an automatic weeding robot
DESCRIPTION
An automatic weeding robot. Session T 94.1 The Danish Plant Production Congress 2006, January 10th, 2006. Mechanically/physically weed control. Formulation of problems:. Operating costs (working hours/ha, varying weed control effeciency). - PowerPoint PPT PresentationTRANSCRIPT
Michael NørremarkMichael Nørremark Department of Agricultural SciencesDepartment of Agricultural SciencesCand. agro., Ph.D.-studentCand. agro., Ph.D.-student Environment, Resources and Technology Environment, Resources and Technology
Hojbakkegaard Alle 10, DK–2630 Taastrup, DenmarkHojbakkegaard Alle 10, DK–2630 Taastrup, Denmark
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
An automatic weeding robotAn automatic weeding robot
Session T 94.1Session T 94.1
The Danish Plant Production Congress 2006, The Danish Plant Production Congress 2006,
January 10th, 2006January 10th, 2006
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Mechanically/physically weed controlMechanically/physically weed control
Formulation of problems: Formulation of problems:
• Capital costs (investment in novel technology)Capital costs (investment in novel technology)
• Operating costs (working hours/ha, varying weed control effeciency)Operating costs (working hours/ha, varying weed control effeciency)
• Herbicides is known technologyHerbicides is known technology
• Novel technology should be better than herbicidesNovel technology should be better than herbicides
• No possibility of efficient mechanical/physically weed control close to cropNo possibility of efficient mechanical/physically weed control close to crop
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Aim of the Research Project ’Robotic Weeding’Aim of the Research Project ’Robotic Weeding’
• manual effort by 50 - 100% at physical weed control in row cropsmanual effort by 50 - 100% at physical weed control in row crops
• herbicide usage by 75 – 100% i conventional grown row cropsherbicide usage by 75 – 100% i conventional grown row crops
To develop novel automatic weeding technology and To develop novel automatic weeding technology and weeding strategies that can reduce:weeding strategies that can reduce:
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
ObjectivesObjectives
To investigate precision and limitations forTo investigate precision and limitations for::
• automatic and unmanned row guidanceautomatic and unmanned row guidance
- scope of application- scope of application::
• weed control between crop rowsweed control between crop rows
• weed control within crop rowsweed control within crop rows
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Automatic row guidance (commercial)Automatic row guidance (commercial)
Photos: www.thyregod.comPhotos: www.thyregod.com
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Automatic row guidance/driver assistance – news!Automatic row guidance/driver assistance – news!
ECO-DAN/agrocom DUO-DRIVEECO-DAN/agrocom DUO-DRIVE
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Aut. and unmanned row guidance & tractor controlAut. and unmanned row guidance & tractor control
RTK-GPS Seeder RTK-GPS Seeder (geo-(geo-spatial seed map)spatial seed map)
Navigation based on geo-spatial seed map Navigation based on geo-spatial seed map (estimated plant (estimated plant positions)positions)
Automatic og unmanned Automatic og unmanned row guidance (RTK-GPS)row guidance (RTK-GPS)
(weed control (weed control between crop rowsbetween crop rows))
Automatic og unmanned Automatic og unmanned row guidance (RTK-GPS) row guidance (RTK-GPS)
(weed control (weed control within within crop rowscrop rows))
(RTK-GPS accuracy < 2 cm)(RTK-GPS accuracy < 2 cm)
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Machines and procedures (I)Machines and procedures (I)
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Machines and procedures (II)Machines and procedures (II)
x
y
r
max(r) = 37.3 mm (P 0.95)max(r) = 37.3 mm (P 0.95)
RTK-GPS seeder (geo-spatial seed map)RTK-GPS seeder (geo-spatial seed map)
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Machines and procedures (III)Machines and procedures (III)
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Machines and procedures (IV)Machines and procedures (IV)
RTK-GPS controlled hoeing between rowsRTK-GPS controlled hoeing between rows
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Machines and procedures (V)Machines and procedures (V)
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Machines and procedures (VI)Machines and procedures (VI)
Supported by:Supported by:
(on-going project)(on-going project)
RTK-GPS controlled ’cycloide’ hoeing within crop rowsRTK-GPS controlled ’cycloide’ hoeing within crop rows
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Field experiments (I)Field experiments (I)
NN
Trial plan:Trial plan:• 2 forward speeds (2 and 4 km/h)2 forward speeds (2 and 4 km/h)
• Straight trajectories (45 m) in NS and EW directionsStraight trajectories (45 m) in NS and EW directions
• 1 repetition1 repetition
• 100 manuallly measured deviations per 45 m 100 manuallly measured deviations per 45 m (ruler)(ruler)
• GPS log file (10 Hz)GPS log file (10 Hz)
Validation:Validation:
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Field experiment (II)Field experiment (II)
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Field experiment (III)Field experiment (III)
Measuring deviations to the planned path (crop rows):Measuring deviations to the planned path (crop rows):
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Cross-track errors and covered area Cross-track errors and covered area (II)(II)
Row width:Row width: 50 cm50 cm
Band width:Band width: 5 cm5 cm
Meas. dev. (x 1.96):Meas. dev. (x 1.96): 6 cm6 cm
Hoe unit working Hoe unit working width:width: 39 cm39 cm
Example:Example:
- assuming max. 5 % crop damage- assuming max. 5 % crop damage
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Cross-track errors and covered area (II)Cross-track errors and covered area (II)
Average forward Average forward velocityvelocity
Hoe unit workingHoe unit workingwidth at 50 cm row widthwidth at 50 cm row width
Treated area at Treated area at 50 cm row width50 cm row width
[km/h][km/h] [cm][cm] [%][%]2.02.0 40.4 - 41.540.4 - 41.5 81 - 8381 - 83
4.34.3 33.8 - 39.933.8 - 39.9 68 - 7968 - 79
Resultater (min. - max.):Resultater (min. - max.):
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
ConlusionsConlusions
Basis for automatic og unmanned hoeing within crop rowsBasis for automatic og unmanned hoeing within crop rows
Automatic og unmanned row guidance worksAutomatic og unmanned row guidance works
Obtained precision similar to other row guidance technologyObtained precision similar to other row guidance technology
Possibility of several treatments without increase in working hours/haPossibility of several treatments without increase in working hours/ha
In principle 24 hour operationIn principle 24 hour operation
~ 20% of the field area still requires hand weeding (or band spraying)~ 20% of the field area still requires hand weeding (or band spraying)
THE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITYTHE ROYAL VETERINARY AND AGRICULTURAL UNIVERSITY
Contributors (aut. hoeing between crop rows)Contributors (aut. hoeing between crop rows)
Jaime Soriano Ibarra (MSc student, master thesis)Jaime Soriano Ibarra (MSc student, master thesis)
Hans W. Griepentrog (main supervision, machine design)Hans W. Griepentrog (main supervision, machine design)
Michael Nørremark (software, hardware, field experiments)Michael Nørremark (software, hardware, field experiments)
Jon Nielsen (software, hardware)Jon Nielsen (software, hardware)
Supported by:Supported by: