In some examples, systems and methods are described for output biasing maneuvers recommendations provided by at least one machine learning maneuver-recommendation (MLM) engine executing on an aerial vehicle. In some examples, output biasing data can be received that includes at least one risk tuning parameter that can influence which of the maneuver recommendations are selected by a maneuver decision engine executing on the aerial vehicle based on a maneuver confidence threshold for implementation by the aerial vehicle. The maneuver confidence threshold can be updated based on the at least one risk tuning parameter to provide an updated maneuver confidence threshold for the output biasing of the maneuvers recommendation provided by the at least one MLM engine. Vehicle command data for implementing a given maneuver recommendation can be outputted based on an evaluation of the updated maneuver confidence threshold.

According to the present invention, a drone control system includes: a flying drone; a cloud server configured to transmit and receive information to and from the drone by wireless communication; and a ground control system configured to establish a flight plan of the drone by connecting the drone and the cloud server by the wireless communication.

A system includes a processing circuit onboard an aircraft and configured to determine an optimum cruise profile for the aircraft based on a flight plan, a characteristic of the aircraft, and an environmental characteristic. The processing circuit is also configured to determine an optimized cruise vertical path based on the optimum cruise profile and air traffic information of at least one other aircraft, and control an autopilot system of the aircraft to cause the aircraft to follow the optimized cruise vertical path.

An electric aircraft with flight trajectory planning. The electric aircraft includes a sensor. The sensor is coupled to the electric aircraft. The sensor is configured to detect a plurality of weather measurements. The electric aircraft includes a processor. The processor is communicatively connected to the sensor. The processor is configured to receive, from the sensor, a weather measurement of the plurality of weather measurements. The processor is configured to receive, from a user, a destination datum and a desired altitude datum. The processor is configured to determine an optimal trajectory of the electric aircraft as a function of the destination datum, weather datum, and altitude datum.

An information processing apparatus includes a controller. The controller is configured to acquire travel information including a travel route for when the vehicle travels and determine, based on the acquired travel information, transfer information for when a delivery item to be delivered by an unmanned aircraft to a user on board the vehicle is transferred to the user.

A machine learning maneuver model can be programmed to generate maneuver data identifying a plurality of flight paths for maneuvering an aerial vehicle through an adverse weather condition and a flight path confidence score for each flight path of the plurality of flight paths based on at least weather sensor data characterizing the adverse weather condition. The flight path confidence score can be indicative of a probability of successfully maneuvering the aerial vehicle through the adverse weather condition according to a respective flight path. A maneuver decision engine can be programmed to evaluate each flight path confidence score for each flight path relative to a flight path confidence threshold to identify a given flight path of the plurality of flight paths through the adverse weather condition that poses a least amount of structural risk to the aerial vehicle.

A device receives a request for a flight path of UAV from a first location to a second location in a region, and determines, based on credentials associated with the UAV, whether the UAV is authenticated for utilizing the device and a network. The device determines, when the UAV is authenticated, capability information for the UAV based on the request and component information associated with the UAV. The device calculates the flight path from the first location to the second location based on the capability information and one or more of weather information, air traffic information, obstacle information, or regulatory information associated with the region. The device generates flight path instructions for the flight path based on one or more of the weather information, the air traffic information, the obstacle information, or the regulatory information associated with the region, and provides the flight path instructions to the UAV.

A weather forecasting system may receive satellite image samples and identify an updraft and components of the updraft within a cloud. These satellite image samples are collected over time (e.g., at 30 second to 1 minute time intervals). The system may identify an area of rotation and/or divergence at cloud top in a cumulus cloud or mature convective storm over time by comparing the samples and determine a parameter indicative of the updraft based on the area of rotation and divergence. The system may estimate aspects of the environment related to storm development and predict the occurrence of a weather event in the future based on the parameter and generate an output indicative of the occurrence.

It is prevented that a communication relay apparatus in an upper airspace, which is suitable for constructing a three-dimensional network, falls by a strong wind. A communication relay apparatus is provided with a relay communication station that performs a radio communication with a terminal apparatus, and is capable of flying in an upper airspace by an autonomous control or an external control. This communication relay apparatus includes a flight control section that controls a flight of the communication relay apparatus based on flight control information determined so as to reduce an influence of a strong wind generated around the communication relay apparatus. The flight control information may include information for controlling at least one of a flight direction, velocity, altitude, attitude, flight route and flight pattern of the communication relay apparatus.

A method for controlling an autonomous unmanned aerial vehicle for delivery of a medication package includes determining a thermal control period for the medication package. The method also includes identifying a delivery location corresponding to the medication package. The method also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between a starting location and the delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the delivery location. The method also includes determining whether to deliver the medication package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.