公开(公告)号：US20250000015A1

公开(公告)日：2025-01-02

申请号：US18217296

申请日：2023-06-30

Applicant: Blue River Technology Inc.

Inventor： Benjamin Kahn Cline ,  Christopher Grant Padwick ,  Chia-Chun Fu ,  Olgert Denas

IPC: A01C21/00 ,  A01M7/00 ,  G06V20/10 ,  G06V20/56

Abstract: A method for calibrating performance characteristics of a farming machine using a performance report is described. The farming machine accesses images of plants in a field captured during the calibration pass. The images are input into a performance model to generate a performance report by identifying plants in the images using a plurality of identification sensitivities and determining expected performance characteristics of the farming machine for each of the identification sensitivities. As such, the performance report includes expected performance characteristics for each identification sensitives. The farming machine accesses a target performance characteristic (e.g., from an operator) for the farming machine corresponding identification sensitivity. Images are input into a plant identification model during a treatment pass which identify a plant in the field using the identification sensitivity corresponding to the target performance characteristic. The farming machine treats the plant in the field using a treatment array of the farming machine.

公开(公告)号：US12166952B2

公开(公告)日：2024-12-10

申请号：US18479504

申请日：2023-10-02

Applicant: Blue River Technology Inc.

Inventor： Lee Kamp Redden

IPC: H04N13/243 ,  G06F18/2415 ,  G06T7/593 ,  G06V10/764 ,  G06V20/00 ,  G06V20/10 ,  H04N13/00 ,  H04N13/128 ,  H04N13/204 ,  H04N13/239 ,  H04N13/271

Abstract: Described are methods for identifying the in-field positions of plant features on a plant by plant basis. These positions are determined based on images captured as a vehicle (e.g., tractor, sprayer, etc.) including one or more cameras travels through the field along a row of crops. The in-field positions of the plant features are useful for a variety of purposes including, for example, generating three-dimensional data models of plants growing in the field, assessing plant growth and phenotypic features, determining what kinds of treatments to apply including both where to apply the treatments and how much, determining whether to remove weeds or other undesirable plants, and so on.

公开(公告)号：US20240303801A1

公开(公告)日：2024-09-12

申请号：US18608760

申请日：2024-03-18

Applicant: Blue River Technology Inc.

Inventor： Divya Sharma ,  Michael Albert Elcano ,  Byron Gajun Ho ,  Jeremy Douglas Krantz ,  Tyler Niday ,  Robert Joseph Plumeau

IPC: G06T7/00 ,  A01B3/26 ,  A01B79/00 ,  G06F18/214 ,  G06F18/24 ,  G06K7/10 ,  G06K19/07 ,  G06N20/00 ,  G06T7/593 ,  H04N13/204

CPC classification number: G06T7/0004 ,  A01B3/26 ,  A01B79/005 ,  G06F18/214 ,  G06F18/24 ,  G06K7/10366 ,  G06K19/0723 ,  G06N20/00 ,  G06T7/593 ,  H04N13/204 ,  G06T2207/20081 ,  G06T2207/30164 ,  G06T2207/30204

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).

公开(公告)号：US11823369B2

公开(公告)日：2023-11-21

申请号：US17126793

申请日：2020-12-18

Applicant: Blue River Technology Inc.

Inventor： Divya Sharma ,  Michael Albert Elcano ,  Byron Gajun Ho ,  Jeremy Douglas Krantz ,  Tyler Niday ,  Robert Joseph Plumeau

IPC: G06T7/00 ,  G06N20/00 ,  G06V20/10 ,  G06F18/2411

CPC classification number: G06T7/0004 ,  G06F18/2411 ,  G06N20/00 ,  G06V20/10 ,  G06T2207/10048 ,  G06T2207/20081 ,  G06T2207/30188

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).

公开(公告)号：US20230202495A1

公开(公告)日：2023-06-29

申请号：US17564063

申请日：2021-12-28

Applicant: Blue River Technology Inc.

Inventor： John William Peake ,  James Patrick Ostrowski ,  Erik Ehn ,  Kent Michael Anderson ,  Benjamin Ray Chostner

IPC: B60W50/035 ,  G06T7/00 ,  B60W50/02 ,  G07C5/08

CPC classification number: B60W50/035 ,  G06T7/0004 ,  B60W50/0205 ,  G07C5/085 ,  G06T2207/30164 ,  B60W2420/42 ,  B60W2300/15

Abstract: As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.

公开(公告)号：US20230189784A1

公开(公告)日：2023-06-22

申请号：US17553232

申请日：2021-12-16

Applicant: Blue River Technology Inc.

Inventor： PAUL YALDEN MONTGOMERY ,  LEE KAMP REDDEN

IPC: A01M7/00 ,  G06T7/70 ,  G06T7/60

CPC classification number: A01M7/0089 ,  G06T7/70 ,  G06T7/60 ,  G06T2207/10028 ,  G06T2207/30188

Abstract: Embodiments relate to a farming machine that includes a beam, an actuator system, a sensor system, and a control system. The beam extends away from a body of the farming machine. The actuator system controls a position of the actuatable beam relative to the body. The sensor system generates measurement data that indicates the position of a ground point in front of a component of the farming machine relative to the sensor system. The control system determines a target beam height for the ground point. Based on the measurement data and the target beam height, the control system actuates the actuator system to adjust the position of the beam. As a result of the position adjustment, the height of the beam relative to the ground is equal to the target beam height prior to the component passing over the ground point.

公开(公告)号：US11672194B2

公开(公告)日：2023-06-13

申请号：US17126764

申请日：2020-12-18

Applicant: Blue River Technology Inc.

Inventor： Divya Sharma ,  Michael Albert Elcano ,  Byron Gajun Ho ,  Jeremy Douglas Krantz ,  Tyler Niday ,  Robert Joseph Plumeau

IPC: A01B79/00 ,  G06N20/00 ,  G05D1/00 ,  G06T7/00 ,  G06T7/70 ,  A01B3/24

CPC classification number: A01B79/005 ,  G05D1/0088 ,  G06N20/00 ,  G06T7/0002 ,  G06T7/70 ,  A01B3/24 ,  G05D2201/0201 ,  G06T2207/20081 ,  G06T2207/30188 ,  G06T2207/30252

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).

公开(公告)号：US20230127880A1

公开(公告)日：2023-04-27

申请号：US18082312

申请日：2022-12-15

Applicant: Blue River Technology Inc.

Inventor： Lee Kamp Redden

IPC: H04N13/243 ,  H04N13/204 ,  G06T7/593 ,  H04N13/128 ,  H04N13/239 ,  H04N13/271 ,  G06V20/00 ,  G06F18/2415 ,  G06V10/764 ,  G06V20/10

Abstract: Described are methods for identifying the in-field positions of plant features on a plant by plant basis. These positions are determined based on images captured as a vehicle (e.g., tractor, sprayer, etc.) including one or more cameras travels through the field along a row of crops. The in-field positions of the plant features are useful for a variety of purposes including, for example, generating three-dimensional data models of plants growing in the field, assessing plant growth and phenotypic features, determining what kinds of treatments to apply including both where to apply the treatments and how much, determining whether to remove weeds or other undesirable plants, and so on.

公开(公告)号：US11570420B2

公开(公告)日：2023-01-31

申请号：US17853925

申请日：2022-06-30

Applicant: Blue River Technology Inc.

Inventor： Lee Kamp Redden

IPC: H04N13/204 ,  G06K9/62 ,  H04N13/128 ,  H04N13/239 ,  H04N13/271 ,  H04N13/243 ,  G06V20/00 ,  G06T7/593 ,  H04N13/00

Abstract: Described are methods for identifying the in-field positions of plant features on a plant by plant basis. These positions are determined based on images captured as a vehicle (e.g., tractor, sprayer, etc.) including one or more cameras travels through the field along a row of crops. The in-field positions of the plant features are useful for a variety of purposes including, for example, generating three-dimensional data models of plants growing in the field, assessing plant growth and phenotypic features, determining what kinds of treatments to apply including both where to apply the treatments and how much, determining whether to remove weeds or other undesirable plants, and so on.

公开(公告)号：US11514671B2

公开(公告)日：2022-11-29

申请号：US16893405

申请日：2020-06-04

Applicant: Blue River Technology Inc.

Inventor： Andrei Polzounov ,  James Patrick Ostrowski ,  Lee Kamp Redden ,  Olgert Denas ,  Chia-Chun Fu ,  Chris Padwick

IPC: G06V20/10 ,  G06N5/04 ,  G06T7/10 ,  G06V10/26 ,  A01B76/00

Abstract: A farming machine including a number of treatment mechanisms treats plants according to a treatment plan as the farming machine moves through the field. The control system of the farming machine executes a plant identification model configured to identify plants in the field for treatment. The control system generates a treatment map identifying which treatment mechanisms to actuate to treat the plants in the field. To generate a treatment map, the farming machine captures an image of plants, processes the image to identify plants, and generates a treatment map. The plant identification model can be a convolutional neural network having an input layer, an identification layer, and an output layer. The input layer has the dimensionality of the image, the identification layer has a greatly reduced dimensionality, and the output layer has the dimensionality of the treatment mechanisms.