Autonomous robotic weed control systems: A review

Slaughter, David C.; Giles, Durham K.; Downey, D.

doi:10.1016/j.compag.2007.05.008

Cited by 647 publications

(409 citation statements)

References 65 publications

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“…Automatic image segmentation by thresholding is a commonly used image processing technique in ecological applications (Cescatti, 2007;Graham et al, 2009). Simple image processing techniques are making standard the use of digital cameras for the detection of plant phenological events (Crimmins and Crimmins, 2008;Graham et al, 2009, in press;Morisette et al, 2009;Richardson et al, 2009) as well as for automating a range of agricultural monitoring practices (Jia et al, 2004;Slaughter et al, 2008). The uses of cameras in these studies have been primarily based on the color reflectance of plants.…”

Section: Discussionmentioning

confidence: 99%

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Graham

Lam

Yuen

2010

Agricultural and Forest Meteorology

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a b s t r a c tThe characterization of the solar radiation environment under a forest canopy is important for both understanding temperature-dependent biological processes and validating energy balance models. A modified sinusoidal model of soil heat conductivity was used to estimate subsurface temperature and heat flux from the uneven but periodic solar heating of the soil surface due to sun flecks from a forest canopy. Using a mobile sensor platform with an infrared thermometer along an 11 m transect, a sunfleck model of soil surface temperature was tested using soil surface temperature maxima, air temperatures, and photodiodes placed on the soil surface to measure sunflecks. A pan-tilt-zoom digital camera on a 10 m tower above the site was then used to capture a time series of panoramic images of sunflecks reflected from the soil surface and to scale the sunfleck temperature model to a wide area. Finally, this image-based model of surface temperatures was combined with the modified sinusoidal model for heat conduction to estimate soil subsurface temperatures and heat flux over a wide area due to sunflecks from a forest canopy.

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Section: Discussionmentioning

confidence: 99%

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Graham

Lam

Yuen

2010

Agricultural and Forest Meteorology

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“…According to Slaughter, Giles, and Downey (2008), one of the most commonly used machine vision methods for identifying crop rows is based upon the Hough (1962) transform. It was intended to deal with discontinuous lines, where the crop stand is incomplete with gaps in crop rows due to poor germination or other factors that result in missing crop plants in the row.…”

Section: Methods Based On the Hough Transformationmentioning

confidence: 99%

“…Astrand (2008) and Slaughter et al (2008) propose a list of requirements for guidance systems that can be also considered for crop row detection, which in essence is a similar problem. Knowledge and requirements are mapped as follows to build the architecture of the proposed automatic expert system for the accuracy crop row detection based on images.…”

Section: System Architecturementioning

confidence: 99%

“…In order to detect the real crop lines over the image we have also applied the Hough transformation (Slaughter et al, 2008). Despite we apply geometric constraints considering the extrinsic and intrinsic parameters; the method produces abundant peaks on the accumulator cells, making difficult the selection of the correct one that identifies a crop row.…”

Section: Qualitative Analysismentioning

confidence: 99%

See 1 more Smart Citation

Automatic expert system based on images for accuracy crop row detection in maize fields

Guerrero

Guijarro

Montalvo

et al. 2013

Expert Systems with Applications

108

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This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil-Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product-moment correlation coefficient.

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“…Over the past decade, rapid advancements in automation and real-time recognition have occurred for weed control in cropping systems (see reviews by Singh et al 2011;Slaughter et al 2008a). The use of sensors and computers to quickly assess plants and their location within a field has led to the development of various systems.…”

Section: Introductionmentioning

confidence: 99%

Targeted and Microdose Chemical Applications

Young

Giles

2013

Automation: The Future of Weed Control in Cropping Systems

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In cropping systems, the precise application of herbicides is important for efficacious weed control. By using plant recognition and precision application technology targeting individual plants, off-target movement can be eliminated and herbicide rates significantly reduced without sacrificing yields. Highly targeted applications of nonselective herbicides into a growing sensitive crop are novel operations, nonexistent before the development of plant-specific targeting. New application technologies are essential when spatial rather than chemical selectively is to be deployed. In many potential applications, the chemical delivery system becomes the spatial resolution and speed limiting factor in the system.

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Autonomous robotic weed control systems: A review

Cited by 647 publications

References 65 publications

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Automatic expert system based on images for accuracy crop row detection in maize fields

Targeted and Microdose Chemical Applications

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