Method and apparatus for generating control data for controlling an agricultural apparatus for treating an agricultural field, product, digital treatment map, method for controlling an agricultural apparatus, and agricultural apparatus

Abstract

A computer-implemented method for generating control data for controlling an agricultural apparatus for treating an agricultural field, comprising gathering a digital representation of at least one portion of the agricultural field; analysing the digital representation of the at least one portion of the agricultural field comprising a plant to determine a height of the plant; determining a treatment for the plant in dependence on the determined height; and generating the control data for controlling the agricultural apparatus to apply the treatment to the plant; and providing the control data for controlling the agricultural apparatus; and a corresponding computer-program product, data processing apparatus, digital treatment map, method for controlling an agricultural apparatus, and agricultural apparatus.

Description

[0001] METHOD AND APPARATUS FOR GENERATING CONTROL DATA FOR CONTROLLING AN AGRICULTURAL APPARATUS FOR TREATING AN AGRICULTURAL FIELD, PRODUCT, DIGITAL TREATMENT MAP, METHOD FOR CONTROLLING AN AGRICULTURAL APPARATUS, AND AGRICULTURAL APPARATUS

[0002] TECHNICAL FIELD

[0003] The invention relates in general to digital farming, particularly to precision farming, and more particularly to a computer-implemented method for generating control data for controlling an agricultural apparatus (treatment apparatus) for treating an agricultural field, and a corresponding computer-program product, data processing apparatus, digital treatment map, method for controlling an agricultural apparatus, and agricultural apparatus.

[0004] TECHNICAL BACKGROUND

[0005] The present disclosure relates, in general terms, to precision farming. In order to maximize yield, reduce costs and reduce environmental impact, agricultural production has, among other things, to minimize use of agronomic products, such as treatment products comprising crop protection products and nutrition products. Knowledge about suitable treatment actions and I or appropriate amounts of treatment products has been subject of long-term studies and experiments. Precision farming uses digital technologies comprising digital products and I or digital services for monitoring, controlling and documenting agricultural production, in order to make the agricultural production more sustainable. Rules for selecting treatment actions and I or amounts of treatment products have been available in digital products and I or services, for example, such as cloud-computing platforms or field managing cloud platform.

[0006] An object of the present disclosure is to provide a method and an apparatus for improved treatment of an agricultural field, which allow for reduction of environmental burden and I or ecological damage.

[0007] SUMMARY

[0008] In an aspect, the disclosure relates to a computer-implemented method for generating control data for controlling an agricultural apparatus for treating an agricultural field, comprising gathering a digital representation of at least one portion of the agricultural field; analysing the digital representation of the at least one portion of the agricultural field comprising a plant to determine a height of the plant; determining a treatment for the plant in dependence on the determined height; generating the control data for controlling the agricultural apparatus to apply the treatment to the plant; and providing the control data for controlling the agricultural apparatus. The method may provide for a measurement, or at least of an estimate, of the plant, in particular a measurement, or at least of an estimate, of a height of the plant.

[0009] For example, the height of a weed in an agricultural field may have different impacts to the quantity of an agronomic product, for example fungicide and herbicide, provided by the treatment device. Higher weed may need a higher dosage of the agronomic product than lower weed. Determining, or detecting or estimating, the height of the weed may help to adjust a spray pattern and I or dosage rate for the portion, or sub-area, of the agricultural field to be sprayed in dependence on the determined height of the weed. Thus, the method may provide for a more precise adaptation of the treatment product, and waste of treatment product, on the agricultural field and I in the tank, may be reduced. The method may avoid scape of weed, thus, subsequent treatment and use of additional treatment product. A user, e. g. farmer, of the method may benefit from savings, e. g. in form of cost and I or time.

[0010] Thus, the method may provide for treating the agricultural field tailored to individual plants, and thus efficient treatment, precise treatment, reduced waste, reduced environmental burden and I or ecological damage. In other words, substantially the quantity of the agronomic product for treating the plant or for destroying the plant dependent on the height of the plant may be provided. Treating a plant may comprise providing a growth controlling product, a herbicide, fungicide or a fertilizer.

[0011] The method may gather the digital representation from a sensor, an interface or a network interface, for example. The method may provide the control data via an interface. The sensor may comprise at least one of an image sensor and a camera, for example. The sensor may be located on at least one of the agricultural apparatus, an aircraft, an uncrewed aerial vehicle (UAV, drone), a spacecraft or a satellite, for example. In other words, the sensor may be attached to the agricultural apparatus and I or released from the agricultural apparatus.

[0012] The least one portion of the agricultural field may be referred to as at least one of a region of interest (ROI), intrafield, zone, sub-area and spot, for example. The at least one portion of the agricultural field may cover a relatively small area of the agricultural field in case that, for example, the sensor is located on the agricultural apparatus. The at least one portion of the field may cover a relatively large area or the whole area of the agricultural field, in case that, for example, in case the sensor is located on the aircraft, UAV, spacecraft or satellite.

[0013] The interface(s) may be mechanical interface(s), such as a plug and socket, a wire-based interface and / or a wireless interface. The interface(s) may comprise at least one of a bus, industrial bus, fieldbus, process fieldbus (Profibus), vehicle bus, controller area network (CAN) bus, tractors and machinery for agriculture and forestry serial control and communications data network bus (ISOBUS), universal serial bus (USB), cloud interface, database interface, network interface, storage interface, local area network (LAN), wireless local area network (WLAN), Wi-Fi and mobile network, for example. The control data may be implemented as at least one of control signals, a height map and a treatment map, for example. The method may use devices that are already mounted and I or installed on the agricultural apparatus. Thus, the method may help to avoid a need for an additional device, or additional device, and, thus, additional weight of the agricultural apparatus.

[0014] In an aspect, the disclosure relates to a computer-program product, comprising instructions which, when executed by a data processing apparatus, cause the data processing apparatus to carry out the computer-implemented method. The computer-program product may provide for a measurement, or at least of an estimate, of the plant, in particular a measurement, or at least of an estimate, of a height of the plant. Thus, the computer-program product may also provide for treating the agricultural field tailored to individual plants, and thus efficient treatment, precise treatment, reduced waste, reduced environmental burden and I or ecological damage.

[0015] In an aspect, the disclosure relates to a data processing apparatus for generating control data for controlling an agricultural apparatus for treating an agricultural field, comprising an input device for gathering a digital representation of at least one portion of the agricultural field; a processing device for analysing the digital representation of the at least one portion of the agricultural field comprising a plant to determine a height of the plant, determining a treatment for the plant in dependence on the determined height, and generating control data for controlling the agricultural apparatus to apply the treatment to the plant; and an output device for providing the control data for controlling the agricultural apparatus. The data processing apparatus may provide for a measurement, or at least of an estimate, of the plant, in particular a measurement, or at least of an estimate, of a height of the plant. Thus, the data processing apparatus may also provide for treating the agricultural field tailored to individual plants, and thus efficient treatment, precise treatment, reduced waste, reduced environmental burden and I or ecological damage.

[0016] In an aspect, the disclosure relates to a digital treatment map comprising control data for controlling an agricultural apparatus for treating an agricultural field, obtained by the computer-implemented method. The digital treatment map may comprise control data obtained from a measurement, or at least of an estimate, of the plant, in particular a measurement, or at least of an estimate, of a height of the plant. Thus, the digital treatment map may provide for treating the agricultural field tailored to individual plants, and thus efficient treatment, precise treatment, reduced waste, reduced environmental burden and I or ecological damage.

[0017] In an aspect, the disclosure relates to a method for controlling an agricultural apparatus for treating an agricultural field, comprising receiving control data generated according to the computer-implemented method; and treating the agricultural field based on the received control data. The method may provide for a measurement, or at least of an estimate, of the plant, in particular a measurement, or at least of an estimate, of a height of the plant. Thus, the method may also provide for treating the agricultural field tailored to individual plants, and thus efficient treatment, precise treatment, reduced waste, reduced environmental burden and I or ecological damage. Treating the agricultural field based on the received control data may treat the plant on the agricultural field.

[0018] In an aspect, the disclosure relates to an agricultural apparatus, comprising a receiving device for receiving control data generated according to the computer-implemented method; and a treatment device for applying the agricultural field in accordance with the received control data. The agricultural apparatus may be controlled by control data obtained from a measurement, or at least of an estimate, of the plant, in particular a measurement, or at least of an estimate, of a height of the plant. Thus, the agricultural apparatus may also provide for treating the agricultural field tailored to individual plants, and thus efficient treatment, precise treatment, reduced waste, reduced environmental burden and I or ecological damage. The agricultural apparatus may be one of an agricultural machine, a tractor, an agricultural tractor, a driverless tractor, a pedestrian-controlled tractor, a walk-behind tractor, an autonomous vehicle, an autonomous drawing vehicle, a robot, a combine I harvester I combine harvester, a planter, a seeder, a seed drill, a sprayer, a grubber, a trailer, an irrigation system, an overhead irrigation system, a spray-irrigation system, a circular irrigation system and a linear irrigation system, for example.

[0019] The receiving device may receive the control data via an interface. The interface may comprise at least one of a bus, industrial bus, fieldbus, Profibus, vehicle bus, CAN bus, ISOBUS, USB, cloud interface, database interface, network interface, storage interface, LAN, WLAN, Wi-Fi and mobile network, for example. The treatment device may be at least one of a nozzle, nozzle arrangement, seeding device, drilling device, planting device, cutting knife and harvesting device, for example. The nozzle may be directed substantially vertically to a surface of the agricultural field in order to generate a predefined shape of a spray pattern on the surface and I or the plant to be treated. The spray pattern may be adjusted to the surface and I or a predefined height of the plant. The seeding device may be used for distributing seeds on an agricultural field. The cutting knife may be used for cutting crops. The harvesting device may be used for collecting yield of an agricultural field. The method may determine the determine the height of the plant to be harvested, i. e. the crops, and determining the treatment for the plant may comprise determining a height of the treatment device, i. e. cutting knife, to adapt to the plant.

[0020] In an aspect, the disclosure may describe a height measuring method and I or a height measuring device and, in this way, may convert physical states of an environment in a digital representation in form of data.

[0021] EMBODIMENTS

[0022] In the following, embodiments of the present disclosure will be outlined by ways of examples. It is to be understood that the present disclosure is not limited to said embodiments and I or examples.

[0023] In an embodiment of the computer-implemented method, analysing the digital representation comprises at least one of analysing the digital representation to classify the plant as one of crop and weed; analysing the digital representation to identify the plant's species; and analysing the digital representation to determine the plant's growth status. The method may provide for treating tailored to the plant, and thus appropriate treatment, reduced environmental burden and I or ecological damage. The method may determine to not treat the plant. For example, the knowledge about suitable treatment actions may suggest that the treatment product available would not provide for suitable treatment of the plant.

[0024] In an embodiment of the computer-implemented method, the treatment for the plant is at least one of a chemical treatment, biological treatment and mechanical treatment dependent on a result of analyzing the digital representation. The method may select a most suitable treatment from a plurality of available treating actions. In an embodiment, the computer-implemented method further comprises determining a treatment product for the plant dependent on the result of analyzing the digital representation. Determining the treatment product may comprise determining at least one of an agronomic product, a concentration of the agronomic product and an amount of the treatment product comprising the determined agronomic product in the determined concentration for treating the agricultural field. The method may provide for treating the agricultural field tailored to the plants.

[0025] In an embodiment of the computer-implemented method, the treatment for the plant is determined in further dependence on at least one of the plant being classified as crop; the plant being classified as weed; the identified species; and the determined growth status. The method may provide for treating tailored to the individual plants. Classifying a plant as crop or weed may be made by using a row detection, e. g. in cases when crop may be planted in physical rows, and I or by image recognition. The growth status may be allocated to the BBCH-scale (Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie) which may be used to identify the phenological development stage of the plant. In this way, it may be possible to identify the age of the plant by converting height to a corresponding growth stage.

[0026] In an embodiment of the computer-implemented method, determining the treatment for the plant comprises at least one of determining a treatment action for the treatment; determining a treatment agent for the treatment; and determining a treatment parameter for the treatment. The method may provide for improved control of the agricultural apparatus.

[0027] In an embodiment of the computer-implemented method, determining the treatment agent comprises at least one of determining an agricultural product; determining an amount of the agricultural product; determining a volume of the agricultural product; determining a concentration of the agricultural product; and determining a dosage of the agricultural product. The method may provide for simplified treatment of the agricultural field, reduction of mistreatment of the agricultural field and I or reduction of errors.

[0028] In an embodiment of the computer-implemented method, at least one the analysing the digital representation, determining the treatment and generating the control data is performed using at least one of artificial intelligence (Al); generative artificial intelligence; machine learning (ML); deep learning; an artificial neural network (ANN); and a large language model (LLM). The method may provide for improved processing, better results and I or better treatment of the agricultural field.

[0029] In an embodiment of the computer-implemented method, at least one the analysing the digital representation, determining the treatment and generating the control data is performed by a processor. The method may provide for improved processing and I or digital processing.

[0030] In an embodiment of the computer-implemented method, the processor is arranged at a location comprising at least one of the agricultural apparatus; a mobile device; a mobile phone; and cloud computing. The method may provide for use of an available resource, processing in proximity to the agricultural field, reduction of processing congestion, reduction of network congestion and I or reduction of lagging.

[0031] In an embodiment of the computer-implemented method, the digital representation is a digital image of the agricultural field generated with an imaging sensor; and analysing of the digital representation comprises at least one of determining, from the digital image, a length of a projection of the plant on the agricultural field; and determining the height of the plant in dependence on the determined length of the projection. The method may provide for use of an available image sensor, such as a camera of a mobile phone, simplified processing and or faster processing.

[0032] The digital image may comprise picture elements (pixels). The pixels may represent the agricultural field with at least one of black and white values, grey (gray) scale values, colour (color) values, red green blue (RGB) values, and infrared (IR) values. The method may use available image formats, select a suitable image format and thus use available processing functions. The method may select the suitable image format in dependence on at least one of the digital representation, required processing, available resources and work load.

[0033] In an embodiment of the computer-implemented method, the projection of the plant on the agricultural field is a shadow where radiation from a radiation source is blocked by the plant. The method may be compatible with an existing radiation source and a plurality of radiation sources. The method may use relatively simple processing functions, for example trigonometric functions. A location, where the plant emerges from a surface (ground) of the agricultural field, (foot) may determine coordinates of the plant on the agricultural field. The location may determine a starting point (base) of the shadow. A top end (head) of the plant may mark an endpoint (head) of the shadow on the surface. The radiation source may be located at least one of on the agricultural apparatus, on a vehicle being separate from the agricultural apparatus, on an aircraft, on an UAV, on a structure that may be mobile or immobile, and in space.

[0034] In an embodiment of the computer-implemented method, determining the length of the projection comprises at least one of determining a vertical distance of the radiation source from the agricultural field; determining a horizontal distance of the radiation source from the plant; determining the length of the projection in dependence on the determined horizontal distance of the radiation source; and determining the length of the projection by comparing the projection with a feature in the digital image, having a known length. The method may be compatible with an existing radiation source or a plurality of radiation sources.

[0035] In an embodiment of the computer-implemented method, determining the height of the plant comprises at least one of determining the height of the plant in dependence on the determined vertical distance of the radiation source, determined horizontal distance of the radiation source and determined length of the projection; and determining the height of the plant from the determined vertical distance of the radiation source multiplied by the determined length of the projection divided by a sum of the determined length of the projection and determined horizontal distance of the radiation source. The method may use a relatively simple function. In an embodiment of the computer-implemented method, determining the height of the plant comprises at least one of determining a relative position of the radiation source to the plant; determining an elevation angle of the radiation source over the agricultural apparatus; determining the height of the plant in dependence on the determined elevation angle and determined length of the projection; determining the height of the plant from the determined length of the projection multiplied by the tangent of the determined elevation angle; and determining the height of the plant from the determined length of the projection divided by the cotangent of the determined elevation angle. The method may be compatible with an existing radiation source, such as a natural radiation source, and may be adaptive to changes in the elevation angle. The elevation angle may change in dependence of day of time and I or time of year, for example.

[0036] In an embodiment of the computer-implemented method, determining the relative position of the radiation source comprises at least one of obtaining a time of origin of the digital image; obtaining position information of the radiation source for the time of origin; and determining the relative position independence on the obtained position information. The method may be adaptive to position changes of the radiation source.

[0037] In an embodiment of the computer-implemented method, determining the length of the projection further comprises at least one of determining a vertical distance of the imaging sensor from the agricultural field; determining a horizontal distance of the imaging sensor from the plant; determining a viewing angle of the imaging sensor to the plant. The method may be adaptive to position changes of the image sensor.

[0038] In an embodiment of the computer-implemented method, determining the height of the plant further comprises determining the height of the plant in further dependence on at least one of the determined vertical distance of the imaging sensor; the determined horizontal distance of the imaging sensor; and the determined viewing angle of the imaging sensor.

[0039] In an embodiment of the computer-implemented method, the radiation comprises light. The method may allow to use a relatively simple radiation source and I or a relatively simple imaging sensor. The light may have a predetermined frequency.

[0040] In an embodiment of the computer-implemented method, the light comprises at least one of ultraviolet light; visible light; near-infrared light; infrared light; invisible light; monochrome light; multi-coloured light; and a light spectrum, such as white light. The method may use light suitable for plants. In an example, the light may be adapted to eliminate interfering radiation sources. For instance, the position of a radiation source such as sun and I or moon may substantially be out of access of any measures to control the light generated by such a source. However, the light generated by such an exterior radiation source may have impact to determining the shadow of the plant. In an example, the radiation may originate from a point located in the moving direction of the agricultural apparatus. In this way, the shadow may be generated directing against the moving direction and may substantially partially not be detectable in the sight field of a camera. Thus, a controllable radiation source, e. g. a radiation source mounted on the agricultural device, may illuminate the plant such that the shadow may be directed in the moving direction of the agricultural apparatus and may dominate the shadow generated by the sun. The controllable radiation source may determine an illumination intensity, illumination wavelength and I or illumination direction and may be aligned with the camera. For example, a controllable radiation source may use IR (infra-red) radiation and the camera may be an IR camera adapted to the wavelength of the controllable radiation source and thus may allow for controlling the shadow independently from the exterior radiation source.

[0041] In an embodiment of the computer-implemented method, the radiation source comprises a light source. The method may be compatible with a relatively simple light source, relatively common light source and I or existing light source.

[0042] In an embodiment of the computer-implemented method, the light source comprises at least one of a natural light source; and an artificial light source. The light source may emit the light with the predetermined frequency. The method may be compatible with a suitable light source. The natural light source may be an existing light source. The artificial light source may be more versatile and I or controllable than the natural light source. The artificial light source may allow to obtain a shadow of the plant on the agricultural field in darkness, at night, during overcast weather and / or in an interior space, such as inside a building, vault and tunnel.

[0043] In an embodiment of the computer-implemented method, the natural light source comprises the sun. The method may benefit from the sun being a free light source.

[0044] In an embodiment of the computer-implemented method, the artificial light source comprises at least one of a lightemitting diode (LED); a matrix of light-emitting diodes; an IR radiator; and a laser. The method may benefit from a versatile, controllable, ubiquitous and relatively low-priced light source.

[0045] In an example where an IR radiator may be used, the height measurement may be executed at substantially the same time when a soil quality and I or a vegetation index may be determined, such as NDVI (Normalized Difference Vegetation Index) and I or LAI (Leaf-Area-Index). In this way a combination sensor may be implemented.

[0046] In a further example, the height measurement and I or vegetation index measuring may be used for controlling a threshold for applying an agricultural product and I or a usage rate of an agricultural product.

[0047] In an embodiment of the computer-implemented method, the artificial light source is configured to generate the light at least as one of switched light; pulsed light; and modulated light. The method may benefit from different modes of operation of the artificial light source. For example, the method may synchronise the artificial light source with the image sensor, to establish a relationship between the light emitted from the artificial light source and image generated by the image sensor. In an embodiment of the computer-implemented method, the artificial light source is mounted to at least one of the agricultural apparatus; a I the mobile device; a I the mobile phone; a structure; a wheeled vehicle; a track vehicle; a rail-bound vehicle; a watercraft; an uncrewed aerial vehicle; an aircraft; a spacecraft; and a satellite. The method may be adapted to a particular use case. For example, the method wherein the artificial light source is mounted to the agricultural apparatus may provide for a direct and simple treatment of the agricultural field, wherein the method determines the treatment while the agricultural apparatus traverses the agricultural field. The artificial light source may be mounted to a boom of the agricultural apparatus. A plurality of artificial light sources may be arranged along the boom, spaced apart at approximately equal distances. The boom may extend perpendicular to a locomotion direction, e. g. driving direction or heading, of the agricultural apparatus. The boom may be arranged at a height of about 0.50 m above a surface of the agricultural field. The boom may extend about 15 m to each side of the agricultural apparatus. The method wherein the artificial light source is mounted to the mobile device or mobile phone may provide for a treatment of the agricultural field, wherein the method gathers the digital representation of the at least one portion of the agricultural field locally before the agricultural apparatus traverses the agricultural field. The method wherein the artificial light source is mounted to the uncrewed aerial vehicle, aircraft, spacecraft or satellite may provide for a treatment of the agricultural field, wherein the method gathers the digital representation of the at least one portion of the agricultural field remotely and or automatically before the agricultural apparatus traverses the agricultural field; and the method may monitor the agricultural field and I or trigger the treatment.

[0048] An embodiment of the computer-implemented method further comprises controlling the imaging sensor to generate the digital image. The method may provide for improved flexibility of the treatment.

[0049] In an embodiment of the computer-implemented method, the imaging sensor is configured to generate the digital image as at least one of grey-scale digital image; colour digital image; and a false colour. The method may provide for a suitable image format.

[0050] In an embodiment of the computer-implemented method, the imaging sensor is mounted to at least one of the agricultural apparatus; a I the mobile device; a I the mobile phone; a I the structure; a I the wheeled vehicle; a I the track vehicle; a I the rail-bound vehicle; a I the watercraft; an I the uncrewed aerial vehicle; an I the aircraft; a I the spacecraft; and a I the satellite. The method may be adapted to a particular use case. For example, the method wherein the image sensor is mounted to the agricultural apparatus may provide for a direct and simple treatment of the agricultural field, wherein the method determines the treatment while the agricultural apparatus traverses the agricultural field. The image sensor may be mounted to the boom of the agricultural apparatus. A plurality of image sensors may be arranged along the boom, spaced apart at approximately equal distances. The method wherein the image sensor is mounted to the mobile device or mobile phone may provide for a treatment of the agricultural field, wherein the method gathers the digital representation of the at least one portion of the agricultural field locally before the agricultural apparatus traverses the agricultural field. The method wherein the image sensor is mounted to the uncrewed aerial vehicle, aircraft, spacecraft or satellite may provide for a treatment of the agricultural field, wherein the method gathers the digital representation of the at least one portion of the agricultural field remotely and or automatically before the agricultural apparatus traverses the agricultural field; and the method may monitor the agricultural field and I or trigger the treatment.

[0051] In an embodiment of the computer-implemented method, the digital representation is a point cloud generated from the agricultural field; and analysing of the digital representation comprises determining, from the point cloud, the height of the plant on the agricultural field in dependence on a surface of the agricultural field. The method may provide a sophisticated analyzing of the digital representation. The point cloud is a set, i. e. collection, of data points in a 3-dimensional (3D) coordinate system, and each data point of the set of data points has x, y, z coordinates and a value such as an intensity value or a colour value generated for the data point, and represents a precise location in the space of the 3D coordinate system. The point cloud creates a 3D representation, i. e. model, of an area such as the agricultural field or an object such as a building.

[0052] In an embodiment of the computer-implemented method, the point cloud is a Lidar point cloud. The method may benefit from use of Lidar, as Lidar may provide a precise digital representation.

[0053] An embodiment of the computer-implemented method further comprises controlling a Lidar sensor to generate the Lidar point cloud. The method may provide for improved generation of the control data.

[0054] In an embodiment of the computer-implemented method, the Lidar sensor is mounted to at least one of the agricultural apparatus; a I the mobile device; a I the mobile phone; a structure; a wheeled vehicle; a track vehicle; a rail-bound vehicle; a watercraft; an uncrewed aerial vehicle; an aircraft; a spacecraft; and a satellite. The method may be adapted to a particular use case. For example, the method wherein the Lidar sensor is mounted to the agricultural apparatus may provide for a direct and simple treatment of the agricultural field, wherein the method determines the treatment while the agricultural apparatus traverses the agricultural field. The Lidar sensor may be mounted to the boom of the agricultural apparatus. A plurality of Lidar sensors may be arranged along the boom, spaced apart at approximately equal distances. The method wherein the Lidar sensor is mounted to the mobile device or mobile phone may provide for a treatment of the agricultural field, wherein the method gathers the digital representation of the at least one portion of the agricultural field locally before the agricultural apparatus traverses the agricultural field. The method wherein the Lidar sensor is mounted to the uncrewed aerial vehicle, aircraft, spacecraft or satellite may provide for a treatment of the agricultural field, wherein the method gathers the digital representation of the at least one portion of the agricultural field remotely and or automatically before the agricultural apparatus traverses the agricultural field; and the method may monitor the agricultural field and I or trigger the treatment.

[0055] An embodiment of the method for controlling an agricultural apparatus further comprises controlling a treatment device of the agricultural apparatus to apply the determined treatment to the agricultural field. The method may provide for an improved control of the treatment device, or an individual treatment device of a plurality of treatment devices, and, thus, for a more precise treatment of the plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In the following, the present disclosure is further described with reference to the enclosed figures. The same reference numbers in the drawings and this disclosure are intended to refer to the same or like elements, components, and I or parts.

[0057] Fig. 1 illustrates a distributed computing environment for controlling an agricultural apparatus 102 for treating an agricultural field 108;

[0058] Fig. 2 illustrates an agricultural apparatus 102;

[0059] Fig. 3 illustrates a treatment system 107;

[0060] Fig. 4 illustrates an agricultural apparatus 102 for treating an agricultural field 108; and

[0061] Fig. 5 illustrates a flow chart of a computer-implemented method 200 for generating control data for controlling an agricultural apparatus 102 for treating an agricultural field 108.

[0062] DETAILED DESCRIPTION

[0063] The following embodiments are mere examples for implementing the method, computer-program product, data processing apparatus, digital treatment map and agricultural apparatus disclosed herein and shall not be considered limiting.

[0064] In the claims as well as in the description the word "comprising” or "including” or similar wording does not exclude other elements or steps and shall not be construed limiting to the elements or steps lined out. The indefinite article "a” or "an” does not exclude a plurality. A single element or other unit may fulfill the functions of several entities or items recited in the claims. The mere fact that certain measures are recited in the mutual different dependent claims does not indicate that a combination of these measures cannot be used in an advantageous implementation or further elements may be included.

[0065] DEFINITIONS

[0066] The term "agricultural field” presents any area, i. e. surface and sub-surface, of a soil to be treated. The agricultural field may be any plant or crop cultivation area, such as a farming field, greenhouse or the like. The "plant” presents any plant present on the agricultural field including but not limited to a crop, weed, volunteer plant, crop from a previous growing season and I or beneficial plant. The agricultural field may be identified through its geographical location or geo-referenced location data. A reference coordinate, size and I or shape may be used to further specify the agricultural field.

[0067] The term "seeding”, or "planting”, presents any action to put, place or bring in seeds in a soil area of an agricultural field. Seed, e. g. seed grain or seed fruit, is any biological plant material that refers to dry, dormant, generative reproductive organs, such as seeds, fruits, pseudo-fruits, infructescences or parts thereof. Seeds contain the complete germ system of the plants, created by fertilization, and contains germination and growth potential.

[0068] The term "planting” presents any action to put, place or bring in a grown plant and I or seedling in a soil area of an agricultural field. Seedlings are young sporophyte developing out of a plant embryo from a seed.

[0069] The term "fertilizing” presents any action to put, place or bring in fertilizers in a soil area of an agricultural field. A fertilizer is any material of natural origin and I or synthetic origin, that is applied to a soil or plant tissues to supply plant nutrients.

[0070] The term "treatment product” represents any object or material useful for the treatment. In the context of the present disclosure, the term "treatment product” includes, but is not limited to, any chemical product, such as fungicide, herbicide, insecticide, acaricide, molluscicide, nematicide, avicide, piscicide, rodenticide, repellant, bactericide, biocide, safener, plant growth regulator, urease inhibitor, nitrification inhibitor, denitrification inhibitor, or any combination thereof; any biological product, such as microorganisms useful as fungicide (biofungicide), herbicide (bioherbicide), insecticide (bioinsecticide), acaricide (bioacaricide), molluscicide (biomolluscicide), nematicide (bionematicide), avicide, piscicide, rodenticide, repellant, bactericide, biocide, safener, plant growth regulator, urease inhibitor, nitrification inhibitor, denitrification inhibitor, or any combination thereof; fertilizer and nutrient; and also seeds; seedlings; plants; water; and any combination thereof.

[0071] The term "application apparatus” represents any agricultural apparatus being configured to provide I spread seeds, plants and I or fertilizers onto a soil of an agricultural field. The application apparatus may be configured to traverse the agricultural field. The application apparatus may be a ground vehicle, e. g. a tractor or rail vehicle, an air vehicle, e. g. an aircraft or unmanned aerial vehicle (UAV), a robot or the like. The application apparatus can be an autonomous application apparatus or a non-autonomous application apparatus.

[0072] The term "treatment system”, or "application system”, represents any system or sub-system of the agricultural apparatus, e. g. application apparatus. This treatment system may be fixedly connected to the agricultural apparatus and comprise actuators, sensors and I or additional components being able to provide the treatment action or treatment operation. The treatment system may comprise a holder or mounting device for a treatment device. The treatment system is mounted, coupled or arranged directly at the agricultural apparatus. The treatment system may comprise an electrical and I or mechanical interface for connecting the treatment system with the agricultural apparatus. For example, the treatment system may include, but is not limited to, a sprayer boom, a fertilizer spreader boom, an arm of a seeder, a disc spreader with section control, a cutting arm of a harvester. At least one treatment device or application device, in particular a plurality of treatment devices or application devices, may be arranged at the treatment system.

[0073] The term "treatment device” represents any device or apparatus being configured to treat an agricultural field or apply a treatment product onto the agricultural field. For example, the treatment device may be at least one outlet or a plurality of outlets, e. g. nozzles of a sprayer or spreader, coulters of a planter for applying the treatment products onto the agricultural field. The treatment device(s) may be arranged at the treatment system of an application apparatus. Further, the treatment device may be a section of the application system comprising a plurality of single treatment devices. The treatment device may be a cutting device in case of a harvester, for example.

[0074] Fig. 1 illustrates a distributed computing environment for controlling an agricultural apparatus 102 for treating an agricultural field 108.

[0075] The distributed computing environment comprises one or more remote computing resources including at least one of a remote server 106, field management system 110, such as an agronomic decision-making engine (agronomical decision engine, ADE), and personal computing device 112, such as mobile phone, hand-held device (tablet computer, tablet) or personal computer. The remote server 106 may offer a cloud-based service.

[0076] The agricultural field 108 comprises a plurality of geographical locations (portions, sub-areas, zones, spots) 108a, 108b, 108c, 108d, each of which accommodating one or more plants. As illustrated in Fig. 1, the plurality of geographical locations comprises a first geographical location 108a accommodating a crop plant 114; a second geographical location 108b accommodating a crop plant and weed plant; a third geographical location 108c accommodating another weed plant, and a fourth geographical location 108d accommodating another crop plant.

[0077] Fig. 1 will be described with reference to a spraying application as an exemplary treatment action. The farming operation may relate to treatment for a crop comprising the crop plant 114 and the other crop plant. Alternatively or additionally, the farming operation may relate to control or eradication of the weed plant and other weed plant.

[0078] The agricultural apparatus 102 comprises a treatment system 107. The treatment system 107 comprises a treatment device (treatment unit) 107 for performing and I or conducting an agricultural farming operation on the agricultural field 108. The agricultural apparatus 102 further comprises a connectivity interface 104 and a computing unit (not shown explicitly in Fig. 1). The connectivity interface 104 may be either a part of a network interface or separate unit. For ease of description, it is assumed that the connectivity interface 104 is part of the network interface. The connectivity interface 104 is operatively coupled to the computing unit. The computing unit is operatively connectable to the treatment device 107a. The connectivity interface 104 is configured to communicatively couple the agricultural apparatus 102 the distributed computing environment. The connectivity interface 104 may be configured to provide field-specific data to the computing unit. Moreover, the connectivity interface 104 may also be configured to provide update data, for example data collected at the treatment device 107a to any one or more of the remote computing resources. Any one or more of the computing resources may be a data management system configured to send data to the treatment device 107a and I or receive data from the treatment device 107a. For example, the update data recorded during the farming operation on the first geographical location 108a may be sent as detected map or farming operation map from the agricultural apparatus 102 to the remote server 106.

[0079] Data of the map(s) may be provided in at least one of ISOxml format (ISO11783 is a communication protocol for the agricultural machines based on CAN Bus, more specific: the SAE J1939), shape format (*.shp) and EFDI (Extended farm management information systems data interface), for example.

[0080] The field management system 110 may be configured to provide at least one of a control protocol, an activation code or a decision logic, and field-specific data to the agricultural apparatus 102, or to receive data, for example update data, from the agricultural apparatus 102. Any one or more of the computing resources may implement the field management system 110. Alternatively or additionally, such data may be received by the field management system 110 via the remote server 106 or data management system.

[0081] Any one or more of the computing resources may be a client computer. The client computer may be configured to receive client data from the field management system 110 and / or the agricultural apparatus 102. The client data may include, for example, a farming operation schedule to be conducted on one or more agricultural fields 108 or on the plurality of geographical locations 108a, 108b, 108c, 108d with the agricultural apparatus 102 and I or the treatment system 107 of the agricultural apparatus 102, or field analysis data to provide insights into a health state of certain one or more geographical locations 108a, 108b, 108c, 108d or agricultural fields 108. The client computer may also refer to a plurality of devices, for example a desktop computer and I or one or more mobile devices such as a smartphone, tablet computer and I or smart wearable device. The treatment device 107a may be equipped with a computing unit, or the computing unit may be a mobile device that can be connected to the treatment device 107a via the connectivity interface 104. It will be appreciated that remote server 106 may implement the field management system 110. The computing unit may receive the field-specific data either via the client computer, or it may receive it directly from the remote server 106 or the field management system 110.

[0082] When data such as update data is recorded by the agricultural apparatus 102, such data may be distributed to any one or more of the computing resources of the distributed computing environment.

[0083] Although Fig. 1 has been described with reference to the spraying application as an exemplary treatment action, it will be understood that a description of another treatment action such as a seeding application may be similar to the description of the spraying application.

[0084] Fig. 2 illustrates an agricultural apparatus 102 with a treatment system 107. The treatment system 107 comprises a nozzle arrangement 122 comprising a plurality of nozzles. The nozzles of the plurality of nozzles may be mounted on boom 120, support or nozzle holder, for example. As shown in Fig. 2, the nozzle arrangement 122 comprises four nozzles serving as the treatment devices 107a. The nozzles may be individually selected by individually switching on and I or off the corresponding nozzle. As will be understood, by individually switching on and off individual nozzles in combination with locomotion in a predefined direction, i. e. a driving direction, of the agricultural apparatus 102. The boom may be arranged at a height of about 0.50 m above a surface of the agricultural field 108. A spray pattern (footprint) may be generated substantially underneath each nozzle. The spray pattern may have a substantially rectangular shape. In this way, it may be possible to generate substantially a grid pattern comprising a plurality of grid portions on the surface of the agricultural field 108 where substantially the same treatment may be executed and I or achieved within each grid portion of the plurality of grid portions. The grid portions coincide with the geographical locations 108a, 108b, 108c and 108d. In this way, the grid portions may substantially correspond to the portions, sub-areas, zones and I or spots of the agricultural field 108.

[0085] Fig. 3 illustrates a treatment system 107. The treatment system 107 may be a large-scale treatment system. As shown in Fig. 3, the treatment system 107 may implement a field sprayer, and comprise a plurality of treatment devices 107a, such as spray nozzles or product tanks 107c, 107d, 107e and sensor devices 107h, for example. The field sprayer may be part of the agricultural apparatus 102 shown in Fig. 1 . The field sprayer may be configured to apply a treatment product to the agricultural field 108, or to one or more geographical locations 108a, 108b, 108c, 108d thereof. The field sprayer may be releasably attached or directly mounted to the agricultural apparatus 102. In at least some embodiments, the field sprayer comprises a boom 120 with a plurality of nozzles spray nozzles arranged along the boom 120. The spray nozzles may be fixed or attached movably along the boom 120 in regular intervals or irregular intervals. Each spray nozzle may be arranged together with one or more, preferably separately, controllable valves 107b to regulate fluid release from the spray nozzles to the agricultural field 108.

[0086] The product tank(s) 107c, 107d, 107e may be placed in a housing 107f and are in fluid communication with the nozzles via one or more fluidic lines 107g and the one or more valves 107b. The fluidic lines 107g distribute one or more treatment products or composition ingredients such as water to the spray nozzles. The treatment product(s) may include chemically active ingredients or inactive ingredients like a treatment product or mixture, individual ingredients of the treatment product or mixture, a selective or non-selective treatment product, a fungicide, ingredients of a fungicide mixture, a plant growth regulator, ingredients of a plant growth regulator mixture, water, oil, or any other treatment product. Each product tank 107c, 107d, 107e may further comprise a controllable valve to regulate fluid release from the product tank 107c, 107d, 107e to the fluid line(s) 107g. The spray patterns are provided by control data to the treatment system 107. The control data may be provided as a treatment map.

[0087] The treatment system 107 may further comprise a detection device 107h for verifying the provided spray dosage with the current local condition detected with detection device 107h. The detection device107h enables the treatment system 107 to monitor, sense and I or detect an actual situation in proximity to the treatment system 107. For that purpose, the detection device 107h may comprise a plurality of detection units (detecting units, sensor units, monitoring units) 107i arranged along the boom 120. The detection units 107i may be fixed or attached movably along the boom 120 in regular intervals or irregular intervals. The detection units 107i may be configured to sense field data and to derive one or more conditions of the agricultural field 108. A condition may be presence of a plant 107j, for example. The detection units 107i may be optical detection components providing images of the agricultural field 108, in particular of a field of view er region of interest (ROI). In an example, the shape of the ROI may substantially correspond to the shape of the geographical locations 108a, 108b, 108c, 108d of the agricultural field 108.

[0088] An optical detection component may comprise at least one of a multispectral camera, stereo camera, infrared (IR) camera, charge-coupled device (CCD) camera, hyperspectral camera, ultrasonic camera and light detection and ranging system (Lidar) camera. Alternatively or additionally, the detection units 107i may comprise further sensors to measure humidity, light, temperature, wind, any other suitable environmental parameter data and I or any condition on the agricultural field 108.

[0089] The collected field data may be provided as operation data to a nozzle validation apparatus. From data obtained from an optical monitoring component, a target area may be determined. In some embodiments, a velocity of the agricultural apparatus 102 may be provided, and a nozzle is validated based on the determined target area and the provided velocity.

[0090] The detection units 107i, the valves of the product tanks 107c, 107d, 107e and I or nozzle valves 107b may be communicatively coupled to a processing device and I or control system 107k. The control system 107k may be located in the housing 107f. Alternatively, more than one control systems 107k may be distributed in the housing 107f. The control system(s) 107k may be communicatively coupled to the detection units 107i, the valves of the product tanks 107c, 107d, 107e and I or nozzle valves 107b. For example, the control system(s) 107k may be wired to the detection units 107i, the valves of the product tanks 107c, 107d, 107e and I or nozzle valves 107b. Alternatively, the control system(s) 107k may be wirelessly connected to the detection units 107i, the valves of the product tanks 107c, 107d, 107e and I or nozzle valves 107b.

[0091] The control system(s) 107k may be configured to control and I or monitor the detection units 107i, the valves of the product tanks 107c, 107d, 107e and I or nozzle valves 107b based on a control file or operation data provided as a control file, and I or following a communication control protocol. In this respect, the control system(s) 107k may comprise a plurality of electronic modules. Alternatively, the detection unit(s) 107i may provide the operation data. For example, a first electronic module of the plurality of electronic modules may be configured to control the detection units 107i to collect field data such as images of the agricultural field 108. A second electronic module of the plurality of electronic modules may be configured to analyze the collected field data such as the images to derive parameters for control of the valves of the product tanks 107c, 107d, 107e and I or nozzle valves 107b. A third electronic module of the plurality of electronic modules may be configured to receive the operation data to derive a control signal. Further electronic module(s) of the plurality of electronic modules may be configured to control the drive system, valves of the product tanks 107c, 107d, 107e and I or nozzle valves 107b based on the derived control signal. As described above, the treatment system 107 comprises or is communicatively coupled to the detection units 1071, such as image capturing devices, and is configured to provide one or more images of the ROI to the control system(s) 107k. The image(s) comprise image data, that can be processed by a data processing unit. Both capturing the image(s) by the detection unit 1071 and processing the captures image(s) by the control system 107k may be performed onboard or through communication means during operation of the treatment system 107, i. e. in real-time. Alternatively or additionally to the image data, any data or set of data from which field conditions are derivable may be used.

[0092] The treatment actions and I or amounts of treatment products may be based on rules. The rules may be made available in digital products and I or services, for example, such as cloud-computing platforms or field managing cloud platform have been available in digital products and I or services, for example, such as cloud-computing platforms or field managing cloud platform.

[0093] The rules may comprise at least one of ecological rules and economical rules. Applying and observing the ecological rules and economical rules may substantially be related to reducing a quantity of agronomic products applied and results in the technical effect of being more sustainable. Data and rules may be processed by an agronomic decisionmaking engine (agronomical decision engine, ADE). The ADE may be executed in a cloud platform. The ADE generates control data and provides the control data at an output interface. The ADE may provide the control data in form of a treatment map (application map) such as digital treatment may. The treatment map may comprise a dosage, a quantity of an agronomic product to be applied and I or an instruction for a treatment related to a geographical coordinate. The agricultural apparatus can be an autonomous agricultural apparatus or a non- autonomous agricultural apparatus. The agricultural apparatus may be a semi-automated agricultural apparatus or fully automated agricultural apparatus. The agricultural apparatus comprises a treatment device (an application device), or a plurality of treatment devices, and a processing device for controlling the treatment device. The treatment device(s) may be arranged on an application system. The application system may be located on, mounted on or fixed to the agricultural apparatus, for example. For example, the treatment device(s) may be located on I mounted to a boom extending perpendicular to a locomotion direction, e. g. driving direction or heading, of the agricultural apparatus.

[0094] The agricultural apparatus is controlled by the generated control data and applies agronomic products in accordance with the control data to an agricultural field, for example. For example, a digitally controlled spraying apparatus (sprayer) may be used to apply a liquid agronomic product to an agricultural field. A digitally controlled seeding apparatus (seeder) may be used for applying seeds to an agricultural field. The agricultural apparatus may be configured to traverse the agricultural field. The treatment device may be adapted for one or more purposes of a plurality of different purposes of treatment of an agricultural field. A treatment device may be any device adapted to provide and I or spread seeds, plants and I or fertilizers onto soil of the agricultural field. The treatment of the agricultural field may comprise at least one of a chemical treatment, biological treatment and mechanical treatment of the agricultural field. The treatment may be comprise at least one of a treatment of the soil and a treatment of pants growing on the agricultural field.

[0095] The treatment device, or the agricultural apparatus, may comprise a single product tank (tank) I. e. a single product tank, for storing, transporting and I or providing a treatment product at a time. Treatment products may be different agronomic products or comprise a single agronomic product having different concentrations, for example. Thus, the treatment device, or the plurality of treatment devices, may be controlled to apply a first treatment product to the agricultural field at a time. The treatment device, or the plurality of treatment devices, may be controlled to apply a second treatment product to the agricultural field at another time.

[0096] For example, the treatment device(s) may be spraying device(s) for spraying the treatment product to the agricultural field. The spraying device(s) may be configured for treating at least one of weed, insects and pathogens on the agricultural field. The spraying device(s) may also be configured for spraying fertilizer to the agricultural field.

[0097] The treatment device, or the agricultural apparatus, may comprise more than one product tank for separately storing, transporting and I or providing one or more treatment products at a time. Thus, the treatment device, or the plurality of treatment devices, may be controlled to apply a first treatment product and a second treatment product to the agricultural field at substantially the same time.

[0098] The field treatment, soil treatment, seeding and plant treatment need to be applied with the correct treatment action(s) and I or amount(s) of treatment product(s).

[0099] Thus, while the technical objectives for robust, reliable and efficient treatment of agricultural fields or parts thereof remain, there are further technical objectives for precise treatment and fast treatment as well as reduction of waste, e. g. treatment product(s) remaining in the thanks after completion of the treatment of the agricultural field, reduction of environmental burden and reduction of ecological damage.

[0100] Fig. 4 illustrates an agricultural apparatus 102 for treating an agricultural field 108.

[0101] In addition to the plurality of nozzles mounted on the boom 120, the agricultural apparatus 102 further comprises, with reference to Fig. 2, a radiation source, in particular a light source 140, to emit light towards the surface of the agricultural field 108, in the driving direction of the agricultural apparatus 102 and an imaging sensor 150 to gather a digital representation of the surface of the agricultural field 108 illuminated by the light emitted by the light source 140. The light source 140 may comprise an artificial light source such as a light-emitting diode (LED), a matrix of LEDs and a laser. The light may comprise at least one of ultraviolet light, visible light, i. e. light generally visible to the human eye, near-infrared light, infrared light, invisible light, i. e. light generally not visible to the human eye, monochrome light, multi-coloured light and a light spectrum. The light source 140 may be configured to generate the light at least as one of switched light, pulsed light and modulated light. The light source 140 may be raised by an inclination angle 168 from plumb-vertical (vertical), I. e. tilted by an elevation angle 166 from horizontal. The imaging sensor 150 may be configured to generate a digital image, such as a grey-scale digital image, colour digital image and false colour digital image, for example.

[0102] The boom 120 and hence the light source 140 and I or imaging sensor 150 may be arranged at a height, I. e. vertical distance 162 from the boom 120 and I or light source 140 and I or imaging sensor 150 from the surface of the agricultural field 108, of typically about 0.50 m above the surface. In a horizontal distance160b ahead of the boom 120 may be a plant 107j, such as a weed plant. In response to the light from the light source 140, the plant having height 162a, which is to be determined, may generate a shadow extending from a base of the plant 107j I shadow to a head of the shadow caused be the head of the plant 107j and having a length 160a on the surface of the agricultural field 108.

[0103] Three points given by the light source 140, the head of the shadow and a projection under the boom 1201 light source 140 on the surface form a larger triangle, I. e. a larger right-angled triangle, having a hypotenuse, the side opposite the right angle, having a length equal to the sum of the distance 164a from head of plant 107j to head of shadow and the distance 164b from the boom 1201 light source 140 to head of plant 107j; a upright side having a length equal the vertical distance 162 from boom 1201 light source 140 to surface; and a side along the surface having a length 160 equal to the length 160a of the shadow and the horizontal distance 160b from the boom 1201 light source 140 to the base of plant 107j I shadow.

[0104] Moreover, the larger triangle accommodates a smaller triangle, I. e. a smaller right-angled triangle, having another hypotenuse, the side opposite the right angle, having a length of the distance 164a from head of plant 107j to head of shadow; another upright side having the height 162a of the plant 107j; and another side along the surface having a length equal to the length 160a of the shadow.

[0105] The intercept theorem, also known as Thales's theorem, of trigonometric calculation applies as follows:

[0106] (length of shadow) I

[0107] (length of shadow + horizontal distance light source to plant)

[0108] (height of plant) I (vertical distance light source to surface)

[0109] (1)

[0110] Conversion provides the height 160a of the plant 107j as:

[0111] (height of plant)

[0112] (vertical distance light source to surface * length of shadow) I (length of shadow + horizontal distance light source to plant) (2) The vertical distancel 62 from the boom 1201 light source 140 to the surface (boom height) may be easily determined. A typical boom height is about 0.50 m. The length 160a of the shadow and I or the horizontal distance 160b from the light source 140 to the plant 107j may be determined from the digital representation. For example, the length 160a I horizontal distance 160b may be determined in dependence on known features, such a length of leaves present in the digital representation. Subject to positioning of the light source 140 and imaging sensor 150 on the boom 120, an angle of the imaging sensor 150 may need to be accounted for, in a similar way.

[0113] The height of the plant 107j may be determined and I or the control data for controlling the agricultural apparatus 102 may be generated by at least one of the remote server 106, field management system 110, such as agronomic decision-making engine (agronomical decision engine, ADE), and personal computing device 112, such as mobile phone, hand-held device (tablet computer, tablet) or personal computer. The remote server 106 may offer a cloudbased service.

[0114] The apparatus 102 provides for a good and substantially precise treatment of the agricultural field 108, which may allow for reduction of environmental burden and I or ecological damage.

[0115] As illustrated in Fig. 4, the light source 140 and I or the imaging sensor 150 may be mounted to the boom 120 of the agricultural apparatus 102. However, alternatively or additionally, the artificial light source may be mounted to at least one of a mobile device, a mobile phone, a structure, such as a mast or tower, a wheeled vehicle, a track vehicle, a rail-bound vehicle, a watercraft, an uncrewed aerial vehicle, an aircraft, a spacecraft and a satellite. Alternatively or additionally, the imaging sensor 150 may be mounted to at least one of a mobile device, a mobile phone, a structure, such as a mast or tower, a wheeled vehicle, a track vehicle, a rail-bound vehicle, a watercraft, an uncrewed aerial vehicle, an aircraft, a spacecraft and a satellite.

[0116] Alternatively or additionally, the light source 140 may be a natural light source such as the sun. In case the light source 140 is the sun, additional information regarding geolocation, date and / or time as to when the imaging sensor 150 has gathered the digital representation may be required, and the position of the sun may need to be accounted for, in a similar way.

[0117] Even if Fig. 4 shows a single light source 140 and I or a single imaging sensor 150 mounted on the boom 120, a plurality of light sources and I or a plurality of imaging sensors may be mounted on the boom 120 and in this way dividing in a plurality of subsections. Each light source 140 and I or each imaging sensor 150 may operate independently from the light source 140 and I or the imaging sensor 150 of a neighbor subsection and in this way heights of plants in different subsections may be determined substantially concurrently. Thus, a fine-tuned control of applying of agronomic products may be possible allowing for different thresholds, dosages and I or application rates along the length of the boom 120. Fig. 5 illustrates a flow chart of a computer-implemented method 200 for generating control data for controlling an agricultural apparatus 102 for treating an agricultural field 108.

[0118] The computer-implemented method 200 begins at box 210.

[0119] At box 220, the computer-implemented method 200 gathers a digital representation of at least one portion of the agricultural field 108. The portion(s) may coincide with the geographical locations 108a, 108b, 108c and 108d.

[0120] At box 230, the computer-implemented method 200 analyses the digital representation of the portion(s) of the agricultural field 108 to determine a height of the plant 107j. Alternatively or additionally, analysing the digital representation may comprise analysing the digital representation to classify the plant 107j as one of crop and weed. Alternatively or additionally, analysing the digital representation comprise analysing the digital representation to identify the plant's species.

[0121] Alternatively or additionally, analysing the digital representation comprise analysing the digital representation to determine the plant's growth status. Growth of various plants has been scientifically categorized in phenological development stages of the plants comprising both crops and weed plants. The phenological development stages are used in scientific disciplines such as crop physiology, phytopathology, entomology and plant breeding, and application in agriculture industry such as risk assessment of pesticides, timing of pesticide application, fertilization, agrometeorology and agricultural insurance. The plant development stages have, according to the BBCH-scale, corresponding structured numeric codes. The principal growth stages include:

[0122] 0 Germination, sprouting, bud development

[0123] 1 Leaf development

[0124] 2 Formation of side shoots, tillering

[0125] 3 Stem elongation or rosette growth, shoot development

[0126] 4 Development of harvestable vegetative plant parts, bolting

[0127] 5 Inflorescence emergence, heading

[0128] 6 Flowering

[0129] 7 Development of fruit

[0130] 8 Ripening or maturity of fruit and seed

[0131] 9 Senescence, beginning of dormancy

[0132] The height of a plant may allow to estimate its growth stage.

[0133] At box 240, the computer-implemented method 200 analyses a treatment for the plant 107j in dependence on the determined height. The treatment for the plant 107j may comprise, dependent on a result of analyzing the digital representation, a chemical treatment. Alternatively or additionally, the treatment for the plant 107j may comprise, dependent on the result of analyzing the digital representation, a biological treatment. Alternatively or additionally, the treatment for the plant 107j may comprise, dependent on the result of analyzing the digital representation, a mechanical treatment.

[0134] Alternatively, the computer-implemented method 200 may determine to not treat the plant 107j, as knowledge about suitable treatment may suggest that the treatment product available would not provide for suitable treatment of the plant or the determined treatment is not suitable, efficient and I or allowed in a particular location and or a particular time, for example. For example, a particular chemical treatment of a weed plant of a particular type, having a height of more than about 15 cm and corresponding growth stage cannot destroy this plant. Hence chemical treatment of this plant would be futile, but may incur costs and I or ecological damage.

[0135] At box 250, the computer-implemented method 200 generates 250 the control data for controlling the agricultural apparatus 102 to apply the treatment to the plant 107j. The method may need to convert or "translate” the treatment in dependence of a type and version of the agricultural apparatus 102, treatment system 107 and I or treatment device(s) 107a.

[0136] At box 260, the computer-implemented method 200 provides 260 the control data for controlling the agricultural apparatus 102.

[0137] The computer-implemented method 200 ends at box 270.

[0138] Returning to Fig. 3 illustrating the treatment system 107 implementing a field sprayer as an exemplary embodiment. The treatment system 107 comprises the plurality of spray nozzles arranged along the boom 120 in regular intervals or irregular intervals and plurality of detection units 1071 arranged along the boom 120 in regular intervals or irregular intervals, where spray nozzles and detection units 1071 alternate. The detection units 1071 may be implemented as optical detection component providing a light detection and ranging system (Lidar). As shown in Fig. 3, the detection units 107i may be directed substantially vertically to a surface of the agricultural field. The Lidar may determine distance data from the detection units 107i down towards the surface of the agricultural field 108 for gathering 220 the digital representation of a portion of the agricultural field 108, and the control system(s) 107k may be configured to analyse the digital representation of the portion of the agricultural field 108 comprising the plant 107j to determine the height of the plant 107j, analyse the treatment for the plant 107j in dependence on the determined height, and generate control data for controlling the agricultural apparatus 102 to apply the treatment to the plant 107j, and provide the control data for controlling the agricultural apparatus 102, i. e. the treatment devices 107a to apply the agricultural field 108 in accordance with the control data. The Lidar may generate a Lidar point cloud.

[0139] Alternatively or additionally, the Lidar may be mounted to at least one of a mobile device, a mobile phone, a structure, a wheeled vehicle, a track vehicle, a rail-bound vehicle, a watercraft, an uncrewed aerial vehicle, an aircraft, a spacecraft, and a satellite. For example, an airbourne Lidar, e. g. a Lidar mounted to an uncrewed aerial vehicle (UAV) or aircraft, may be configured to scan the ground using the detection unit 107i, track its x, y, z position using GPS, track the vehicles orientation, i. e. pitch roll and yaw, using an inertial measurement unit (I M U), and records data using a computing device.

[0140] Thus, the treatment system 107 shown in Fig. 3 may implement the method shown in Fig. 5.

[0141] REFERENCE NUMBERS

[0142] 102 agricultural apparatus

[0143] 107a treatment device

[0144] 107j plant

[0145] 108 agricultural field

[0146] 140 light source

[0147] 150 imaging sensor

[0148] 160 horizontal distance from boom to head of shadow

[0149] 160a length of shadow

[0150] 160b horizontal distance from boom to base of plant I shadow 162 vertical distance from boom / light source to surface 162a height of plant

[0151] 164a distance from head of plant to head of shadow

[0152] 164b distance from boom / light source to head of plant

[0153] 166 elevation angle

[0154] 168 inclination angle

[0155] 200 computer-implemented method

[0156] 220 gathering a digital representation

[0157] 230 analysing the digital representation

[0158] 240 determining a treatment

[0159] 250 generating control data

[0160] 260 providing the control data

Claims

CLAIMS1 . A computer-implemented method (200) for generating control data for controlling an agricultural apparatus (102) for treating an agricultural field (108), comprising: gathering (220) a digital representation of at least one portion of the agricultural field (108); analysing (230) the digital representation of the at least one portion of the agricultural field (108) comprising a plant (107j) to determine a height of the plant (107j); analysing (240) a treatment for the plant (107j) in dependence on the determined height; generating (250) the control data for controlling the agricultural apparatus (102) to apply the treatment to the plant (107j); and providing (260) the control data for controlling the agricultural apparatus (102).

2. The computer-implemented method (200) of claim 1, wherein: analysing (230) the digital representation comprises at least one of: analysing the digital representation to classify the plant (107j) as one of crop and weed; analysing the digital representation to identify the plant's species; and analysing the digital representation to determine the plant's growth status; the treatment for the plant (107j) is at least one of a chemical treatment, biological treatment and mechanical treatment dependent on a result of analyzing the digital representation.

3. The computer-implemented method (200) of one of claims 1 to 2, wherein: the digital representation is a digital image of the agricultural field (108) generated with an imaging sensor (150); and analysing (230) of the digital representation comprises at least one of: determining, from the digital image, a length of a projection of the plant (107j) on the agricultural field (108); and determining the height of the plant (107j) in dependence on the determined length of the projection.

4. The computer-implemented method (200) of claim 3, wherein: the projection of the plant (107j) on the agricultural field (108) is a shadow where radiation from a radiation source is blocked by the plant (107j).

5. The computer-implemented method (200) of claim 4, wherein: determining the length of the projection comprises at least one of: determining a vertical distance of the radiation source from the agricultural field (108); determining a horizontal distance of the radiation source from the plant (107j); determining the length of the projection in dependence on the determined horizontal distance of the radiation source; anddetermining the length of the projection by comparing the projection with a feature in the digital image, having a known length; determining the height of the plant (107j) comprises at least one of: determining the height of the plant (107j) in dependence on the determined vertical distance of the radiation source, determined horizontal distance of the radiation source and determined length of the projection; and determining the height of the plant (107j) from the determined vertical distance of the radiation source multiplied by the determined length of the projection divided by a sum of the determined length of the projection and determined horizontal distance of the radiation source; determining the height of the plant (107j) comprises at least one of: determining a relative position of the radiation source to the plant (107j); determining an elevation angle of the radiation source over the agricultural apparatus (102); determining the height of the plant (107j) in dependence on the determined elevation angle and determined length of the projection; determining the height of the plant (107j) from the determined length of the projection multiplied by the tangent of the determined elevation angle; and determining the height of the plant (107j) from the determined length of the projection divided by the cotangent of the determined elevation angle; determining the relative position of the radiation source comprises at least one of: obtaining a time of origin of the digital image; obtaining position information of the radiation source for the time of origin; and determining the relative position independence on the obtained position information; or determining the length of the projection further comprises at least one of: determining a vertical distance of the imaging sensor (150) from the agricultural field (108); determining a horizontal distance of the imaging sensor (150) from the plant (107j); and determining a viewing angle of the imaging sensor (150) to the plant (107j); or determining the height of the plant (107j) further comprises: determining the height of the plant (107j) in further dependence on at least one of: the determined vertical distance of the imaging sensor (150); the determined horizontal distance of the imaging sensor (150); and the determined viewing angle of the imaging sensor (150).

6. The computer-implemented method (200) of one of claims 4 to 5, wherein: the radiation comprises light; the light comprises at least one of: ultraviolet light; visible light; near-infrared light;infrared light; invisible light; monochrome light; multi-coloured light; and a light spectrum; the radiation source comprises a light source; the light source comprises at least one of: a natural light source; and an artificial light source; the natural light source comprises the sun; the artificial light source comprises at least one of: a light-emitting diode; a matrix of light-emitting diodes; and a laser; the artificial light source is configured to generate the light at least as one of: switched light; pulsed light; and modulated light; or the artificial light source is mounted to at least one of: the agricultural apparatus (102); a I the mobile device; a I the mobile phone; a structure; a wheeled vehicle; a track vehicle; a rail-bound vehicle; a watercraft; an uncrewed aerial vehicle; an aircraft; a spacecraft; and a satellite.

7. The computer-implemented method (200) of one of claims 3 to 6, wherein: the computer-implemented method (200) further comprises: controlling the imaging sensor (150) to generate the digital image; the imaging sensor (150) is configured to generate the digital image as at least one of: grey-scale digital image; colour digital image; anda false colour; or the imaging sensor (150) is mounted to at least one of: the agricultural apparatus (102); a I the mobile device; a I the mobile phone; a I the structure; a I the wheeled vehicle; a I the track vehicle; a I the rail-bound vehicle; a I the watercraft; an I the uncrewed aerial vehicle; an I the aircraft; a I the spacecraft; and a I the satellite.

8. The computer-implemented method (200) of one of claims 1 to 2, wherein: the digital representation is a point cloud of the agricultural field (108); and analysing (230) of the digital representation comprises: determining, from the point cloud, the height of the plant (107j) on the agricultural field (108) in dependence on a surface of the agricultural field (108).

9. The computer-implemented method (200) of claim 8, wherein: the point cloud is a Lidar point cloud; the computer-implemented method (200) further comprises: controlling a Lidar sensor to generate the Lidar point cloud; or the Lidar sensor is mounted to at least one of: the agricultural apparatus (102); a I the mobile device; a I the mobile phone; a structure; a wheeled vehicle; a track vehicle; a rail-bound vehicle; a watercraft; an uncrewed aerial vehicle; an aircraft; a spacecraft; and a satellite.

10. A computer-program product, comprising instructions which, when executed by a data processing apparatus, cause the data processing apparatus to carry out the computer-implemented method (200) of one of claims 1 to 9.

11. A data processing apparatus for generating control data for controlling an agricultural apparatus (102) for treating an agricultural field (108), comprising: an input device for gathering (220) a digital representation of at least one portion of the agricultural field; a processing device for analysing (230) the digital representation of the at least one portion of the agricultural field (108) comprising a plant (107j) to determine a height of the plant (107j), analysing (240) a treatment for the plant (107j) in dependence on the determined height, and generating (250) control data for controlling the agricultural apparatus (102) to apply the treatment to the plant (107j); and an output device for providing (260) the control data for controlling the agricultural apparatus.

12. A digital treatment map comprising control data for controlling an agricultural apparatus (102) for treating an agricultural field (108), obtained by the computer-implemented method (200) of one of claims 1 to 9.

13. A method for controlling an agricultural apparatus (102) for treating an agricultural field (108), comprising: receiving control data generated according to the computer-implemented method (200) of one of claims 1 to 9; and treating the agricultural field (108) based on the received control data.

14. The method of claim 13, further comprising: controlling a treatment device (107a) of the agricultural apparatus (102) to apply the determined treatment to the agricultural field (108).

15. An agricultural apparatus (102), comprising: a receiving device for receiving control data generated according to the computer-implemented method (200) of one of claims 1 to 9; and a treatment device (107a) for applying the agricultural field (108) in accordance with the received control data.

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