X Development LLC

Bot & Dolly, LLC

Verily Life Sciences LLC

Intrinsic Innovation LLC

X Development Llx

Matthew A Bitterman

Kendra Byrne

Jeffrey Linnell

Jeff Linnell

William Raymond Regan

David R Brown

Elliott Grant

Benoit M Schillings

Eli Reekmans

Tobias Kinnebrew

Anthony Sean Jules

Zhiqiang Yuan

Marek Piotr Michalowski

Michael Beardsworth

Brandon Kruysman

Jonathan Proto

Christopher Van Arsdale

In embodiments, acquiring sensor data associated with a plant growing in a field, and analyzing the sensor data to extract one or more phenotypic traits associated with the plant from the sensor data. Indexing the one or more phenotypic traits to one or both of an identifier of the plant or a virtual representation of a part of the plant, and determining one or more plant insights based on the one or more phenotypic traits, wherein the one or more plant insights includes information about one or more of a health, a yield, a planting, a growth, a harvest, a management, a performance, and a state of the plant. One or more of the health, yield, planting, growth, harvest, management, performance, and the state of the plant are included in a plant insights report that is generated.

Capture of ground truthed labels of plant traits method and system

Example systems and methods allow for runtime control of robotic devices during a construction process. One example method includes determining at least one sequence of robot operations corresponding to at least one robot actor, causing the at least one robot actor to execute a portion of the at least one sequence of robot operations during a first time period, receiving an interrupt signal from a mobile computing device indicating a modification to the at least one sequence of robot operations, where the mobile computing device is configured to display a digital interface including one or more robot parameters describing the at least one robot actor and one or more tool parameters describing operating characteristics of at least one physical tool, and causing the at least one robot actor to execute a portion of the at least one modified sequence of robot operations during a second time period.

Runtime controller for robotic manufacturing system

Example systems and methods allow for use of a graphical interface to cause one or more robotic devices to construct an output product. One example method includes causing a graphical interface to be displayed on a display device, receiving input data corresponding to one or more interactions with the graphical interface indicating at least one motion path and at least one sequence of tool actions to execute at one or more points within the at least one motion path for use in construction of an output product, generating a plurality of digital nodes including at least one robot node, at least one motion command node, and at least one tool command node, and providing instructions for the at least one robot actor to move according to the sequence of robot motion commands determined by the at least one motion command node and execute the sequence of tool commands determined by the at least one tool command node to construct the output product.

Software interface for authoring robotic manufacturing process

A robotic system includes end-effector(s) that combine a plurality of objects in a production process. The system includes sensor(s) that obtain measurement(s) relating to a combination of a first object and one or more other objects during the production process. The system includes a control system communicatively coupled to the sensor(s). The control system stores specifications relating to the combination of the plurality of objects. The control system receives the measurement(s) from the sensor(s), determines a difference based on the measurement(s) and the specifications, determines adjustment(s) to the production process based on the determined difference, and sends, for the end-effector(s), instruction(s) based on the specifications and the one or more adjustment(s). The end-effector(s) combine a second object with the first object and the one or more objects based on the specifications and the one or more adjustment(s).

Error accrual and mitigation during robotic process

In embodiments, acquiring sensor data associated with a plant growing in a field, and analyzing the sensor data to extract, while in the field, one or more phenotypic traits associated with the plant from the sensor data. Indexing, while in the field, the one or more phenotypic traits to one or both of an identifier of the plant or a virtual representation of a part of the plant, and determining one or more plant insights based on the one or more phenotypic traits, wherein the one or more plant insights includes information about one or more of a health, a yield, a planting, a growth, a harvest, a management, a performance, and a state of the plant. One or more of the health, yield, planting, growth, harvest, management, performance, and the state of the plant are included in a plant insights report that is generated.

Embodiments described herein may relate to a system comprising a plurality of optical elements, comprising at least a first optical element and one or more secondary optical elements, a heliostat comprising the first optical element, where the heliostat is operable to move the first optical element to continuously reflect light from a non-stationary light source in a beam towards a first of the secondary optical elements, and where the secondary optical elements are arranged to re-direct the reflected beam of light towards an illumination target. The system further includes a controller configured to receive position data indicative of the position of the non-stationary light source over time, and in response to the position data, control at least the heliostat to continuously direct the beam of light towards the first of the secondary optical elements, such that the beam of light is continuously re-directed towards the illumination target.

Kinematically linked optical components for light redirection

Systems and Methods for Augmented-Human Field Inspection Tools for Automated Phenotyping Systems and Agronomy Tools. In one embodiment, a method for plant phenotyping, includes: acquiring a first set of observations about plants in a field by a trainer. The trainer carries a sensor configured to collect observations about the plant, and the first set of observations includes ground truth data. The method also includes processing the first set of observations about the plants by a trait extraction model to generate instructions for a trainee; and acquiring a second set of observations about the plants by a trainee while the trainee follows the instructions.

Augmented-human field inspection tools for automated phenotyping systems and agronomy tools

Systems and methods for plant phenotyping using mechanical manipulation are disclosed. In one embodiment, a method for plant phenotyping includes: agitating a plant with an agitator; acquiring images of the plant with a camera while agitating the plant; and analyzing the images of the plant to determine properties of the plant. The plant may be at least partially agitated at a resonance frequency of oscillation of a stalk of the plant.

Plant phenotyping techniques using mechanical manipulation, and associated systems and methods

Example implementations may relate to methods and systems for determining operational modes for a particular arrangement of controllers. Accordingly, a computing device may detect that a first controller is within a threshold distance of a second controller. Responsively, the device may determine a spatial arrangement of the first and second controllers. The device may then determine a set of operational modes that corresponds to the spatial arrangement, where the set includes (i) a first operational mode that corresponds to a first location in the spatial arrangement and (ii) a second operational mode that corresponds to a second location in the spatial arrangement. The device may then load (i) the first operational mode to whichever of the first and second controllers is in the first location and (ii) the second operational mode to whichever of the first and second controllers is in the second location.

Automatic distribution of control functions between multiple knob controllers based on proximity and relative positioning of the knobs

Example methods and systems are disclosed for on-demand packaging of one or more items. According to one example, a method can include receiving an order for the item(s) and determining characteristic-information for the item(s) using a computer system. The characteristic-information includes an indication of at least a size and a shape of the item(s). The method also includes processing the characteristic-information based on design criteria to determine an arrangement of the item(s) within at least one container volume, and a configuration for a protective structure to hold the item(s) in the arrangement within the container volume(s). The method can further include, in response to the processing the characteristic-information, forming the protective structure according to the configuration, placing the item(s) into the protective structure according to the arrangement, and placing the protective structure and the item(s) in the container volume(s).

On-demand protective structures for packaging items in a container

Example systems and methods may allow for closed-loop control of robotic operation. One example method includes receiving input data that identifies data sources to monitor and indicates adjustments to make in response to deviations by at least one of the data sources from at least one predicted state during subsequent execution of sequences of operations by robotic devices, receiving data streams from the data sources during execution of the sequences of operations by the robotic devices, identifying a deviation by one of the data sources from a predicted state for which the received input data indicates adjustments to the sequences of operations for the robotic devices, providing instructions to the robotic devices to execute the adjusted sequences of operations, and providing instructions to a second computing device to update a visual simulation of the robotic devices based on the adjusted sequences of operations.

Growing community of inventors

Mountain View, CA, United States of America

Matthew A Bitterman