Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 350225
Title A Mobile Field Robot with Vision-Based Detection of Volunteer Potato Plants in a Corn Crop
Author(s) Evert, F.K. van; Heijden, G.W.A.M. van der; Lotz, L.A.P.; Polder, G.; Lamaker, A.; Jong, A. de; Kuyper, M.C.; Groendijk, E.J.K.; Neeteson, J.J.; Zalm, A.J.A. van der
Source Weed Technology 20 (2006)4. - ISSN 0890-037X - p. 853 - 861.
DOI https://doi.org/10.1614/WT-05-132.1
Department(s) Agrosystems
PRI Biometris
PRI Bioscience
Centre Geo-information
PRI Facility Services
Publication type Refereed Article in a scientific journal
Publication year 2006
Keyword(s) mechanical weed-control
Abstract Volunteer potato is a perennial weed that is difficult to control in crop rotations. It was our objective to build a small, low-cost robot capable of detecting volunteer potato plants in a cornfield and thus demonstrate the potential for automatic control of this weed. We used an electric toy truck as the basis for our robot. We developed a fast row-recognition algorithm based on the Hough transform and implemented it using a webcam. We developed an algorithm that detects the presence of a potato plant based on a combination of size, shape, and color of the green elements in an image and implemented it using a second webcam. The robot was able to detect potatoes while navigating autonomously through experimental and commercial cornfields. In a first experiment, 319 out of 324 images were correctly classified (98.5%) as showing, or not showing, a potato plant. In a second experiment, 126 out of 141 images were correctly classified (89.4%). Detection of a potato plant resulted in an acoustic signal, but future robots may be fitted with weed control equipment, or they may use a global positioning system to map the presence of weed plants so that regular equipment can be used for control.
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