The RoMoVi project has as main objective the development of robotic components and a modular and extensible mobile platform, which will allow in the future to provide commercial solutions for hillside vineyards capable of autonomously executing operations of: Monitoring, Logistics. The RoMoVi aims to develop a platform simultaneously low cost and extremely modular and versatile to be able to integrate the most diverse types of payload, both sensors and actuators.

Development of vision technologi for detection of weeds in early development stage. Implementation in a weeding robot with thermal destruction of weeds. Suitable for production of organic food.

Automatic vision and robot technologi for sustainable and competitive production of plant decoration products

Automated Weeder Separates Friend from Foe. Friday, February 20, 2015 New technology being developed by the University of California – Davis is putting precision weed control onto farm equipment, which will eliminate the need for much of today’s manual labor. This is not your granddad’s weed whacker.

Case Study: Maximising production from our limited water resource and unlocking the power of variable rate irrigation INDUSTRY: AGRICULTURE AND IRRIGATION The Need: Reducing the water required to irrigate crops, thereby increasing the land area that can be irrigated from existing water takes, and reducing the nutrient leaching that can result from over irrigation and cause groundwater contamination. The Solution: Lincoln Agritech has been awarded Ministry of Business, Innovation and Employment science funding to develop a novel, cost-effective moisture sensor that is capable of remo

The project AGROBV14 aims to answer a need identified by the European Steep Slope Viticulturalists/wine makers (more about this reality can be found at http://www.dourovalley.eu/en/).

This research project is to start the development of new tools robotic serving the environment and agriculture. Its purpose is to increase efficiency of operations to perform in natural environments, while contributing to the preservation of environmental goods. To do this, several scientific barriers must be removed, requiring the emergence of a research team brings together multidisciplinary expertise: algorithm for decision support, man / machine interaction, robotics system control and perception.

IDFS project aims to develop a new sensor system for providing information on water requirements of plants. This system will be integrated to an existing robot, used for weed control: Anatis.

The project aims to deploy a robotic solution in the sectors of horticulture, viticulture, arboriculture or field crops. Improving the reliability of robotic systems, security, visual perception or autonomy among its working axes. The premise is this: fewer pesticides, less painfulness

Broad-leaved dock (Rumex obtusifolius L.) is a common and troublesome weed with a wide geographic distribution. The weed is readily consumed by livestock but its nutritive value is less than that of grass. The high contents of oxalic acid and oxalates can affect animal health if consumed in larger doses. When left uncontrolled, the weed will reach a high density and reduce grass yield by 10 to 40%. In conventional dairy farming, the weed is normally controlled by using herbicides. In organic farming no synthetic pesticides are used and there is a risk that broad-leaved dock will spread.

The main goal is to optimise the feeding strategy for grazing cattle and to improve the methods of pasture management. An in the frame of the project developed pasture robot and a modified automatic grazing system (AGS) will be integrated into existing herd management software (HMS), providing an optimal feeding strategy for cattle and pasture maintenance. A robot will be redesigned and sensors for detection of biomass, cowpats etc. and actuators, a mulcher and a seeder, will be implemented.

Lowland areas and other marginal areas form a huge and currently unused resource of biomass for the biogas and bio refinery industry. Alone for Denmark, it has been estimated that 160-180.000 hectares of unused lowland could be harvested if the appropriate technology was available. This project will develop a novel lightweight, autonomous machine concept for economically and environmentally sound harvest of grass on lowland.

The idea of this project is that of using different sensor modalities and multi-algorithm approaches to detect the various kinds of obstacles and to build an obstacle database that can be used for vehicle control. For instance, bearing and distance to the nearest collision can be estimated and used by the path planner to change route or to lower the speed if an obstacle is in close proximity to the vehicle’s planned path. Road and cliff edges should be handled as special cases since the consequences to the vehicle of breaching a cliff edge are very severe.

The main objective of the ROBOFARM project is to create a technology platform that integrates and harmonizes existing software and hardware technologies into a single system and makes use of robots equipped with sensors and active vision systems to collect data from the fields automatically, in order to feed a Decision Support System (DSS) for the farm management and considering the agronomical, environmental and food safety aspects.

The main objective of the STRATOS project is to develop an open ICT hardware-software infrastructure enabling the partial automation of tractors and at the same time enhancing their operational safety and production efficiency, with the positive effects of reduced accident risk and environmental impact.