Machine Vision Based Steering System for Agricultural Combines

نویسنده

  • E. R. Benson
چکیده

Agriculture is vitally important to the economy and well being of the United States. Corn and soybeans are two of the most important crops in the Midwest. Automated agricultural guidance systems offer opportunities for reduced fatigue, improved safety, increased efficiency and a host of other improvements. A machine vision based guidance system for agricultural combines was developed at the University of Illinois. Three machine vision guidance algorithms were developed; the most successful algorithm utilized a single camera mounted at approximately operator eye level on the cab of the combine. The algorithm, called the Cab Mounted Camera Algorithm (CMCA), closely mimics the perceptive process used by the operator. The algorithm developed was used to automatically harvest a 4.6 ha (12.0 a) cornfield during both the day and at night. The indicated accuracy of the guidance system was statistically the same as the accuracy of the GPS used to record the position of the combine.

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تاریخ انتشار 2001