DYNAMIC TANK MANAGEMENT BASED ON PREVIOUS ENVIRONMENT AND MACHINE MEASUREMENTS

    公开(公告)号:US20230165234A1

    公开(公告)日:2023-06-01

    申请号:US17538912

    申请日:2021-11-30

    CPC classification number: A01M7/0089 G05D1/0219 G06V20/188 G05D2201/0201

    Abstract: Historical information is accessed that describes a previous state of a field, previous environmental conditions for the field, and previous farming machine actions performed in the field. A tank management model is applied to the historical information to determine expected weed densities within field portions and an amount of treatment fluid required to treat plants within the field. While the farming machine is treating plants in the field, current information describing a current state of the field is accessed. The tank management model is applied to the current information to determine updated weed densities within field portions not yet treated. The farming machine performs a modified plant treatment action based on the updated weed densities and a comparison of a remaining amount of treatment fluid within a tank of the farming machine and an updated amount of treatment fluid for treating plants within field portions not yet treated.

    Modular precision agriculture system

    公开(公告)号:US11659793B2

    公开(公告)日:2023-05-30

    申请号:US17410998

    申请日:2021-08-24

    CPC classification number: A01G22/00 A01C21/002 A01M21/04 A01M21/043 Y02A40/10

    Abstract: A modular system includes a hub and a set of modules removably coupled to the hub. The modules are physically coupled to the frame relative to each other so that each module can operate with respect to a different row of a field. An individual module includes a sensor for capturing field measurement data of individual plants along a row as the modular system moves through the geographic region. An individual module further includes a treatment mechanism for applying a treatment to the individual plants of the row based on the field measurement data before the modular system passes by the individual plants. An individual module further includes a computing device that determines the treatment based on the field measurement data and communicates data to the hub. The hub is communicatively coupled to the modules, so that it may exchange data between the modules and with a remote computing system.

    Plant group identification
    113.
    发明授权

    公开(公告)号:US11580718B2

    公开(公告)日:2023-02-14

    申请号:US16995618

    申请日:2020-08-17

    Abstract: A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.

    DETECTING UNTRAVERSABLE SOIL FOR FARMING MACHINE

    公开(公告)号:US20230040430A1

    公开(公告)日:2023-02-09

    申请号:US17396170

    申请日:2021-08-06

    Abstract: A farming machine moves through a field and performs one or more farming actions (e.g., treating one or more plants) in the field. Portions of the field may include moisture, such as puddles or mud patches. A control system associated with the farming machine may include a traversability model and/or a moisture model to help the farming machine operate in the field with the moisture. In particular, the control system may employ the traversability model to reduce the likelihood of the farming machine attempting to traverse an untraversable portion of the field, and the control system may employ the moisture model to reduce the likelihood of the farming machine performing an action that will damage a portion of the field.

    MACHINE-LEARNED TILLAGE SWEEP MALFUNCTION IN AN AUTONOMOUS FARMING VEHICLE

    公开(公告)号:US20220198642A1

    公开(公告)日:2022-06-23

    申请号:US17126793

    申请日:2020-12-18

    Abstract: A detection system detects malfunctions in an autonomous farming vehicle during an autonomous routine using one or more models and data from sensors coupled to the autonomous farming vehicle. The models may include machine-learned models trained on the sensor data and configured to identify objects indicative of an operational or malfunctioning component within a tilling assembly such as a tilling shank or sweep. Additionally, a machine-learned model may be trained on sensor data to detect whether debris has plugged the tilling assembly of the autonomous farming vehicle. In response to detecting a malfunction or a plug, the detection system may modify the autonomous routine (e.g., pausing operation) or provide information for the malfunction to be addressed (e.g., the likely location of a malfunctioning sweep that has detached from the tilling assembly).

    Identifying and treating plants using depth information in a single image

    公开(公告)号:US11367207B2

    公开(公告)日:2022-06-21

    申请号:US17033263

    申请日:2020-09-25

    Abstract: A farming machine includes one or more image sensors for capturing an image as the farming machine moves through the field. A control system accesses an image captured by the one or more sensors and identifies a distance value associated with each pixel of the image. The distance value corresponds to a distance between a point and an object that the pixel represents. The control system classifies pixels in the image as crop, plant, ground, etc. based on the visual information in the pixels. The control system generates a labelled point cloud using the labels and depth information, and identifies features about the crops, plants, ground, etc. in the point cloud. The control system generates treatment actions based on any of the depth information, visual information, point cloud, and feature values. The control system actuates a treatment mechanism based on the classified pixels.

    System and method for plant treatment based on neighboring effects

    公开(公告)号:US11350622B2

    公开(公告)日:2022-06-07

    申请号:US17497866

    申请日:2021-10-08

    Inventor: Lee Kamp Redden

    Abstract: A method for plant treatment, including: receiving a first measurement for a plant from a sensor as the sensor moves within a geographic area comprising a plurality of plants; in response to receipt of the first measurement and prior to receipt of a second measurement for a second plant of the plurality, determining a set of treatment mechanism operation parameters for the plant to optimize a geographic area output parameter based on the first measurement and historical measurements for the geographic area; determining an initial treatment parameter for the plant; and operating a treatment mechanism in a treatment mode based on the set of operating parameters in response to satisfaction of the initial treatment parameter.

    PLANT IDENTIFICATION USING DYNAMIC CROPPING

    公开(公告)号:US20220058770A1

    公开(公告)日:2022-02-24

    申请号:US17405932

    申请日:2021-08-18

    Abstract: A farming machine identifies and treats a plant as the farming machine travels through a field. The farming machine includes an array of tiled image sensors for capturing images of the field. A control system identifies an active region in the captured images and generates a tiled image that includes the active region. The control system applies image processing functions to identify the plant in the tiled image and actuates a treatment mechanism to treat the identified plant. The control system causes the array of image sensors to capture the image, identifies the plant, and actuates the treatment mechanism in real time as the farming machine travels through the field.

    Automated plant detection using image data

    公开(公告)号:US11093745B2

    公开(公告)日:2021-08-17

    申请号:US15975092

    申请日:2018-05-09

    Abstract: A plant treatment platform uses a plant detection model to detect plants as the plant treatment platform travels through a field. The plant treatment platform receives image data from a camera that captures images of plants (e.g., crops or weeds) growing in the field. The plant treatment platform applies pre-processing functions to the image data to prepare the image data for processing by the plant detection model. For example, the plant treatment platform may reformat the image data, adjust the resolution or aspect ratio, or crop the image data. The plant treatment platform applies the plant detection model to the pre-processed image data to generate bounding boxes for the plants. The plant treatment platform then can apply treatment to the plants based on the output of the machine-learned model.

    Nozzles with interchangeable inserts for precision application of crop protectant

    公开(公告)号:US11071293B2

    公开(公告)日:2021-07-27

    申请号:US16154578

    申请日:2018-10-08

    Abstract: A treatment system for spraying treatment fluid onto plants in a field is described. The treatment system includes a configurable treatment mechanism including an array of nozzles and valve assemblies coupled into manifolds, and manifold assemblies. The nozzle comprises a nozzle housing and an insert assembly contained within the nozzle housing. When coupled, a top casing including a fluid inlet and a bottom casing including at least one fluid outlet form the nozzle housing. The insert assembly comprises at least one nozzle insert to fluidically couple the fluid inlet and the fluid outlets such that fluid entering from the fluid inlet exits the nozzle housing through the fluid outlets.

Patent Agency Ranking