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 apparatuses, methods, systems, and computer program products described herein are directed to a treatment system. An example apparatus includes a treatment apparatus having a first fluid source, one or more channels for delivering a first fluid of the first fluid source, and a treatment unit, the treatment unit having one or more fluid regulators, including a first fluid regulator configured to regulate a flow of the first fluid received by the treatment unit, a movable treatment head unit having one or more spraying tips, a first channel fluidly coupling the one or more spraying tips with the first fluid regulator, wherein the first fluid regulator controls a volume of fluid emitted from the one or more spraying tips, an one or more controllers disposed in the treatment unit configured to control the one or more fluid regulators.

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 spraying fluid at agricultural objects. The treatment unit is configured with a treatment head assembly that includes a moveable treatment head with one or more spraying 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: 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 survey an agricultural environment. In some examples, a system can receive sensor data of a geographic boundary from one or more sensors onboard of the agricultural observation system, detect a plurality of external dynamic objects, a plurality of external static objects, one or more agricultural objects, or a combination thereof from the sensor data, determine a position of a component of the agricultural observation system relative to the plurality of external dynamic objects, the plurality of external static objects, the one or more agricultural objects, or a combination thereof, and generate a local map, in real time, via one or more processing units.

Abstract: A method implemented by a treatment system disposed on a vehicle, the treatment system having one or more processors, a storage, and a treatment mechanism, includes capturing a first image of a region of an agricultural environment, detecting, by implementing a first machine learning (ML) algorithm on a first portion of the first image, a presence of at least a portion of a first object in the first image, determining whether the first object detected is a treatment candidate, determining, upon determining that the first object is a treatment candidate, a first three dimensional (3D) location of at least a portion of the first object in the agricultural environment, and applying, a treatment to at least the portion of the first object by activating the treatment mechanism to interact with the first object.

Abstract: Various embodiments of methods, systems, and computer program products described herein are directed to a treatment system. An example method includes identifying a type of a first target agricultural object, based on the identified type of the first target agricultural object, determining a first spray profile for treating the first target agricultural object, sending instructions of a first treatment parameter to a treatment unit, and based on the first spray profile, activating the treatment unit to emit a first fluid at the first target agricultural object, wherein the first fluid regulator is moved to an opened position for an amount of time such that the first fluid is emitted, via the first spraying tip, as a first fluid projectile at the first target agricultural object for a first spray duration.

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 receive captured sensor data of an agricultural environment by one or more image capture devices, generate a first image from the captured sensor data, detect a first real-world agricultural object from the first image, determine a first pose of the first real-world agricultural object, identify the detected first real-world agricultural object as a new agricultural object or a preidentified agricultural object, and determine a treatment policy associated with the first real-world agricultural object.

Abstract: A method includes traversing, by the treatment system, along a path in an agricultural environment, receiving, by the treatment system, one or more sensor readings comprising one or more agricultural objects, identifying one or more objects of interest from the one or more agricultural objects by analyzing the one or more sensor readings, determining a first target object of the one or more objects of interest for treatment, selecting a treatment policy to treat the first target object, and activating the treatment mechanism to treat the first target object with the treatment policy.

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. 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: 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: 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 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: 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 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 computer-implemented method includes performing, using a processor onboard a vehicle, a machine learning (ML) processing on sensor input from sensors onboard an agricultural vehicle, identifying, according to a rule, a subset of data resulting from the ML processing and generating and displaying, in real-time, the subset of data to a user interface, thereby enabling a user interaction with the subset of data.

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: 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.