An unmanned aerial vehicle (UAV) carries a camera, sends data from the camera, and receives commands. The UAV is connected to a messaging platform. Pictures or video clips received from the UAV are selected and placed in messages broadcast by an account associated with the UAV. Video footage from the camera is live-streamed in a card-type message. Account holders of the messaging platform may control the UAV with commands embedded in messages and directed towards an account associated with the UAV. Controllable elements of the UAV include UAV location, camera orientation, camera subject, UAV-mounted lighting, a UAV-mounted display, a UAV-mounted projector, UAV-mounted speakers, and a detachable payload. UAV control may be determined through democratic means. Some UAV functionality may be triggered through aggregated engagements on the messaging platform. The UAV may include a display screen and/or a microphone to provide for telepresence or interview functionality.

The devices and methods described herein integrate security and/or recording mechanisms into unmanned vehicle interdiction devices to prevent unauthorized use and to record information related to operation of the unmanned vehicle interdiction device, identification of an unmanned vehicle, location of the unmanned vehicle, and operation of the unmanned vehicle.

A system for navigating a vehicle automatically from a current location to a destination location without a human operator is provided. The system of the vehicle includes a global positioning system (GPS) for identifying a vehicle location and a communications system for communicating with a server of a cloud system. The server is configured to identify that the vehicle location is near or at a parking location. The communications system is configured to receive mapping data for the parking location from the server, and the mapping data is at least in part used to find a path at the parking location to avoid a collision of the vehicle with at least one physical object when the vehicle is automatically moved at the parking location. The mapping data is processed by electronics of the vehicle so that when the vehicle is automatically moved collision with the at least one physical object is avoided and the electronics of the vehicle is configured to process a combination of sensor data obtained by sensors of the vehicle. The processing of the sensor data uses image data obtained from one or more cameras and light data obtained from one or more optical sensors.

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.

Some embodiments of the invention relate to generating correction information based on global or regional navigation satellite system (NSS) multiple-frequency signals observed at a network of reference stations, broadcasting the correction information, receiving the correction information at one or more monitoring stations, estimating ambiguities in the carrier phase of the NSS signals observed at the monitoring station(s) using the correction information received thereat, generating residuals, generating post-broadcast integrity information based thereon, and broadcasting the post-broadcast integrity information. Other embodiments relate to receiving and processing correction information and post-broadcast integrity information at NSS receivers or at devices which may have no NSS receiver, as well as to systems, NSS receivers, devices which may have no NSS receiver, processing centers, and computer programs. Some embodiments may for example be used for safety-critical applications such as highly-automated driving and autonomous driving.

Disclosed are systems, methods and devices for centralized control of autonomous vehicles. In some embodiments, a system and method allow an autonomous control system on-board an autonomous vehicle to pass control of the autonomous vehicle to an offboard panel of experts upon encountering an anomaly. In some embodiments, a system and method allow a regulatory entity to proactively distribute rules and requirements to autonomous vehicles while operating within a regulated space.

Systems and methods for automatically identifying and ascertaining an estimated amount of damage at a location by utilizing one or more autonomous vehicles, e.g., “drone” devices, to autonomously capture data of the location and utilizing Artificial Intelligence (AI) logic modules to analyze the captured data and construct a 3-D model of the location.

An aircraft control device and a remote controller aircraft are disclosed. The aircraft control device includes a first channel configured to receive first control information outputted by a remote controller and transmit the first control information to an aircraft; a second channel configured to receive second control information outputted by the remote controller and transmit the second control information to a camera and/or a gimbal; and a switch unit configured to switch that the first control information is received by the second channel and transmitted to the aircraft when the first channel is disturbed or a distance between the remote controller and the aircraft is larger than a distance threshold. The present invention is able to switch the transmission route of the first control information between the first channel and the second channel in accordance with situations of the first channel and the second channel.

A method for monitoring an unmanned aerial vehicle (UAV) includes a processor obtaining a datagram based on monitoring data for a UAV-detector communication between the UAV and one or more detectors. The monitoring data indicates at least one of a location of the UAV or a location of a control station in communication with the UAV. The method further includes determining a risk level by retrieving pre-stored risk information associated with the UAV based on the datagram.

One variation of a method for accessing supplemental data from other vehicles includes, at an autonomous vehicle: recording a scan image of a scene around the autonomous vehicle at a first time; detecting insufficient perception data in a region of the scan image; in response to detecting insufficient perception data in the region, defining a ground area of interest containing the region and wirelessly broadcasting a query for perception data representing objects within the ground area of interest; in response to receiving supplemental perception data—representing objects within the ground area of interest detected by the second vehicle at approximately the first time—from a second vehicle proximal the scene, incorporating the supplemental perception data into the scan image to form a composite scan image; selecting a navigational action based on objects in the scene represented by the composite scan image; and autonomously executing the navigational action.