A buoyant aerial vehicle includes: a balloon configured to store a gas; a payload coupled to the balloon; and a propulsion unit coupled to the payload by a tether. The propulsion unit includes: a fuselage having a substantially longitudinal shape, a first end, and a second end; a primary airfoil coupled to the fuselage; a secondary airfoil coupled to the fuselage at one of the first end or the second end; and a thrust generating device disposed at one of the first end or the second end and configured to move the propulsion unit relative to the payload along a propulsion flight path. The movement of the propulsion unit imparts movement of the buoyant aerial vehicle along a vehicle flight path.

An unmanned aerial vehicle with deployable components (UAVDC) is disclosed. The UAVDC may comprise a fuselage, at least one wing, and at least one control surface. In some embodiments, the UAVDC may further comprise a propulsion means and/or a modular payload. The UAVDC may be configured in a plurality of arrangements. For example, in a compact arrangement, the UAVDC may comprise the at least one wing stowed against the fuselage and the at least one control surface stowed against the fuselage. In a deployed arrangement, the UAVDC may comprise the at least one wing deployed from the fuselage and the least one control surface deployed from the fuselage. In an expanded arrangement, the UAVDC may comprise the at least one wing telescoped to increase a wingspan of the deployed arrangement.

A controller for an unmanned aerial vehicle (UAV) comprising an image capture means, the controller comprising: inputs arranged to receive: positional data relating to the UAV, a vehicle and a user device; image data captured by the image capture means; a processor arranged to process the received positional data to determine the relative locations of the UAV, vehicle and user device; an output arranged to output a control signal for controlling the UAV and to output an image signal comprising captured image data; wherein the processor is arranged to: generate the control signal for the UAV such that the image data captured by the image capture means comprises at least an image of an obscured portion of the vehicle that is obscured from a field of view of a user of the user device.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for using a drone to test a sensor. In one aspect, the method includes actions of detecting a message (i) broadcast by the drone and (ii) indicating that the drone is going to administer a test of a sensor, determining, by the monitoring system and based on the message and (i) sensor data generated by the sensor in response to the administration of the test, by the drone, within a predetermined period of time of the message or (ii) a lack of sensor data generated by the sensor in response to the administration of the test, by the drone, within a predetermined period of time of the message, whether the sensor is functioning properly, and in response to a determination that the sensor is not functioning properly, storing data indicating that the sensor is not functioning properly.

An aerial vehicle is programmed or configured to respond to reports of events or conditions within spaces of a facility. The aerial vehicle travels to a location of a reported event or condition and captures data using onboard sensors. The aerial vehicle independently determines whether the reported event or condition is occurring, or is otherwise properly addressed by resources that are available at the location, using images or other data captured by the onboard sensors. Alternatively, the aerial vehicle transmits a request for additional resources to be provided at the location, where necessary. A map of the location generated based on images or other data captured by the onboard sensors may be utilized for any purpose, such as to make one or more recommendations of products that are appropriate for use at the facility.

A response system may be provided. The response system may include a security system and an autonomous drone. The security system includes a security sensor and a controller. The drone includes a processor, a memory in communication with the processor, and a drone sensor. The processor may be programmed to receive the deployment request from the security system, navigate to the one or more zones of the coverage area included in the deployment request, collect drone sensor data of the one or more zones of the coverage area using the at least one drone sensor, determine that an incident has occurred, and/or transmit the collected drone sensor data and incident verification to the security system, wherein, in response to receiving the collected drone sensor data and incident verification, the security system is configured to generate a command for responding to the incident.

The system for managing bird populations includes a drone; a disruptor comprising an extension arm having a proximal end and a distal end, the proximal end being operatively coupled with the drone, and the distal end comprising a tool portion, where the tool portion comprises a piercing element constructed for engagement with one or more eggs in a nest; and a remote control system. The remote control system may comprise one or more remote control units and a monitor.

The system can be used to manage bird populations by flying the drone above a bird's nest; positioning the drone above the bird's nest; and descending the drone to disrupt eggs in the bird's nest with the disruptor.

Methods, computer program products, and systems are presented. The methods include, for instance: providing a cognitive tour guide service to a group of participants for a tour with an initial route planned by participants registration information and environment information along the initial route. During the tour, real time sensory data on the participants and environment are collected by a cognitive agent accompanying the group to lead the tour are relayed to a cognitive tour guide engine, and real time multi-objective optimization is modeled and performed. The participants are regrouped responsive to their respective objectives of the tour as represented by respective levels of interest in certain stage of the tour as well as circumstances of the environment. Respective subgroups are formed from the participants per respective objectives, and respective new routes are selected from a set of optimal solutions for each subgroup. During the tour, the cognitive tour guide engine iteratively optimizes routes responsive to incoming real time sensory data, objectives of the tour, and participant feedback.

An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

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.