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.

The location detection unit detects a destination location for delivery of an item by a drone. The release determination unit determines whether the drone transporting the item can release and place the item at the destination. Upon determination that the release and placement is not possible, a standby airspace determination unit determines a standby airspace within which the drone waits. The wait-time determination unit determines a wait-time for the drone in the determined standby airspace. The wait-time determination unit determines a wait-time by which the drone can arrive at a next destination by a scheduled arrival time following departure of the drone departs after standby. The standby instruction unit issues to the drone an instruction related to the standby.

An apparatus is provided for detecting and avoiding objects in real-time. The apparatus includes a first sensor that collects environmental data and a second sensor that collects external data corresponding to an external object within a detection range from the apparatus. The apparatus further includes a processor that, in real-time, calculates a minimum distance to avoid the external object, based at least in part on the environmental data and the external data, monitors the environmental data and the external data, and controls the apparatus to avoid the external object based on the calculated minimum distance and the monitored environmental data and external data.

A control system acquires predicted tsunami information, and generates a flight plan for unmanned aerial vehicles. The flight plan includes flight paths along safety boundaries between an expected damage area and a safe area. The expected damage is an area expected to be damaged by the tsunami indicated by the predicted tsunami information. The safe area is an area to be safe from damage caused by the tsunami. The control system transmits the flight plan to the unmanned aerial vehicles.

A method of displaying, on a screen of a mobile device, time on target information for an aircraft in flight. The method includes displaying a current location of the aircraft on a map, a waypoint between a departure point and a destination point, a symbol indicating the waypoint in a first area of the screen overlapping the map, and a first pop-up window in a second area of the screen overlapping the first area. The first pop-up window displays a current arrival time at the waypoint and an input area to receive an adjustment to the current arrival time.

Disclosed are methods, systems, and non-transitory computer-readable media for detecting wind shear conditions in an urban airspace. For instance, the method may include obtaining aircraft information related to an aircraft in the urban airspace, accessing three-dimensional building information corresponding to the airspace, obtaining wind speed and direction data from a plurality of sensors provided about the airspace, and detecting wind shear conditions in at least a portion of the airspace based on the obtained wind speed and direction data. The method may further include determining real-time flight safety parameters in the portion of the airspace based on the wind shear conditions detected in at least the portion of the airspace, analyzing the determined real-time flight safety parameters along a designated flight path through the portion of the airspace to determine whether an unsafe flight condition exists, and transmitting the analysis to the aircraft or a remote operating station.

A method of automatically determining a flight trajectory of a vertical take-off and landing aircraft having vectorable propulsion can be used to improve flight efficiency. The method includes receiving one or more aircraft flight constraints, inputting the aircraft flight constraints to a trajectory planning algorithm to determine a minimum energy aircraft transition trajectory, and outputting a control schedule to fly the aircraft to along the flight trajectory.

The UAV 1a includes a dust sensor 16 and a dust-preventing function 17 and performs a processing for a different UAV 1b not provided with a dust-preventing function on the basis of a dust amount detected by the dust sensor 16 during a flight of the UAV 1a.

Method and device for determining trajectory to optimal position of a follower aircraft with respect to vortices generated by a leader aircraft. The method includes controlling trajectory of a follower aircraft to an optimal position where the follower aircraft benefits from effects of at least one of the vortices of a leader aircraft. A first section control step controls flight of the follower aircraft using current measurements of flight parameters, from a safety position to a search position, along an approach section passing through an approach zone. A second section control step controls flight of the follower aircraft using current measurements of flight parameters, from the search position to a precision position, along a search section passing through a search zone, and a third section control step controls flight of the follower aircraft, from the precision position to the optimal position, along an optimization section passing through an optimization zone.

Systems and methods are described herein for determining an optimized flight route for an aerial vehicle. In some examples, weather conditions for the aerial vehicle during a flight can be predicted based on weather data. At least two flight route segments based on the predicted weather data can be determined. The at least two flight route segments can include one of a solar flight route segment and a thermal flight route segment. A respective flight route segment of the at least two flight route segments can be discarded that can cause the aerial vehicle to violate a flight constraint. A replacement flight route segment for the respective discarded flight route segment can be determined. An optimized flight route for the aerial vehicle can be generated based on the replacement flight route segment and at least one remaining flight route segment of the at least two flight route segments.