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A robot to detect and control broad-leaved dock (Rumex obtusifolius L.) in grassland

Authors :
van Evert, F.K.
Samsom, J.
Polder, G.
Vijn, M.P.
van Dooren, H.J.C.
Lamaker, E.J.J.
van der Heijden, G.W.A.M.
Kempenaar, C.
van der Zalm, A.J.A.
Lotz, L.A.P.
van Evert, F.K.
Samsom, J.
Polder, G.
Vijn, M.P.
van Dooren, H.J.C.
Lamaker, E.J.J.
van der Heijden, G.W.A.M.
Kempenaar, C.
van der Zalm, A.J.A.
Lotz, L.A.P.
Source :
ISSN: 1556-4959
Publication Year :
2011

Abstract

Broad-leaved dock is a common and troublesome grassland weed with a wide geographic distribution. In conventional farming the weed is normally controlled by using a selective herbicide, but in organic farming manual removal is the best option to control this weed. The objective of our work was to develop a robot that can navigate a pasture, detect broad-leaved dock, and remove any weeds found. A prototype robot was constructed that navigates by following a predefined path using centimeter-precision global positioning system (GPS). Broad-leaved dock is detected using a camera and image processing. Once detected, weeds are destroyed by a cutting device. Tests of aspects of the system showed that path following accuracy is adequate but could be improved through tuning of the controller or adoption of a dynamic vehicle model, that the success rate of weed detection is highest when the grass is short and when the broad-leaved dock plants are in rosette form, and that 75% of weeds removed did not grow back. An on-farm field test of the complete system resulted in detection of 124 weeds of 134 encountered (93%), while a weed removal action was performed eight times without a weed being present. Effective weed control is considered to be achieved when the center of the weeder is positioned within 0.1 m of the taproot of the weed—this occurred in 73% of the cases. We conclude that the robot is an effective instrument to detect and control broad-leaved dock under the conditions encountered on a commercial farm. © 2010 Wiley Periodicals, Inc.

Details

Database :
OAIster
Journal :
ISSN: 1556-4959
Notes :
application/pdf, Journal of Field Robotics 28 (2011) 2, ISSN: 1556-4959, ISSN: 1556-4959, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1452797704
Document Type :
Electronic Resource