Yield forecasting can provide important benefits for wine industry in terms of quality and
efficiency. Vineyard yield estimation can be obtained using several methods being the most widely
used the method based on visual assessment and/or counting/weighing the yield components The
increasing importance of yield forecast has lead to automated solutions for the data acquisition and
allowed the first service robotics applications in viticulture. In this paper we aim to present the
preliminary results obtained in the European research project VinBot: “Autonomous cloudcomputing
vineyard robot to optimize yield management and wine quality”. The paper focuses in
the robot navigation. Robot navigation for agriculture has been a continuous research topic in the
last years. Even there is a wide number of RTK-DGPS and PPP based navigation solutions available
for precision farming, navigation in vineyards has some particularities and can benefit from other
navigation techniques. The high cost and in some cases other limitations as fix ratios (determined
by baseline distances to base stations), or communication limitations in the field make alternative
solutions desirable. In this paper, we present a hybrid reactive/GPS based navigation scheme tested
successfully in vineyard navigation. The proposed solution makes use of a laser range finder and
RGBD device to perform reactive row following and obstacle avoidance, while it can make use of
other reactive behaviors or GPS waypoint navigation for changing from row to row or field to field,
thus supporting different levels of automation. The paper includes also some experiences with
recently introduced new generation low-cost RTK-DGPS devices, that in the coming years will
enable the progressive introduction of viticulture robotsinfo:eu-repo/semantics/publishedVersio
