The present invention provides a fruit harvesting, dilution and/or pruning system comprising: (a) a computerized system for mapping an orchard or a map of trees position and their contour in a plantation; (b) a management system for autonomous unmanned aircraft vehicle (UAV) fleet management for harvesting, diluting or pruning fruits; and a method for UAV autonomous harvesting, dilution and/or pruning of an orchard.

The present invention provides a fruit harvesting, dilution and/or pruning system comprising: (a) a computerized system for mapping an orchard or a map of trees position and their contour in a plantation; (b) a management system for autonomous unmanned aircraft vehicle (UAV) fleet management for harvesting, diluting or pruning fruits; and a method for UAV autonomous harvesting, dilution and/or pruning of an orchard.

A system and method for obtaining real-time data regarding the condition of a crop and planning and executing an irrigation cycle in response to the data. The invention uses an unmanned aerial vehicle to survey the conditions within an irrigated area. The irrigation system includes components to vary the amount of water dispensed within particular areas. The data obtained is used to create an irrigation schedule that the irrigation system then carries out. For example, surveyed areas that contain more moisture may be given relatively less water during the next irrigation cycle. The data obtained may also be used to alter a scheduled delivery of fertilizer, pesticide, or some other substance.

Systems and methods are provided for imposing physical actions, by endpoints, based on activities by users. One such method includes imposing a physical actions via a drone, by an endpoint associated with the drone, based on an activity undertaken by a user. The method includes receiving, by a computing device, an activity message including data indicative of an activity of a user and retrieving at least on rule from a data structure based on the data indicative of the activity where the at least one rule includes a physical action for said activity of the user. The method then includes identifying, by the computing device, the physical action from the at least one rule and transmitting, by the computing device, an order for the physical action to an endpoint, whereby the endpoint commands a drone to perform the physical action.

A housing for a ground vehicle-mountable aerial vehicle is provided. The housing includes a base portion defining a cavity and an opening leading into the cavity. The cavity is structured to receive an unmanned aerial vehicle therein. The cavity is configured so as to open upwardly when the housing is mounted on the vehicle. The housing also includes a drafting wall structured to extend from the base portion at a location forward of at least a portion of the cavity when the housing is mounted on the ground vehicle.

Phased array radar systems for unmanned aerial vehicles (UAVs) are disclosed. A disclosed example radar apparatus for a small UAVs includes a transmitter to transmit a transmit signal in the X-band, a receive phased array including at least two receive antennas, wherein the receive phased array provides a field-of-view of at least 100 degrees in a first direction and at least 20 degrees in a second direction perpendicular to the first direction, a first processor programmed to determine a location of an object based on an output from each of the at least two antennas, a second processor programmed to perform collision avoidance based on the location of the object, and a mount to mechanically couple the radar apparatus to the UAV.

Drone-based inventory management method and systems. One embodiment provides a drone-based inventory management system including one or more unmanned aerial vehicles (UAVs), and a central management system having an electronic processor, and a transceiver configured to communicate with the one or more UAVs. The electronic processor is configured to determine a discrepancy in inventory and select a UAV for verification. The electronic processor is also configured to determine whether weather permits UAV operation and operate the UAV in a pre-determined route when the weather permits UAV operation. The electronic processor is further configured to capture images using the UAV and determine new inventory based on captured images. The electronic processor is also configured to update inventory based on the new inventory.

An introduced autonomous aerial vehicle can include multiple cameras for capturing images of a surrounding physical environment that are utilized for motion planning by an autonomous navigation system. In some embodiments, the cameras can be integrated into one or more rotor assemblies that house powered rotors to free up space within the body of the aerial vehicle. In an example embodiment, an aerial vehicle includes multiple upward-facing cameras and multiple downward-facing cameras with overlapping fields of view to enable stereoscopic computer vision in a plurality of directions around the aerial vehicle. Similar camera arrangements can also be implemented in fixed-wing aerial vehicles.

In some examples, a computing device receives, from an unmanned aerial vehicle (UAV), a first image from a first camera on the UAV and a plurality of second images from a plurality of second cameras on the UAV. The plurality of second cameras may be positioned on the UAV for providing a plurality of different fields of view in a plurality of different directions around the UAV. Further, the first camera has a longer focal length than the second cameras. The computing device presents, on a display, a composite image including at least a portion of the first image within a merged image generated from the plurality of second images. The presented composite image enables a user to at least one of: zoom out from the at least one first image to the merged image, or zoom in from the merged image to the at least one first image.

A method of communicating between an aerial vehicle and a cellular radio access network is described. In some cases, the method includes determining a current location of the aerial vehicle; determining, in response to the current location, a location of a nearest cell of the cellular radio access network; and processing communications between the aerial vehicle and the cellular radio access network, using the nearest cell as a serving cell. When the method is performed on-board an aerial vehicle, the method further includes orienting a directional antenna of the aerial vehicle toward the location of the nearest cell.