Requirements and challenges
Traditional vegetable farms in the Loire Valley are based on bed cropping, in open field or under cold plastic greenhouse. More than 60 kinds of vegetables are grown and the pilot area requires 20 workers for an area of 70 ha to cultivate salads, lamb lettuce, leeks, baby-leaf salad, carrots, and in one year, several (3-5) crops are produced at the same place. As a result, many kinds of tasks must be managed on different vegetables, and many tools must be available at any time, while several passes of tractors damage the soil and cause severe compaction. That is the reason why, most often, old tractors are used with always the same tool: tools are not uncoupled.
The second testing site will be established to focus on high precision inter and intra row weeding of vegetables using the Ceol robot and several different mechanical weeding implements attached. Emphasis will be given on navigation and weeding along the rows, in order to ensure that Ceol does not step over the plants and weeding knives make accurate distinction between vegetables and weeds.
Technology: Ceol robot, Mechanical weeding implements
Partners: Terrena, Agreenculture, Agricultural University of Athens, Fundacio Eurecat, University of Copenhagen
Via trials in four countries – the Netherlands, France, Spain and Greece — Robs4Cros hopes to create a robotic farming solution consisting of three elements: smart implements, autonomous vehicles, and the farming controller.
Direct comparison of both retrofit tractor and Ceol robot, under the same scenarios.
Addressing the labour challenge of the apple sector by automating the complex task of orchard spraying.
Low weight Robot and camera-based weeder to innovate potato farming and minimize damage to soil structure.
With the help of Ceol robot, Robs4Crops will reduce chemical use and labor costs, and evaluate the modularity of the platform.
Wageningen University & Research
Department of Agrosystems Research
PO Box 16
6700 AA Wageningen
The Netherlands
info@robs4crops.eu
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101016807.
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