Abstract: The calibration system of the farming machine receives images from each camera of the camera array. The images comprise visual information representing a view of a portion of an area surrounding the farming machine. To calibrate a pair of cameras including a first camera and second camera, the calibration system determines a relative pose between the pair of cameras by extracting relative position and orientation characteristics from visual information in both an image received from the first camera and an image received from the second camera. The calibration system identifies a calibration error for the pair of cameras based on a comparison of the relative pose with an expected pose between the first pair of cameras. The calibration system transmits a notification to an operator of the farming machine that describes the calibration error and instructions for remedying the calibration error.

Abstract: A method for determining how using a respiratory therapy system impacts sleep sessions of a user, includes receiving first activity information corresponding to actions of a user occurring prior to a use of the respiratory therapy system by the user. The first activity information includes activity information associated with use of a mobile device by the user prior to the use of the respiratory therapy system. The method also includes receiving second activity information corresponding to actions of the user occurring after the use of the respiratory therapy system. The second activity information includes activity information associated with use of the mobile device by the user after the use of the respiratory therapy system, as well as respiratory information generated by the respiratory therapy system during a sleep session of the user when using the respiratory therapy system.

Abstract: Disclosed is a system for encoding and/or rendering animations without temporal or spatial restrictions. The system may encode an animation as a point cloud with first data points having a first time value and different positional and non-positional values, and second data points having a second time value and different positional and non-positional values. Rendering the animation may include generating and presenting a first image for the first time value of the animation based on the positional and non-positional values of the first data points, and generating and presenting a second image for the second time value of the animation by changing a visualization at a first position in the first image based on the positional values of a data point from the second data points corresponding to the first position and the data point non-positional values differing from the visualization.

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.

Abstract: Disclosed is a system for encoding and/or rendering animations without temporal or spatial restrictions. The system may encode an animation as a point cloud with first data points having a first time value and different positional and non-positional values, and second data points having a second time value and different positional and non-positional values. Rendering the animation may include generating and presenting a first image for the first time value of the animation based on the positional and non-positional values of the first data points, and generating and presenting a second image for the second time value of the animation by changing a visualization at a first position in the first image based on the positional values of a data point from the second data points corresponding to the first position and the data point non-positional values differing from the visualization.

Abstract: A farming machine identifies and treats a plant as the farming machine travels through a field. The farming machine includes a pair of image sensors for capturing images of a plant. The image sensors are different, and their output images are used to generate a depth map to improve the plant identification process. A control system identifies a plant using the depth map. The control system captures images, identifies a plant, and actuates a treatment mechanism in real time.

Abstract: Disclosed is a system for encoding and/or rendering animations without temporal or spatial restrictions. The system may encode an animation as a point cloud with first data points having a first time value and different positional and non-positional values, and second data points having a second time value and different positional and non-positional values. Rendering the animation may include generating and presenting a first image for the first time value of the animation based on the positional and non-positional values of the first data points, and generating and presenting a second image for the second time value of the animation by changing a visualization at a first position in the first image based on the positional values of a data point from the second data points corresponding to the first position and the data point non-positional values differing from the visualization.

Abstract: Disclosed is a system for encoding and/or rendering animations without temporal or spatial restrictions. The system may encode an animation as a point cloud with first data points having a first time value and different positional and non-positional values, and second data points having a second time value and different positional and non-positional values. Rendering the animation may include generating and presenting a first image for the first time value of the animation based on the positional and non-positional values of the first data points, and generating and presenting a second image for the second time value of the animation by changing a visualization at a first position in the first image based on the positional values of a data point from the second data points corresponding to the first position and the data point non-positional values differing from the visualization.

Abstract: The calibration system of the farming machine receives images from each camera of the camera array. The images comprise visual information representing a view of a portion of an area surrounding the farming machine. To calibrate a pair of cameras including a first camera and second camera, the calibration system determines a relative pose between the pair of cameras by extracting relative position and orientation characteristics from visual information in both an image received from the first camera and an image received from the second camera. The calibration system identifies a calibration error for the pair of cameras based on a comparison of the relative pose with an expected pose between the first pair of cameras. The calibration system transmits a notification to an operator of the farming machine that describes the calibration error and instructions for remedying the calibration error.

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.

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.

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.

Abstract: An expandable porous framework, the framework containing a dry cementitious powder fill that when exposed to an aqueous media, will expand against the constraint of the framework and set to form a solid, hard and coherent material, the formwork being porous to liquids but substantially impermeable to the powder fill.

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.

Abstract: A farming machine identifies and treats a plant as the farming machine travels through a field. The farming machine includes a pair of image sensors for capturing images of a plant. The image sensors are different, and their output images are used to generate a depth map to improve the plant identification process. A control system identifies a plant using the depth map. The control system captures images, identifies a plant, and actuates a treatment mechanism in real time.

Abstract: Provided is an anonymization system for performing distributed, stateless, and persistent anonymization of with variable encoding. The anonymization system may receive a first file with at least a first data element. The first data element may include a tag and restricted data. The anonymization system may change a first encoding of the tag having a first size to a second encoding having a second size that is smaller than the first size. The anonymization system may replace the restricted data with different anonymized data based on a persistent mapping of the restricted data to the anonymized data, and may output the first data element with the second encoding of the tag and the anonymized data to a database or an anonymized second file.

Abstract: A path of travel used by an autopilot operation system for auto-guidance of a mobile machine is defined, transparently to a human operator, in response to the human operator engaging and disengaging operation of an implement coupled with the mobile machine. The auto-guidance of the mobile machine is activated, transparently to the human operator, in response to the human operator engaging the implement a second time.

Abstract: A path of travel used by an autopilot operation system for auto-guidance of a mobile machine is defined, transparently to a human operator, in response to the human operator engaging and disengaging operation of an implement coupled with the mobile machine. The auto-guidance of the mobile machine is activated, transparently to the human operator, in response to the human operator engaging the implement a second time.

Abstract: Auto-guidance of a mobile machine is provided that does not require a graphical user interface display. Human interactions with the auto-guidance system of a mobile machine are performed solely with one or more electromechanical switches of the auto-guidance system while the mobile machine is operating. A first point for auto-guidance of a mobile machine is set by an auto-guidance system in response to a first electromechanical switch input. A second point for auto-guidance of the mobile machine is set by the auto-guidance system in response to a second electromechanical switch input after movement of the mobile machine from the first point. The auto-guidance system activates auto-guidance of the mobile machine along a path defined by the first point and the second point. The setting of the first point, the setting of the second point, and the activating are performed by one or more hardware processors.

Abstract: A path of travel used by an autopilot operation system for auto-guidance of a mobile machine is defined, transparently to a human operator, in response to the human operator engaging and disengaging operation of an implement coupled with the mobile machine. The auto-guidance of the mobile machine is activated, transparently to the human operator, in response to the human operator engaging the implement a second time.