A Low-Cost Navigation Strategy for Yield Estimation in Vineyards

Accurate yield estimation is very important for improving the vineyard management, the quality of the grapes and the health of the vines. The most common systems use RGB image processing for achieving a good estimation. In order to collect images, robots or farming vehicles can be equipped with a RGB camera. In this paper, we propose a low-cost autonomous system which can navigate through a vineyard while collecting grape pictures in order to provide a yield estimation. Our system uses only a laser scanner to detect the row and follows it until its end, then it navigates towards the next one, exploiting the knowledge of the vineyard. The navigation algorithm was tested both in simulation and in a real environment with good results. Furthermore, a yield estimation of two different grape varieties is presented.

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