echo data curves. The existence of obstacles on the road surface is judged through calculating... |
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