Abstract: A computer-implemented method of sensor input processing, implemented by an agricultural platform comprising a processor and a sensor, includes capturing, using the sensor, sensor images of a vicinity of a target object of a time interval during which a treatment is applied to the target object; processing the sensor images using one or more machine learning (ML) algorithms wherein at least one ML algorithm uses an ML model trained to detect a presence of a treatment action in the vicinity of the target object; and providing, selectively based on a result of detecting the presence of the treatment action in the vicinity of the target object, an outcome of the processing for further processing.

Abstract: A method of processing agricultural images includes comparing object detections performed by multiple image processing schemes to determine a set of ground truth images from which at least one machine learning (ML) models used by at least one ML algorithm included in the multiple image processing schemes is trained, wherein the multiple image processing schemes include two or more of (a) an image processing scheme that includes a cascade of multiple ML algorithms; (b) an image processing scheme that includes image annotation based on user feedback; or (c) an image processing scheme that includes a cascade of an ML algorithm or a computer vision (CV) algorithm and a user feedback.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. The agricultural treatment system may determine a first real-world geo-spatial location of the treatment system. The system can receive captured images depicting real-world agricultural objects of a geographic scene. The system can associate captured images with the determined geo-spatial location of the treatment system. The treatment system can identify, from a group of mapped and indexed images, images having a second real-word geo-spatial location that is proximate with the first real-world geo-spatial location. The treatment system can compare at least a portion of the identified images with at least a portion of the captured images. The treatment system can determine a target object and emit a fluid projectile at the target object using a treatment device.

Abstract: An agricultural treatment system can include one or more motor assemblies, linkage assemblies coupled to the motor assemblies, and a treatment head assembly coupled to the linkage assemblies. Each motor assembly can rotate about a motor assembly rotational axis and each linkage assembly can move in a direction in response to motor assembly rotation about a motor assembly rotational axis. Portions of the treatment head assembly can rotate about one or more treatment head assembly rotational axes in response to linkage assembly movement. The treatment head assembly can include a treatment head, a fluid port that delivers a fluid into the treatment head, spraying tip(s) that spray the fluid onto an agricultural target object, and a fluid regulator that delivers the fluid from the fluid port to the spraying tip(s). The fluid regulator can be coupled to and can rotate with the treatment head, which can be movable.

Abstract: Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. The system uses a pump in combination with a fluid regulator to obtain and disperse fluid from the fluid tanks. The fluid regulator includes a fluid input port, a fluid output port and a fluid control valve. A first tube fluidly coupled from the fluid pump to the fluid input port. The system includes a moveable treatment head having one or more spraying tips, including a first spraying tip. A second tube is fluidly coupled from the fluid output port to the moveable treatment head. A system includes a controller configured to provide to the fluid regulator to open and close the fluid control valve to release an amount of the first fluid.

Abstract: Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include, receiving data representing a policy specifying a type of action for an agricultural object, selecting an emitter with which to perform a type of action for the agricultural object as one of one or more classified subsets, and configuring the agricultural projectile delivery system to activate an emitter to propel an agricultural projectile to intercept the agricultural object.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. Fluid may be provided through a first pressurized fluid line from a fluid source within an agricultural treatment system to a fluid port of a treatment head assembly of the agricultural treatment system. The fluid may be delivered from the fluid port to one or more spraying tips when the fluid regulator is actuated when in a desired position.

Abstract: A method includes receiving, by the treatment system, during operation in an agricultural environment, one or more images comprising one or more agricultural objects in the agricultural environment, identifying, in real-time, one or more objects of interest from the one or more agricultural objects by analyzing the one or more images, wherein the analyzing results in a first object being identified as belonging to one or more target objects and a second object being identified as not belonging to the one or more target objects, logging one or more results of the identification of each of the one or more objects of interest and a corresponding treatment decision; and activating the treatment mechanism to treat the one or more target objects.

Abstract: A method performed by a treatment system disposed on a moving platform, the treatment system having one or more processors, a storage and a treatment mechanism, comprising: receiving one or more images of an environment in which the moving platform is operating; identifying, in real-time, a pose of the moving platform using sensor inputs; identifying one or more target objects by processing the one or more images using a machine learning (ML) algorithm; and controlling the treatment mechanism to treat the one or more target objects by orienting the treatment mechanism towards the one or more target objects at least partially based on the pose.

Abstract: A method performed by a treatment system disposed on a moving platform, the treatment system having one or more processors, a storage and a treatment mechanism, comprising: receiving one or more images of an environment in which the moving platform is operating; identifying, in real-time, a pose of the moving platform using sensor inputs; identifying one or more target objects by processing the one or more images using a machine learning (ML) algorithm; and controlling the treatment mechanism to treat the one or more target objects by orienting the treatment mechanism towards the one or more target objects at least partially based on the pose.

Abstract: A method includes receiving, by the treatment system, during operation in an agricultural environment, one or more images comprising one or more agricultural objects in the agricultural environment, identifying, in real-time, one or more objects of interest from the one or more agricultural objects by analyzing the one or more images, wherein the analyzing results in a first object being identified as belonging to one or more target objects and a second object being identified as not belonging to the one or more target objects, logging one or more results of the identification of each of the one or more objects of interest and a corresponding treatment decision; and activating the treatment mechanism to treat the one or more target objects.

Abstract: Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include, at least, detecting an optical sight to align with an associated agricultural object, tracking the agricultural objects relative to the optical sight, predicting a parameter to track in association with agricultural object, and activating an emitter to apply an action based on the parameter.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an agricultural observation and treatment system and method of operation. The agricultural treatment system uses a treatment unit for emitting a laser at agricultural objects. The treatment unit is configured with a treatment head assembly that includes a moveable treatment head with one or more laser emitting tips. A first and second motor assembly are operated by the treatment unit to control the movement of the treatment head. The first motor assembly includes a first motor rotatable in a first rotational axis. A first linkage assembly is connected to the first motor and the treatment head assembly. The first linkage assembly is rotatable by the first motor. The second linkage assembly is rotatable by the second motor.

Abstract: Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include, receiving data representing a policy specifying a type of action for an agricultural object, selecting an emitter with which to perform a type of action for the agricultural object as one of one or more classified subsets, and configuring the agricultural projectile delivery system to activate an emitter to propel an agricultural projectile to intercept the agricultural object.

Abstract: Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include receiving data representing an image, detecting a portion of the image associated with a unit of spatial translation relative to a reference, identifying a subset of pixels to be formed on the surface, and causing emission of a subset of pixel projectiles directed to impact a portion of a surface to form a replica of a portion of the image.

Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.

Abstract: A method includes obtaining, by the treatment system configured to implement a machine learning (ML) algorithm, one or more images of a region of an agricultural environment near the treatment system, wherein the one or more images are captured from the region of a real-world where agricultural target objects are expected to be present, determining one or more parameters for use with the ML algorithm, wherein at least one of the one or more parameters is based on one or more ML models related to identification of an agricultural object, determining a real-world target in the one or more images using the ML algorithm, wherein the ML algorithm is at least partly implemented using the one or more processors of the treatment system, and applying a treatment to the target by selectively activating the treatment mechanism based on a result of the determining the target.

Abstract: Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include, at least, detecting an optical sight to align with an associated agricultural object, tracking the agricultural objects relative to the optical sight, predicting a parameter to track in association with agricultural object, and activating an emitter to apply an action based on the parameter.

Abstract: A method includes receiving, by the treatment system, during operation in an agricultural environment, one or more images comprising one or more agricultural objects in the agricultural environment, identifying, in real-time, one or more objects of interest from the one or more agricultural objects by analyzing the one or more images, wherein the analyzing results in a first object being identified as belonging to one or more target objects and a second object being identified as not belonging to the one or more target objects, logging one or more results of the identification of each of the one or more objects of interest and a corresponding treatment decision; and activating the treatment mechanism to treat the one or more target objects.