Abstract: A computer-implemented method includes obtaining image data representing a set of images of a worksite captured by an image capture component of a mobile computing device, identifying a set of virtual markers associated with the set of images, each virtual marker having a corresponding position in one of the images, and determining, for each virtual marker, a set of coordinates in a coordinate system based on the corresponding position of the virtual marker. Based on the set of coordinates, boundary data is generated that represents a boundary on the worksite. The boundary data is communicated to a robotic mower for control of the robotic mower within an operating area defined based on the boundary.

Abstract: A user defines a boundary of a mowed area on an image of the mowed area, on a mobile device. An optimization algorithm operates on the bounded mowing area to identify a beacon configuration that identifies a location for each of a plurality of different beacons to be placed about the mowing area. The user can then be guided to the different beacon locations, in order to place a beacon at each of the different beacon locations, using an augmented reality system that provides user assistance on a camera view of the user's mobile device.

Abstract: A scouting system can include an autonomous ground vehicle having a perception sensor and a motion sensor to construct an occupancy grid referenced to a coordinate system of the autonomous ground vehicle. The autonomous ground vehicle is configured to use information from the occupancy grid to detect crop rows in a crop field. The autonomous ground vehicle is configured to identify and classify one or more non-crop plant in-lier objects arranged within the crop rows and generate an output signal received by an external vehicle to cause the external vehicle to perform a task when the one or more non-crop plant in-lier objects are identified within the crop rows.

Abstract: A computer-implemented method includes obtaining image data representing a set of images of a worksite captured by an image capture component of a mobile computing device, identifying a set of virtual markers associated with the set of images, each virtual marker having a corresponding position in one of the images, and determining, for each virtual marker, a set of coordinates in a coordinate system based on the corresponding position of the virtual marker. Based on the set of coordinates, boundary data is generated that represents a boundary on the worksite. The boundary data is communicated to a robotic mower for control of the robotic mower within an operating area defined based on the boundary.

Abstract: A scouting system can include an autonomous ground vehicle having a perception sensor and a motion sensor to construct an occupancy grid referenced to a coordinate system of the autonomous ground vehicle. The autonomous ground vehicle is configured to use information from the occupancy grid to detect crop rows in a crop field. The autonomous ground vehicle is configured to identify and classify one or more non-crop plant in-lier objects arranged within the crop rows and generate an output signal received by an external vehicle to cause the external vehicle to perform a task when the one or more non-crop plant in-lier objects are identified within the crop rows.

Abstract: Embodiments include a ground scout having an ability to identify the location of rows of crops and the end of the rows so that it can navigate, but in other embodiments, the ground scout can also rely more on an aerial drone to navigate, to act as a communication relay system, and so on. A buddy system including a ground scout and an air scout (e.g. drone) communicate their findings with each other.

Abstract: Computer-implemented methods for mapping sensor tags of assets to input ports of an analytic process are disclosed. In an embodiment, a processor receives a selection by a user of an analytic process to run on a plurality of assets, automatically maps the analytic input ports of the selected analytic process to sensor tags of each of the plurality of assets that have matching tag names, and determines which analytic input ports have not been fully mapped. The processor then provides a map by asset option and a map by tag option to the user device, receives a selection of the map by asset option, provides an unmapped assets list including at least one asset that is not fully mapped and a list of tag alias names, and then receives a selection from the user device of an asset from the unmapped assets list along with selections of tag alias names mapped to the unmapped analytic input ports of the selected analytic process.

Abstract: Embodiments include a ground scout having an ability to identify the location of rows of crops and the end of the rows so that it can navigate, but in other embodiments, the ground scout can also rely more on an aerial drone to navigate, to act as a communication relay system, and so on. A buddy system including a ground scout and an air scout (e.g. drone) communicate their findings with each other.

Abstract: A sensing system collects position data associated with one or more obstacles within a certain range of a vehicle. A former establishes an occupancy grid based on the collected position data. A motion monitoring module determines a reaction distance and a deceleration distance associated with a vehicle at a regular time interval during an operational state. A safety guidance module establishes a safety zone (e.g., safety zone grid) for the regular time interval based on the occupancy grid, the determined reaction distance, and the deceleration distance.