A vehicle is provided that comprises two or more radio frequency (RF) antennas and two or more RF transceivers to communicate wirelessly sensitive information associated with a user of the vehicle (the two or more RF antennas being at different physical locations on an exterior of the vehicle). The vehicle determines which one of the two or more RF antennas is receiving a strongest signal from a common signal source, selects a first RF transceiver associated with the RF antenna with the strongest signal to send the sensitive information associated with the user to the common signal source, and sends the sensitive information associated with the user to the first RF transceiver for transmission to the common signal source.

A mobile robot includes a receiving unit that receives a request for providing a service, a notifying unit that notifies a client that the request is received by performing an operation oriented toward the client who has made the request, a moving unit that moves toward a user designated as a receiver of the service in accordance with the request, and a providing unit that provides the service.

A protection system for a classroom or other space to protect against a terrorist. The system includes a fixed control unit and a mobile control unit. The fixed control unit contains a hanger for drones to be launched against the terrorist. The fixed control unit also includes data storage units, a computer, a computer program and a memory, power storage units, a sighting laser for obtaining location information about the terrorist and an etching laser for marking the terrorist, an optics system for receiving visual information, and a telecommunication unit to send and receive information. The mobile control unit is worn by a protecting person in the space and includes some of the same components as the fixed control unit. It also has a local aiming system that includes for example a rifle type sight. The drone is a self-contained, self-propelled robotic flying vehicle that can be very small or even the size of a mouse. It has a mag-lev engine, electrical storage units and an aeronautically shaped body.

Systems, methods and apparatuses for inspecting a tank containing a flammable fluid are provided. The system includes a vehicle having a propeller, a latch mechanism, a pressure switch, and an inspection device. The system includes a control unit in communication with the propeller, the latch mechanism, and the inspection device, and electrically connected to the pressure switch. The control unit powers on responsive to the pressure switch detecting an ambient pressure greater than a minimum threshold. The control unit receives, from the latch mechanism, an indication of a state of the latch mechanism. The control unit determines that the cable used to lower the vehicle into the tank containing the flammable fluid is detached from the vehicle. The control unit commands the propeller to move the vehicle through the flammable fluid. The control unit determines a quality metric of a portion of the tank.

A flight task processing method includes generating and displaying a user prompt according to flight data of a plurality of flight tasks, selecting one of the flight tasks as a target flight task in response to a selection operation with respect to the user prompt, determining the flight data of the target flight task, processing the flight data of the target flight task to obtain control instruction, and automatically controlling an operation of an aerial vehicle according to the control instruction to reproduce the target flight task by controlling the aerial vehicle to fly to a waypoint included in the flight data, controlling a gimbal of the aerial vehicle to face a gimbal orientation included in the flight data while the aerial vehicle is at the waypoint, and controlling a camera carried by the gimbal to acquire an image while the aerial vehicle is at the waypoint.

A device and method for remotely controlling an unmanned aerial vehicle based on reinforcement learning are disclosed. An embodiment provides a device for remotely controlling an unmanned aerial vehicle based on reinforcement learning, where the device includes a processor and a memory connected to the processor, and the memory includes program instructions that can be executed by the processor to determine an inclination direction corresponding to the hand pose of a user, the movement direction of the hand, and the angle in the inclination direction based on sensing data associated with the pose of the hand or the movement of the hand acquired by way of at least one sensor, and determine one of a movement direction, a movement speed, a mode change, a figural trajectory, and a scale of the figural trajectory of the unmanned aerial vehicle according to the determined inclination direction, movement direction, and angle.

A control device of a moving object includes: a communication unit configured to communicate with an information terminal carried by a user of the moving object; and a controller configured to perform movement control of the moving object. When a predetermined operation from the user of the moving object is received, the controller transmits inquiry information on driver determination to the information terminals around the moving object, the controller receives predetermined answer information for the inquiry information, the controller selects an information terminal, which is a transmission source of the answer information that is received first, as a driver terminal, and the controller performs movement control of the moving object based on movement instruction information from the driver terminal.

A system for producing a control signal of an electric vertical take-off and landing (eVTOL) aircraft includes a flight controller configured to obtain a requested aircraft force, generate an optimal command mix, wherein the optimal command mix includes a plurality of commands to a plurality of actuators as a function of the requested aircraft force, wherein generating further comprises receiving an ideal actuator model includes at least a performance parameter, producing a model datum as a function of the ideal actuator model, and generating the optimal command mix as a function of the request aircraft force and the model datum, and produce a control signal as a function of the optimal command mix.

A vehicle remote instruction system 100 transmits a remote instruction request from an autonomous driving vehicle 2 to a remote instruction apparatus 1, and controls travel of the autonomous driving vehicle 2 based on a remote instruction transmitted from the remote instruction apparatus 1 in response to the remote instruction request. The vehicle remote instruction system 100 includes a delay determination unit 39 configured to determine whether or not a communication delay occurs between the remote instruction apparatus 1 and the autonomous driving vehicle 2, and a rejection unit 40 configured to reject the remote instruction transmitted in response to the remote instruction request if it is determined by the delay determination unit 39 that the communication delay occurs.

A method for controlling an unmanned aerial vehicle (UAV) includes obtaining a signal strength of a remote control signal received by the UAV, obtaining a movement path of the UAV in response to the signal strength being less than a preset strength threshold, controlling the UAV to enter a backtrack return mode to return along the movement path, and controlling the UAV to exit the backtrack return mode in response to the signal strength being greater than the preset strength threshold. The movement path of the UAV includes position information of a plurality of discrete points, and the position information of the plurality of discrete points is calculated based on at least one of sensing information obtained by a satellite positioning system disposed in the UAV or sensing information obtained by a vision positioning sensor disposed in the UAV.