REVIEW OF POSITION RESEARCH ON AUTOMATION NAVIGATION SYSTEM FOR AGRICULTURE MACHINES

摘要

vehicle automation is one of important contents of precision agriculture. This paper focuses on the location problem of agricultural automation navigation system. Based on the current development of agricultural automation navigation at home and abroad, pointed out the commonly used sensors such as GPS 、IMU and machine vision technology which have the characteristics and shortcomings respectively. The high accuracy GPS is with high initial cost, it provides absolute position measurements. Some factors influence GPS's accuracy. IMU is unsuitable for accuracy positioning over an extended period of time. The machine vision system supplies relative position measurements along a row of plants. But it is impacted by the natural environment. The systems require not only with higher accuracy but also with better reliability and integrity. Excellent method can correct sensor errors and enhance accuracy. Currently, the most commonly used method of multi-sensor information fusion is Kalman filter. On the basis of analysis the Kalman filtering algorithm, presented some intelligent algorithms. Finally, summarizes the existence of the problems and key technologies of the current autonomous navigation of agricultural machinery, and analyze the development trends of agricultural machinery automatic navigation.