There is provided a marking positioning device for an elevator which is capable of easily performing marking at a designated position inside a hoistway. The marking positioning device for an elevator includes a body portion that flies inside the hoistway of an elevator, a detecting unit provided at the body portion and configured to detect a position of the body portion inside the hoistway, a measuring unit provided at the body portion and configured to measure a three-dimensional shape inside the hoistway, a marking unit provided at the body portion and configured to perform marking, and a control unit provided at the body portion and configured to control flight of the body portion on the basis of the position detected by the detecting unit so that a position of marking by the marking unit is located at a designated position set in the three-dimensional shape measured by the measuring unit.

A method comprises performing, by a first coherent radar system on a chip configured to operate in a terahertz range between 0.1 THz and 1 THZ, a first radar scan of a target, the first coherent radar system being in physical contact with a first non-physical scanning device. The first non-physical scanning device then receives first scanning data from the first radar scan, and sends a coordination signal to a second non-physical scanning device. A second coherent radar system on a chip configured to operate in the terahertz range performs a second radar scan of the target, the second coherent radar system being in physical contact with the second non-physical scanning device. The second non-physical device receives second scanning data from the second radar scan, and the first and second scanning data are sent to a processor for a determination as to whether an impermissible object has been detected.

A method for generating data sets of a UAV, performed by a data set generation apparatus, may comprise obtaining flight environment information including a moving object; obtaining flight data including first physical information and first sensor information of the UAV in a flight environment based on the flight environment information; obtaining second physical information and second sensor information of the UAV when the moving object exists, based on the flight data, and generating a first data set based on the second physical information and the second sensor information; obtaining third physical information and third sensor information of the UAV when the moving object does not exist, based on the flight data, and generating a second data set based on the third physical information and the third sensor information; and combining the first data set and the second data set to generate a third data set.

A post-disaster conditions monitoring system is disclosed. The system may include plurality of aircraft drones configured to take photographic images; a conditions monitoring center having a controller including a device processor and a non-transitory computer readable medium including instructions executable by the device processor to perform the following steps: receiving images from the plurality of aircraft drones in a geographic region; determining conditions in the geographic region based on the images received from the plurality of aircraft drones; and sending information regarding the determined conditions to one or more users of the system.

Autonomous unmanned aerial vehicle management service may provide a platform to manage groups of unmanned aerial vehicles to work together on a task simultaneously in an autonomous manner.

Data regarding possible flight paths for a drone in relation to a start location and a destination is analyzed using a computer. Air space accessibility over a plurality of properties is determined, as part of a criteria, and the air space accessibility includes property owner permission and authorization for drone flight paths over the properties, respectively. Legal regulations regarding the possible drone flight paths over locations including the plurality of properties is determined as part of the criteria. An approved flight path is generated which includes permissions for the flight path granted by the property owners for flying through respective air space over the respective properties, and meeting legal regulations for flying over the locations including the respective properties on the possible flight paths. The approved flight path is sent to the drone or a drone control system for initiating a flight of the drone along the approved flight path.

In an example embodiment, a drone-based system comprises: a base station, wherein the base station is configured to provide drone control and power, a drone; a tether connecting the base station to the drone and configured to provide the drone with the power from the base station; and a lighting system, operably attached to the drone via the tether, configured to generate illumination of a ground area, wherein the illumination of the ground area is controllable by modifying least one of an intensity of the illumination and a height of the drone above the ground area.

A method enabling an authorized control system operator to remotely override a primary means of communication therewith, the control system including a primary controller integrated with, and configured to control an operation of a vehicle/vessel, a machine, etc. A remote controller communicates with the primary controller via a first mode of communication. An auxiliary controller module, integrated with the control system, communicates with the base controller via a different, second mode of communication, such that the auxiliary controller module functions as an emergency backup to take over control of the control system, in place of the primary controller, when, for example, the primary controller is rendered non-responsive to authorized operator-attempted communication from the remote controller to the primary controller, wherein the second mode of communication relies upon a coded messaging scheme.

Described are systems and methods relating to the causal detection and diagnosing of faults and anomalous operation of autonomous vehicles, such as unmanned aerial vehicles (UAVs), using machine learning. Embodiments of the present disclosure can provide systems and methods for detecting and diagnosing faults based on comparisons between the measured operation and/or behavior of a vehicle to the vehicle's expected nominal operation and/or behavior. Accordingly, the systems and methods according to embodiments of the present disclosure do not require prior knowledge of faults or modeling of the vehicle, the vehicle's operation, and/or environmental uncertainties. Further, embodiments of the present disclosure can facilitate sequencing of a vehicle's faults and/or anomalous operation and/or behavior, identify dependencies between a vehicle's faults and/or anomalous operation and/or behavior, and can detect and diagnose faults and/or anomalous operation and/or behavior in a contextual manner.

A method is provided for supporting an aircraft to execute a mission in which the aircraft maneuvers in an airspace system. The method includes detecting a lost-link event in which a datalink between the aircraft and a control station is interrupted or lost, and responsive to which the aircraft is preconfigured to execute a procedure. The method also includes conveying an intent of the aircraft to execute the procedure over a radio channel assigned for voice communication in the airspace system. In this regard, conveying the intent includes composing a message that indicates the intent of the aircraft to execute the procedure. The message is applied to a text-to-speech engine to convert the message to a corresponding verbal message in which the intent of the aircraft is conveyed. The corresponding verbal message is then sent over the radio channel assigned for voice communication in the airspace system.