Unmanned Aerial Vehicles also known as UAVs or Drones, either autonomous or remotely piloted, are classified as drones by the US Federal Aviation Administration (FAA) as weighing under 212 pounds. The system described herein details Autonomous Flight Vehicles (AFV) which weigh over 212 pounds but less than 1,320 pounds which may require either a new classification or a classification such as Sport Light Aircraft, but without the requirement of a pilot due to the safe autonomous flight system such as the Safe Temporal Vector Integration Engine or STeVIE. Safe Autonomous Light Aircraft (SALA) are useful as drone carriers, large scale air package or cargo transport, and even human transport depending on the total lift capability of the platform.

[Object] [Solving Means] A moving body according to an embodiment of the present technology includes an imaging unit, a first detection unit, and a control unit. The first detection unit detects a front direction of the moving body. The control unit controls a posture around a first axis of the imaging unit to a posture specified by a steering apparatus based on an output of the first detection unit, an output of a second detection unit that detects a front direction of the steering apparatus that steers the imaging unit, and input data generated by the steering apparatus.

Disclosed is an elevator inspection system, having: a sensor implement; a robotic platform supporting the sensor, the robotic platform configured to inspect a hoistway; a controller operationally connected to the robotic platform and the sensor, wherein the controller is configured to define hoistway model data for the hoistway, from sensor data, corresponding to locations and shape boundaries of the hoistway and doorway openings formed in the hoistway.

Said control system comprises: a remote device comprising: a remote module for acquiring flight plan data, and a remote module for calculating a remote trajectory or a remote setpoint according to the flight plan data; an on-board device comprising: an on-board module for acquiring flight plan data, an on-board module for calculating an on-board trajectory or an on-board setpoint according to the data acquired by the on-board acquisition module.

The remote device comprises a module for validating the trajectory which is configured to: acquire the on-board and remote trajectory or setpoint; validate or reject the on-board trajectory or setpoint according to the remote trajectory or setpoint; transmit the result of the validation to the on-board device.

A method for securing a geographical area encompassing a route. A map of the area is obtained. A weapon is associated with a firing modeling consisting of a probability model of hitting its target when shooting, as a function of the firing distance. Positions of potential shelters of threats on the map are determined by using a trained artificial intelligence device. The modeling is applied for each weapon and potential shelter while relating the shots to the route and summing all the probabilities of hitting its target on each portion of the route. The potential shelters most likely to constitute attack threats along the route are determined. A path is defined in order to address these potential shelters most likely to constitute attack threats.

According to a technical aspect of the invention, there is provided a multiple unmanned aerial vehicles navigation optimization method is performed at a ground base station which operates in conjunction with unmanned aerial vehicles-base stations which are driven by a battery to move and cover a given trajectory point set, the multiple unmanned aerial vehicles navigation optimization method including: calculating an age-of-information metric by receiving an information update from the unmanned aerial vehicles-base stations through communication, when the ground base station is present within a transmission range of the unmanned aerial vehicles-base stations; setting conditions of a trajectory, energy efficiency, and age of information of each of the unmanned aerial vehicles-base stations; and executing Q-learning for finding a trajectory path policy of each of the unmanned aerial vehicles-base stations, so as to maximize total energy efficiency of an unmanned aerial vehicles-base station relay network to which the energy efficiency and the age of information are applied. According to the invention, the following effects are obtained. Age of information (AoI) that is a new matrix used to measure up-do-dateness of data is set, an edge computing environment for a remote cloud environment is provided by using the AoI, and a computing-oriented communications application can be executed by using the edge computing environment.

A modular flat-packable drone kit includes a plurality of components that can be assembled into a drone. Components of the drone kit include elements that may be cut from a flat sheet of material, thereby enabling low cost manufacturing and compact packaging and may be assembled without specialized tools. A set of drones may operate in a standalone mode or may be coupled together and operated in a group configuration.

Systems, devices, and methods for: an unmanned aerial vehicle (UAV); at least one sensorless motor of the UAV, the at least one sensorless motor comprising a set of windings and a rotor; at least one propeller connected to the at least one sensorless motor; a microcontroller in communication with the at least one sensorless motor, wherein the microcontroller is configured to: determine a rotation rate of the at least one propeller; determine a rotation direction of the at least one propeller; provide an output to stop the at least one propeller if at least one of: the determined rotation rate is not a desired rotation rate and the determined rotation direction is not a desired rotation direction; and provide an output to start the at least one propeller if the at least one propeller is stopped at the desired rotation rate and the desired rotation direction.

A fractal unmanned aircraft system (200) includes a first module (100), a second module (100) and a third module, (100) each having a top member (120) and a first thruster (130) affixed thereto. Each module (100) is laterally coupled to each other. A fourth module (100) has a bottom that is affixed to the top members (120) of the first module(100), the second module (100) and the third module (100) so as to form a tetrahedral structure. A power source (220) supplies power to the first thrusters (130). A control circuit (222) controls the unmanned aircraft system so as to cause the fractal unmanned aircraft system (200) to fly in a controlled manner.

A control method and device of a movable platform, a movable platform, and a storage medium are provided. The control method may include acquiring a control amount for controlling the movable platform; converting the control amount into control instruction of the movable platform based upon a position of the movable platform and a position of a target object photographed by the movable platform; and controlling the movable platform to move relative to the target object according to the control instruction.