A response system may be provided. The response system may include an autonomous drone. The autonomous drone may include a processor, a memory in communication with the processor, and a sensor. The processor may be programmed to build a virtual map of a coverage area, store the virtual map in the memory, receive a deployment signal, deploy the drone in response to the deployment signal, control movement of the drone within the coverage area using the virtual map, collect sensor data of the coverage area using the sensor, and/or analyze the sensor data to generate an inventory list of the coverage area, the inventory list including a personal article within the coverage area.

An airborne coordinate measuring machine (CMM) includes a noncontact 3D scanner constructed to obtain measurement data of an object under scrutiny and a drone aircraft mechanically coupled to the 3D scanner and constructed to traverse a flight path that is specific to the object under scrutiny.

The present inventive concept provides for a method of unmanned machine synchronization using robotic sensing. The method includes generating at least one physical signal in the vicinity of at least one unmanned machine. The at least one generated physical signal is received by the at least one unmanned machine. At least one task is performed by the at least one unmanned machine based on the at least one received generated physical signal.

An aerial vehicle is configured to calculate ranges to objects around the aerial vehicle when operating within indoor spaces, using a LIDAR sensor or another range sensor. The aerial vehicle calculates ranges within a plurality of sectors around the aerial vehicle and identifies a minimum distance measurement for each of the sectors. Sets of adjacent sectors having distance measurements above a threshold are identified, and bearings and minimum distance measurements of the sets of adjacent sectors are determined. When the aerial vehicle detects an object within a flight path, the aerial vehicle selects one of the sets of adjacent sectors based on the minimum distance measurements and executes a braking maneuver in a direction of the selected one of the sets of adjacent sectors.

Systems, devices, and methods for determining, by a processor, an unmanned aerial system (UAS) position relative to at least one flight boundary; and effecting, by the processor, at least one flight limitation of a UAS if the determined UAS position crosses the at least one flight boundary.

A method for controlling secure delivery of a medication package includes receiving a medication delivery request to deliver a medication package to a first delivery location. The method also includes identifying one or more authenticated delivery locations corresponding to a recipient and determining whether the one or more authenticated delivery locations includes the first delivery location and, in response to a determination that the one or more authenticated delivery locations includes the first delivery location, instructing an unmanned aerial vehicle to transport the medication package from a starting location to the first delivery location. The method also includes, in response to the unmanned aerial vehicle communicating authentication data, determining whether the authentication data corresponds to the recipient. The method also includes, in response to a determination that the authentication data corresponds to the recipient, instructing the unmanned aerial vehicle to release the medication package to the recipient.

An aerial vehicle is provided. The aerial vehicle can include a plurality of sensors mounted thereon, an avionics system configured to operate at least a portion of the aerial vehicle, and a machine vision controller in operative communication with the avionics system and the plurality of sensors. The machine vision controller is configured to perform a method. The method includes obtaining sensor data from at least one sensor of the plurality of sensors, determining performance data from the avionic system or an additional sensor of the plurality of sensors, processing the sensor data based on the performance data to compensate for movement of the unmanned aerial vehicle, identifying at least one geographic indicator based on processing the sensor data, and determining a geographic location of the aerial vehicle based on the at least one geographic indicator.

A handheld module including a battery, an electro-mechanical interface, and a display. The electro-mechanical interface is configured to attach the handheld module to an image capture module, wherein when attached to the image capture module, the handheld module forms a communication link to the image capture module via the electro-mechanical interface and supplies power from the battery to the image capture module via conductors of the electro-mechanical interface. The display is configured to present images captured by the image capture module and received from the image capture module via the communication link.

Systems and methods for automated unmanned aerial vehicle recognition. A multiplicity of receivers captures RF data and transmits the RF data to at least one node device. The at least one node device comprises a signal processing engine, a detection engine, a classification engine, and a direction finding engine. The at least one node device is configured with an artificial intelligence algorithm. The detection engine and classification engine are trained to detect and classify signals from unmanned vehicles and their controllers based on processed data from the signal processing engine. The direction finding engine is operable to provide lines of bearing for detected unmanned vehicles.

A computerized system and method for managing a fleet of Unmanned Aerial Systems (UAS) collaboratively performing a mission. The system receives mission requirements comprising mission goals, area of operation, characteristics of each UAS and calculates data acquisition points in the area of operation according to mission goals, sensor types and constraints. It then calculates a flight plan for each UAS. Once flying in the field, the system verifies for each UAS at predetermined intervals during flight the UAS' aerial location at that time and compares the UAS aerial location to the expected aerial location according to flight plan in that time. If necessary, adjustments are made to the flight plan of one or more UAS. Other considerations for flight adjustments are battery power level, mission goal accomplishments, signal quality and more.