The vision of the project is to contribute to the development of novel weeding technologies that can reduce manual effort by 50-100% in organically grown sugar beets and vegetables and herbicide usage by 75-100% in high value crops, e.g. conventional grown sugar beets. An important aim is to establish a synergistic framework for key-scientists, the commercial partners, PhD and MSc-students carrying out research on robotic weeding. The specific objectives of the project within this framework are
- to optimise (technically and biologically) the geo-referencing of seeds during the sowing operation
- to develop automated identification and geo-referencing of crop and weed seedlings
- to investigate the accuracy, potentials and limitations of non-chemical devices for intra-row and close-to-crop weeding
- to investigate targeted micro-spraying of weeds in the close-to-crop area
The goal of the project is to demonstrate an integration of crop-seed mapping, computer vision for identification crop and weed seedlings and highly accurate devices for mechanical and chemical targeting of weed seedlings. The investigations and demonstrations will be carried out in fields with sugar beets but the detection and weeding principles studied in the project can be modified to work with any wider spaced crops (densities < 20 plants m-2), e.g. maize and vegetables.
This project is part of the National Research programme ‘Sustainable Technology in Agriculture’ ("Bæredygtigt teknologi i Jordbruget”), supported by the Danish Technical Research Council (STVF), the Danish Agricultural and Veterinary Research Council (SJVF) and the Danish Ministry of Food, Agriculture and Fisheries.
2003 - 2005
Project
leader:
Svend Christensen, Research
Director at DIAS
Research Center, Bygholm
Hans W. Griepentrog,
Associate
Professor at KVL, Frederiksberg
Michael Nørremark,
PhD student at KVL, Frederiksberg
Henning Tangen
Søgaard, Senior Researcher at DIAS
Research Center, Bygholm
Ivar Lund, PhD student at DIAS
Research Center, Bygholm
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WP1: System definition and integration (DIAS + KVL) |
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WP2: Seed geo-referencing (KVL) |
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WP3: Computer vision for identification of crop seedlings (DIAS) |
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WP4: Non-chemical weeding tools (KVL) |
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WP5: Micro-spray system (DIAS) |
- Eco-Dan A/S, Bøgeskovvej 6, DK-3490 Kvistgaard
- Hardi International A/S, Helgeshøj Alle 38, DK-2630 Taastrup
- Osnabrück University of Applied Sciences, Postfach 19 40, D-49009 Osnabrück
- Hako-Werke GmbH&Co, Hamburger Str. 209-239, D-23843 Bad Oldesloe
Page updated 07/02/2008