876results about "Remote controlled aircraft" patented technology

A docking system is disclosed for an unmanned aerial vehicle (UAV). The docking system includes a base station that is configured to receive the UAV and a pedestal that is configured to support the base station in an elevated position. The pedestal defines an interior space that is configured in correspondence with an outer contour of the base station such that the base station is positionable within the pedestal to protect the base station during nonuse.

A drone system and method for deploying and autonomously refuelling. The drone system includes a base station and a drone. The base station and drone are configured for autonomous refuelling when the drone has landed in the base station. The base station also provides portability and security of the drone.

Described herein are systems for automated docking of an unmanned aerial vehicle. For example, some systems include a landing surface configured to hold an unmanned aerial vehicle; a box configured to enclose the landing surface in a first arrangement of the dock and expose the landing surface in a second arrangement of the dock; and a retractable arm, wherein the landing surface is positioned at an end of the retractable arm and the retractable arm is configured to extend to move the landing surface outside of the box and contract to pull the landing surface inside of the box.

A system for dynamic asset addition management is disclosed. The system includes a communication interface and processor(s). The processor(s) is / are configured to obtain data associated with task(s) being performed by a set of assets, wherein the set of assets comprises a plurality of drones and the plurality of drones is at least semi-autonomous; determine to modify the set of assets based at least in part on the data associated with the task(s), including: 1) determining one or more capabilities associated with remaining task(s); and 2) determining a modification to the set of assets based at least in part on (i) the one or more capabilities associated with the remaining task(s), and (ii) one or more drone capabilities respectively associated with the set of assets; and communicate, via the communication interface, an instruction to at least one drone, the instruction indicating the modification to the set of assets.

A UAV for transporting a payload comprising a vehicle body; a retractable rail exposed on an underside of the vehicle body; a retraction mechanism coupling the rail to the vehicle body for causing the rail to raise and lower relative to the vehicle body; and a barrier located on the vehicle body so as to confront the rail when the rail is in its raised position to block the removal from the rail of a payload slidably engaged with the rail. A mechanism for advancing a payload onto and along the rail and pushing it off.

Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

A drone station according to an embodiment of the present invention may comprise: a station main body (10) having, mounted thereon, a charging device (20) allowing a drone to land thereon so as to be charged with drone power; a cover (30) provided at the station main body (10) so as to open / close the charging device (20) while rotating around an axle (12); and a window panel (34) provided in the cover (30), and made of a nonconductor material to transmit a GPS signal therethrough.

An introduced autonomous aerial vehicle can include multiple cameras for capturing images of a surrounding physical environment that are utilized for motion planning by an autonomous navigation system. In some embodiments, the cameras can be integrated into one or more rotor assemblies that house powered rotors to free up space within the body of the aerial vehicle. In an example embodiment, an aerial vehicle includes multiple upward-facing cameras and multiple downward-facing cameras with overlapping fields of view to enable stereoscopic computer vision in a plurality of directions around the aerial vehicle. Similar camera arrangements can also be implemented in fixed-wing aerial vehicles.

Described herein are techniques for generating contextually rich plant images. A number of data captures of raw plant data are generated via a sensing unit configured to navigate a growing facility. Metadata is generated and assigned to the raw plant data including at least one of: plant location, timestamp, plant identification, plant strain, facility identification, facility location, facility type, health risk factors, plant conditions, and human observations. Images generated by the sensing unit are analyzed and pixel annotations are generated in the images based on their relation to one or more plant well-being features. Data tags are generated and assigned the data captures based on an analysis of the data captures. The data tags are text phrases linking a particular data capture to a specific threat to plant well-being.

A landing pad receives and stores packages delivered from an aerial vehicle or awaiting pickup from an aerial vehicle. The landing pad can be placed outside of a window and can contain a transmitter for sending out an identification signal via radio frequency to aid aerial vehicles in finding the landing pad. The landing pad contains a landing platform with a trapdoor that leads to a storage compartment. The trapdoor can be configured to only open when it receives a signal from an authorized aerial vehicle. The storage compartment can be accessed via a storage compartment door which can contain a locking mechanism. The storage compartment can be climate controlled. The landing pad can also have a transmitter that emits sounds to discourage animals from nesting on or near the landing pad. The landing pad can also include a solar power generator as a source of electrical energy.

A method includes receiving a two-dimensional (2D) image captured by a camera on a unmanned aerial vehicle (UAV) and representative of an environment of the UAV. The method further includes applying a trained machine learning model to the 2D image to produce a semantic image of the environment and a depth image of the environment, where the semantic image comprises one or more semantic labels. The method additionally includes retrieving reference depth data representative of the environment, wherein the reference depth data includes reference semantic labels. The method also includes aligning the depth image of the environment with the reference depth data representative of the environment to determine a location of the UAV in the environment, where the aligning associates the one or more semantic labels from the semantic image with the reference semantic labels from the reference depth data.

An environmental monitoring network has transportable, self-contained, environment sensing capsules, each capsule is water-proof, with first and second sections, the second section being hollow. Apertures in the capsule's housing enable fluid and gas entry wherein first sensor(s) disposed internal to the housing measure within the hollow, and second sensor(s) disposed external to the housing measure external to the housing. A controller and power system are connected to the first and second sensors and transmits measured data. An access entry way is on a side of the housing, enabling access to first sensors, controller system, power system, and the communication system. A central data server is configured to receive and analyze the measurement data sent from the capsules. There is a priority list of appropriate personnel for contact by the central data server in an event there is an emergency condition at a capsule location.

The invention discloses an unmanned aerial vehicle having multifunctional leg assembly and charging system, including unmanned aerial vehicle and charging station. The UAV includes obstacle avoidance sensors, flight control module, first signal processing module, electric undercarriage and power charge / storage module. The charging station includes power charge / supply module. The obstacle avoidance sensors sense obstacles near the UAV to generate obstacle sensing signals. The first signal processing module interprets and processes the obstacle sensing signals to determine whether there is an obstacle near the UAV, and when the judgment result is yes, an avoidance instruction is transmitted to the flight control module, so that the flight control module drives the UAV to avoid the obstacle. The electric undercarriage includes first leg frame, second leg frame and electric driving mechanism. The electric driving mechanism drives the first leg frame and the second leg frame to fold and unfold alternately. The power charge / storage module includes first positive electrode and first negative electrode. The charging station includes power charge / supply module. The power charge / supply module includes second positive electrode and second negative electrode. When the UAV parks on a platform of the charging station, and the first positive electrode and the first negative electrode are in contact with the second positive electrode and the second negative electrode, then the power charge / supply module charges electricity to the power charge / storage module.

In an example embodiment, a method carried out by an uncrewed aerial vehicle (UAV) may involve receiving a reference map of a cluster of charging pads from a server. The cluster may include a layout of charging pads and fiducial markers distributed across the layout, the reference map representing the layout and fiducial markers. The UAV may fly to the cluster and acquire an image of charging pads and observed fiducial markers near the charging pads. The image may capture an observed constellation of fiducial markers at apparent positions and orientations relative to the charging pads. A reference constellation of fiducial markers at reference positions and orientations relative to reference charging pads may be identified in the reference map. Identities of the reference charging pads and a match of the reference constellation to the observed constellation may be used to disambiguate a particular charging pad from among the charging pads.

An unmanned aerial vehicle (UAV) having wings stowed against a fuselage of the UAV in a first arrangement is disclosed. Methods and systems for deploying the wings into a second arrangement are disclosed. For example, after a launch of the UAV, the UAV monitors for at least one precondition. The at least one pre-condition being a pre-condition associated with deploying wings of the UAV into the second arrangement. Upon detecting the at least one precondition, the wings of the UAV are deployed into a second arrangement. Deploying the wings comprises activating, in response to detecting the at least one precondition associated with the UAV, a gearbox configured to transition the wings from the first arrangement to the second arrangement. Roll control may be maintained throughout launch and deployment.

A device and a method for introducing a drone to an area of interest are presented. The delivery system may include a housing, a drone, either a timer or a receiver, a lock mechanism, and a biasing mechanism. The housing further includes a pair of parts with or without subparts. At least one sensor is attached to the drone. The timer or the receiver is secured to the housing and communicable with the lock mechanism to control function thereof. The lock mechanism is adapted to releasably secure the parts or the subparts. The drone is enclosed within the housing in a CLOSED configuration when the lock mechanism is locked. The biasing mechanism separates the parts or the subparts to an OPEN configuration when the lock mechanism is unlocked. The drone is introducible to the area of interest in the CLOSED configuration and separable from the housing in the OPEN configuration.

Systems and apparatus are provided for a high-power microwave sensor using an unmanned aerial vehicle. The unmanned aerial vehicle may include a central body, at least one electric motor, and a barometric pressure feedthrough. The central body may include a first enclosure housing a plurality of low voltage components, a voltage feedthrough connector, and a second enclosure housing a plurality of high voltage components. The low voltage components may include a first signal processing system, a first radio transceiver, a flight controller, a second signal processing system, a second radio transceiver, and a navigation system. The high voltage components may include a plurality of electronic speed controllers, a power distribution module, an input power interface, and a plurality of high power filters. The components of each enclosure may be segregated such that the high voltage components do not create electromagnetic interference with the low voltage components.

According to one embodiment, a method, computer system, and computer program product for performing a close-range inspection on a façade is provided. The present invention may include conducting a close-range inspection of inspection sites using a camera-equipped drone, wherein the close-range inspection comprises a close visual inspection and a tactile assessment; determining, by the visual AI engine, a visual building quality of the façade at the inspection sites based on images from the close visual assessment of the inspection sites; determining, by the acoustic AI engine, an acoustic building quality of the façade at the inspection sites based on impact sounds from the tactile assessment of the inspection sites; generating a digital representation of the façade based on the visual building quality and the acoustic building quality.

A system, a method, and / or a computer program for mounting a cable device on an electric cable of an electric grid, and dismounting therefrom, the mounting device including a first coupling part arranged to attach the mounting device to a flying vehicle, a second coupling part arranged to attach the cable device to the mounting device, and a navigation part operative to enable a user to navigate the flying vehicle so as to direct a slot of the cable device to the electric cable, and / or automatically navigate the flying vehicle to direct the slot of the cable device to the electric cable, and / or enable a user to navigate the flying vehicle to the cable device, and / or automatically navigate the flying vehicle to the cable device.

Systems, computer readable medium and methods for fully autonomous drone flight are disclosed. Example methods include taking off, navigating in accordance with a flight plan, and navigating the autonomous drone to land. The autonomous drone performs flight plans with only an initial command for the autonomous drone to fly and, in some examples, an indication of a landing space such as an open hand presented under the autonomous drone. After an initial fly command, the autonomous drone is not controlled by a remote-control device and does not receive any additional commands to complete the flight plan. The autonomous drone enters a lower energy state while flying where the wireless connections are turned off since the autonomous drone does not respond to commands during flight.

A computer stores dense maps generated by one or more aerial vehicles. The computer generates a global graph based on the dense maps and a sparse map. The computer stores a representation of one or more paths traversed by the one or more aerial vehicles within the global graph. The computer determines a path from an origin location to a destination location based on the global graph. The determined path enables an aerial vehicle to avoid objects.

An automated system provides end-to-end (E2E) orchestration for machine learning (ML)-enabled and software-defined network (SDN)-enabled reactive and predictive (e.g., 5G) cell-on-drone (COD) dispatch and deployment. The system may be configured to detect or predict traffic surges (e.g., relative to typical or baseline levels) in a given cell site and orchestrate provisioning of resources, including COD deployment, to address the surge. COD deployment may involve one or more clusters or colonies of drones equipped with low-powered cellular radio access (or small cell) nodes, where each cluster includes (or is led by) one or more SDN-equipped drones that provide intelligent SDN-on-drone (SOD) functionality.

A system includes a processor that is configured to detect occurrence of a disaster, activate a plurality of unmanned aerial vehicles and collect image and video data of a disaster-affected area, analyze the collected image and video data and generate a damage assessment as a three-dimensional map, visualize the generated three-dimensional map and distribute countermeasure instructions, receive information from residents of shelters and rescue workers, and extract important information by natural language analysis, and determine rescue activity instructions and support goods transport routes based on the extracted information.

A system for controlling unmanned vehicles such as drones, ground vehicles and robots includes multiple human-to-machine interface components to manage interactions efficiently and effectively between humans and robots with respect to control mechanisms (i.e., inputs such as voice-commands or joystick use) and monitoring (i.e., outputs such as camera or other sensor feeds, geolocation overlay, or audio feedbacks). A system according to the principles of the invention includes numerous modalities for control (e.g., voice-control, gesture-control, touch screen, joystick or other hand-held controllers) as well as monitoring (visual screen display, heads-up-display, audio feedbacks, geolocation overlay, haptic feedback, wearable sensor devices). The system is preferably expandable and may include additional modalities in the future, such as eye-tracking as compared to voice or gesture control.

The present disclosure is directed to a camera configured to capture a set of oblique images along a scan path on an object area; a scanning mirror structure including at least one surface for receiving light from the object area, the at least one surface having at least one first mirror portion at least one second portion comprised of low reflective material arranged around a periphery of the first mirror portion, the low reflective material being less reflective than the first mirror portion; and a drive coupled to the scanning mirror structure and configured to rotate the scanning mirror structure about a rotation axis based on a scan angle. The at least one second portion can be configured to block light that would pass around the first mirror portion and be received by the camera at scan angles beyond the set of scan angles.

The present disclosure relates to an autonomous, electric, vertical takeoff and landing (VTOL) aircraft that is low-noise, safe, and efficient to operate for cargo transportation over relatively long ranges. A VTOL aircraft includes a fuselage, a plurality of arms, a tail, and a plurality of propulsion systems mounted on the arms and the tail. The plurality of arms have parts that are rotatable and the tail has a part that is rotatable for transitioning the VTOL aircraft between a forward-flight configuration and a hover configuration.

Systems, methods, and apparatus for identifying, tracking, and disrupting UAVs are described herein. A tracking system can include one or more first computing devices that receive sensor data associated with an object in a particular airspace from one or more sensors. The first computing device can analyze the sensor data relating to the object to determine information about the object. A portable countermeasure device can include one or more second computing devices. The second computing device can receive the information relating to the object. The second computing device can display a visual indicator indicating the information on a display.

A device and a method for introducing a drone to an area of interest are presented. The delivery system may include a housing, a drone, either a timer or a receiver, a lock mechanism, and a biasing mechanism. The housing further includes a pair of parts with or without subparts. At least one sensor is attached to the drone. The timer or the receiver is secured to the housing and communicable with the lock mechanism to control function thereof. The lock mechanism is adapted to releasably secure the parts or the subparts. The drone is enclosed within the housing in a CLOSED configuration when the lock mechanism is locked. The biasing mechanism separates the parts or the subparts to an OPEN configuration when the lock mechanism is unlocked. The drone is introducible to the area of interest in the CLOSED configuration and separable from the housing in the OPEN configuration.

Systems, devices, and methods for a ground support system for an unmanned aerial vehicle (UAV) including: at least one handling fixture, where each handling fixture is configured to support at least one wing panel of the UAV; and at least one dolly, where each dolly is configured to receive at least one landing pod of the UAV, and where each landing pod supports at least one wing panel of the UAV; where the at least one handling fixture and the at least one dolly are configured to move and rotate two or more wing panels to align the two or more wing panels with each other for assembly of the UAV; and where the at least one dolly further allows for transportation of the UAV over uneven terrain.

A system includes a processor that controls an operable flying device, controls an operable imaging means, performs real-time analysis of generated data using artificial intelligence processing means, calculates an optimal rescue route based on the analysis results, controls means for loading and transporting supplies with the flying device, controls means for deploying equipment in regions where communication is disrupted and collecting local condition data, analyzes the collected data to generate emergency response information, and communicates the emergency response information to external rescue organizations.