299 results about "Flight planning" patented technology

Systems and methods are provided for promoting stable aircraft approach conditions. The system comprises a display device that is onboard an aircraft and a controller in communication with the display device. The controller is configured to, by a processor: receive data that includes information relating to an action configured to stabilize an approach of the aircraft during landing thereof and a recommended timing of performing the action relative to a predetermined flight plan of the aircraft, and render a first visual element on the display device that is configured to display the action relative to the flight plan and dynamically indicate the recommended timing of performing the action relative to a geographic position of the aircraft along the flight plan.

The invention provides an aircraft digital twinning situation deduction and risk assessment method in a complex meteorological environment, and belongs to the technical field of data processing, the aircraft digital twinning situation deduction and risk assessment method in the complex meteorological environment comprises the following steps: collecting and processing weather data covering parameters such as wind direction and wind speed; obtaining aircraft performance parameters and building a database; and inputting and analyzing the flight plan. By establishing a three-dimensional deduction model including dynamics, weather influence and environment models, aircraft situations under different weathers are deduced, and flight safety, performance and task risks are evaluated. The method has the advantages that weather factors are comprehensively and accurately analyzed, and influences are quantified through data acquisition and processing and a meteorological model; the system is suitable for various aircrafts, can integrate navigation and control systems, and realizes remote monitoring management; risk assessment is scientific and reliable, multiple factors are integrated, powerful support is provided for flight decision making, and aircraft safety and task success rate in complex weather are effectively improved.

A method for determining improved flight trajectory. The method includes receiving one or more weather parameters to determine contrail forecast data; receiving one or more flight parameters associated with at least one aircraft 204 to determine flight data thereof; receiving flight schedule including at least one flight plan of at least one aircraft; analyzing at least one flight plan to determine at least one navigational avoidance between at least two aircraft; determining contrail likelihood associated with at least one aircraft; altering one or more flight parameters to determine improved flight trajectory for at least one flight plan; sending at least one flight plan including improved flight trajectory to at least one aircraft; and validating improved flight trajectory using imagery data, when at least one aircraft flies according to at least one flight plan including improved flight trajectory. A system for determining improved flight trajectory.

A method for controlling a plurality of drones to survey a location, the method comprising, at a computing system: automatically generating preliminary flight plans for a plurality of drones to survey the location based on a 3D model; receiving survey data from the plurality of drones as the plurality of drones are surveying the location based on the preliminary flight plans; updating the 3D model based on the survey data received from the plurality of drones; and automatically updating at least a portion of the flight plans based on the updated 3D model

The invention provides an airspace simulation deduction method and system based on digital twinning, and belongs to the technical field of airspace simulation, and the method comprises the steps: integrating geographic bottom plate data and airspace element data, carrying out the meshing based on an airspace grid engine, and constructing an airspace digital twinning model; receiving at least one flight plan, and mapping the flight plan to the airspace digital twin model to generate a corresponding simulation aircraft entity; based on a preset simulation engine, driving the simulation aircraft entity to perform flight simulation in the airspace digital twin model, and calculating a simulation flight situation; in the simulation process, airspace conflict detection and early warning are carried out based on the simulation flight situation and the airspace digital twin model; and outputting a simulation deduction result, performing three-dimensional visual output on the simulation flight situation data and the early warning information, and generating an analysis report including conflict statistics and airspace evaluation. The airspace resource allocation is optimized, the flight safety is improved, and intelligent and efficient management is realized.

Techniques for flight path optimization include obtaining map information defining mapping coordinates of a geographical region, obtaining historical UAV-obtained flight information related to a first autonomous flight of a UAV in the geographical region based on a first flight plan, storing the map information, the historical UAV obtained-flight information, the first flight plan, and current values of a set of external factors separate from the flight information, and generating a second flight plan for a second autonomous flight of the UAV. The generating may include processing the map information, the historical UAV-obtained flight information, and the current values of the set of external factors, and updating the first flight plan based on the processing to generate the second flight plan. The second flight plan may be transmitted to the UAV for a second autonomous flight of the UAV in the geographical region.

A system for filtering and presenting notifications received by an aircraft includes a processor, a display device, a communication device, and computer-readable memory. The computer-readable memory encoded with instructions that, when executed by the processor, cause the system to perform the following steps. The system receives one or more broadcast notifications. The notifications are, for example, Notices to Air Missions (NOTAMs). The system filters the one or more broadcasted notifications based upon applicability to a present flight plan to generate applicable notifications. The system filters the applicable notifications based upon one or more filtering criteria to assign a criticality to each of the applicable notifications. The system display, via the display device, the applicable notifications based upon the criticality of each of the applicable notifications. The system outputs alternate flight plans due to restrictions on the present flight plan.

The invention discloses a fan blade transportation and installation system and method and a flight device, and belongs to the technical field of intelligent transportation of fan blades. The system comprises a flight transportation module, an intelligent navigation control module, an installation auxiliary module and a scheduling module; the flight transportation module is used for suspending and loading the fan blades, and suspending, flying and transporting the fan blades according to a preset flight route; the intelligent navigation control module is used for monitoring a flight path, collecting flight data and environment data in a flight process, predicting potential obstacles according to the flight data and the environment data, and optimizing a flight strategy; the mounting auxiliary module is used for aligning and fastening the blades and the fan hub; the scheduling module is used for determining a flight plan according to the meteorological data, the performance of the flight transportation module and the priority of the transportation installation task. By combining a plurality of transportation, installation and dispatching modules, efficient and safe transportation and installation of the fan blades are achieved, and the transportation and installation difficulty and cost are reduced.

The invention discloses a signal source tracking-oriented Gaussian process space-time modeling and unmanned aerial vehicle flight planning method, which comprises the following steps of: firstly, acquiring RSSI (Received Signal Strength Indicator) data of a signal source by a sensor carried by an unmanned aerial vehicle, and recording corresponding position information and timestamps to form a space-time data set; based on the data set, space-time modeling of signal intensity is carried out by using a Gaussian process, the future position of a signal source is predicted, and the challenge of the position change of the signal source in a dynamic environment is overcome. And then, in combination with a designed flight planning algorithm, calculating a target position of the unmanned aerial vehicle at the next moment according to a signal intensity distribution prediction result. The flight planning method is divided into an exploration stage and a tracking stage, and the path of the unmanned aerial vehicle is dynamically optimized by adopting an overall variance reduction (IVR) evaluation function and a likelihood weighting (LW) evaluation function respectively. According to the invention, through spatial-temporal distribution modeling of signal intensity and flight path optimization, accurate tracking of the unmanned aerial vehicle on the mobile signal source is realized, and hardware dependence and realization cost are effectively reduced.

A method and an unmanned aerial vehicle for identifying and remediating a gas leak. The method includes flying the unmanned aerial vehicle towards a possible location of the gas leak, then detecting a first condition indicative of the gas leak with a first sensor and sensing environmental conditions near the gas leak with an environmental sensor. The method includes receiving, by a controller, a signal representing the first condition indicative of the gas leak and a signal representing the environmental conditions. The method includes determining, based on the first condition indicative of the gas leak and the environmental conditions near the gas leak, a flight plan including an ignition zone. The method includes positioning, based on the flight plan, the unmanned aerial vehicle relative to the ignition zone and discharging, by an ignition mechanism, an ignition source into the gas leak to ignite the gas leak.

A flight planning system and method include one or more control units configured to determine, from ensemble data, a plurality of flight plans for an aircraft from a departure location to an arrival location. The ensemble data includes an aggregation of data from multiple data sources. In at least one example, the one or more control units are further configured to determine a preferred flight plan from the plurality of flight plans.

The invention discloses an aircraft simulation data generation and situation deduction method based on a flight plan, and the method comprises the steps: firstly constructing an analysis model which is used for receiving a flight plan generated by a front end and carrying out the preprocessing, and then carrying out the aircraft situation deduction based on the information of each flight segment. The method comprises the following steps: generating an independent aircraft class, attaching different state attributes to the aircraft class, establishing an aircraft climbing and descending model, and continuously updating the state attributes of the aircraft class according to real-time deduction data. And finally, designing cyclic output of the aircraft simulation situation data once every 4 seconds. The method aims at providing assistance for work of a controller and improving situation awareness and real-time state monitoring of the aircraft in the operation stage. Meanwhile, an aircraft driver is assisted to make a decision autonomously, and control over the aircraft by the driver and information interaction between the driver and a controller are enhanced; and enough reaction time can be reserved for a driver and a controller at the emergency moment.

The invention discloses a report generation method and device, equipment and a storage medium, and relates to the technical field of air traffic management, and the method comprises the steps: obtaining the current navigation data and meteorological data of a target aircraft, and constructing corresponding target data based on the navigation data and meteorological data; the navigation data comprises radar data and flight plan data of a target aircraft; determining the flight conflict probability of the target aircraft according to the target data through a preset conflict probability prediction model; the preset conflict probability prediction model is constructed based on a long and short term memory network; determining a conflict risk level of the target aircraft based on the flight conflict probability of the target aircraft and preset historical conflict data; and generating a conflict report of the target aircraft based on the flight conflict probability and the conflict risk level. Through deep fusion of the large language model and air traffic control field knowledge, a more comprehensive conflict analysis basis can be provided, automatic report generation is realized, and the accuracy of conflict detection is significantly improved.

The invention provides a generator and battery power distribution method and device based on model prediction control, and belongs to the technical field of power distribution. The method provided by the invention comprises the following steps: loading a preset dynamic model library; generating and calibrating a total load power prediction sequence based on the flight plan and the rotor aerodynamic power model; calling the dynamic model library to predict and control the rolling optimization to output the optimal power instruction sequence of the generator; in the rolling optimization execution process, bus voltage dynamic characteristics are monitored in real time, a graded response mechanism is started based on a turboshaft engine dynamic model when load sudden change occurs, and the power of a generator and the power of a battery are adjusted; in the load abrupt change response process, rolling optimization is executed again based on the adjusted power and the corresponding system state, meanwhile, feed-forward compensation is carried out on the bus voltage deviation, and the voltage is controlled to be within a stable interval set by rolling optimization by adjusting the power of the generator; and circularly executing until the flight task is finished, and determining the generator power and the battery power.

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 system and a method include a monitoring control unit configured to compare an initial flight plan, as generated by a flight planner for an aircraft, and an assessed flight plan, as determined by air traffic control. The monitoring control unit is further configured to determine one or more alternate initial flight plans that differ from the initial flight plan in response to determining one or more differences between the initial flight plan and the assessed flight plan.

The invention discloses an unmanned aerial vehicle route planning method and device, equipment, a product and a storage medium. Comprising the following steps: determining a first grid bitmap of at least one unmanned aerial vehicle route planning area; the first grid bitmap comprises identification information of grids; the identification information represents whether the grid is released after a preset time when the grid is occupied; acquiring planning request information of the first unmanned aerial vehicle under the condition that the first unmanned aerial vehicle needs to adjust the route; determining a second grid bitmap corresponding to the at least one unmanned aerial vehicle route planning area according to the identification information and the planning request information; based on the first grid bitmap and the second grid bitmap, whether the first unmanned aerial vehicle passes the course adjustment is judged, and a judgment result is obtained; whether the first unmanned aerial vehicle travels according to the adjusted route is determined according to the judgment result, the efficiency and flexibility of intelligent flight planning and grid distribution are achieved, and meanwhile the probability that the same grid is seized by multiple aircrafts is reduced, and the situation that the unmanned aerial vehicles lose communication exists and the route conflicts among the unmanned aerial vehicles are reduced.

The invention provides a self-organizing flight planning method based on behavior parameter dynamic adjustment, and belongs to the technical field of unmanned aerial vehicle flight planning. Each unmanned aerial vehicle obtains and updates own state and environmental threat information through a sensor, and establishes a cluster member level interaction model to interact neighbor motion states; comprehensively considering the interaction between members in the cluster and the interaction between the members and the external environment, respectively calculating an internal interaction effect and an external interaction effect, and further obtaining an overall interaction effect; on the basis of an asynchronous optimization criterion triggered by an event, online optimization adjustment is carried out on a behavior parameter set of the unmanned aerial vehicle in combination with an optimization guard interval, a flight state is predicted through a motion model, an optimal parameter is determined by means of a local performance evaluation function, a final control input driving state is generated and updated, and autonomous flight planning is realized. According to the method, the online cooperative flight requirement of the unmanned aerial vehicle cluster in a dynamic unknown environment is met.

The present disclosure provides techniques for dynamic utilization of aircraft based on environmental conditions. A proposed flight plan for an aircraft is received. Environment data representing a set of environmental conditions at a source airport indicated in the proposed flight plan is collected. Weather data representing a set of environmental conditions at a destination airport indicated in the proposed flight plan is collected. Operation data related to the aircraft indicated in the proposed flight plan is received. Aircraft engine degradation of the aircraft is dynamically simulated based on the collected environment data and the received operation data using a trained machine learning (ML) model. The simulated aircraft engine degradation is output.

An aircraft includes a flight plan and contingency data including a plurality of contingency landing sites. An aircraft communication system communicates with a ground control station via a communication link and detects a lost communication scenario in response to degradation in the communication link. An aircraft flight control system controls the aircraft en route according to the flight plan. In response to detecting the lost communication scenario, the flight control system routes the aircraft back to a last known location in which the communication link was not degraded. In response to failure to re-establish the communication link, the flight control system selects a landing site based on a current aircraft location relative to a plurality of potential landing sites including an origin airport, a destination airport, and a first continency landing site. The flight control system controls the aircraft to approach and land at the selected landing site.

The embodiment of the invention provides an aircraft path planning method, an aircraft and a storage medium. The aircraft path planning method comprises the steps that path planning reference information of an aircraft is acquired, and the path planning reference information comprises a path planning starting point position and a path planning ending point position; a path planning data set associated with the path planning reference information is determined, and the path planning data set comprises topographic data, obstacle data, environment data and aircraft attribute data associated with the path planning reference information; a target navigation path of the aircraft is generated according to the path planning data set, the target navigation path is used for describing a flight plan adopted when the aircraft passes through multiple target waypoints, and the multiple target waypoints are determined based on the path planning starting point position and the path planning ending point position. According to the invention, the technical problem of poor flight safety of the hovercar caused by low precision of path planning in the prior art is solved.

A method for communication between an air traffic control system and a communication module, the communication method includes a step of determining environmental optimization time slots based on the air traffic absorption capacities of the various flight information regions, the environmental optimization time slots at least partially covering one or more flight information regions, each environmental optimization time slot having an associated efficiency level; a step of negotiation, between the pilot via the communication module and the air traffic control system, to negotiate changes to the flight plan on the basis of the environmental optimization time slots and the environmental optimization levels of the environmental optimization time slots.

The invention provides an airport taxiing intelligent control method based on a graph neural network and multi-agent reinforcement learning. The method comprises the following steps: receiving taxiing state information and a taxiway space structure of each airplane i on an airport scene; converting the obtained state information and taxiway space structures of all aircrafts into a graph form, and substituting the graph form into a graph attention network and a deep neural network; the neural network selects taxiing actions for the corresponding aircrafts according to the obtained taxiway traffic data, the state information of all the aircrafts is trained, and the neural network of each aircraft i on the scene is updated and shared; the learning process is repeated, and all aircrafts can slide to specified destinations on the premise of avoiding sliding conflicts. The optimal and conflict-free taxiing control can be automatically executed under the condition that the airport flight plan and the taxiway traffic condition are given, and the aspects of reducing the taxiing time, reducing the oil consumption, improving the adaptability to different taxiway conditions and the like are obviously optimized.

A system and a method include a flight plan generating control unit configured to receive a flight plan request for an aircraft from a user interface, determine if the flight plan request matches a flight plan within a flight plan database, in response to the flight plan request matching the flight plan within the flight plan database, submit the flight plan to a validation sub-system, and in response to the flight plan request not matching the flight plan within the flight plan database, determine a new flight plan.

An aircraft includes a flight plan and contingency data including a plurality of contingency landing sites. An aircraft communication system communicates with a ground control station via a communication link and detects a lost communication scenario in response to degradation in the communication link. An aircraft flight control system controls the aircraft en route according to the flight plan. In response to detecting the lost communication scenario, the flight control system routes the aircraft back to a last known location in which the communication link was not degraded. In response to failure to re-establish the communication link, the flight control system selects a landing site based on a current aircraft location relative to a plurality of potential landing sites including an origin airport, a destination airport, and a first continency landing site. The flight control system controls the aircraft to approach and land at the selected landing site.

The invention discloses a flight route detection method and device, electronic equipment and a storage medium. The method comprises the following steps: determining identity information of a target aircraft according to an image acquired by image acquisition equipment deployed in a flight space; according to an association relationship between the identity information and a flight area, obtaining a target flight area corresponding to the target aircraft, the target flight area being an area determined according to flight plan information reported by the target aircraft and gridding information of a flight space; determining an actual flight path of the target aircraft according to electromagnetic information detected by a base station deployed in the flight space; the actual flight path of the target aircraft is detected based on the target flight area, a detection result is obtained, and the detection result is used for representing whether the flight route of the target aircraft deviates or not. According to the scheme provided by the embodiment of the invention, the accuracy of route deviation detection can be improved, and a basis is provided for the flight safety of an aircraft.

Example systems, computer readable medium and methods for automatically generating portrait videos from landscape videos include receiving a landscaped video, identifying one or more objects to track, and tracking the one or more objects by moving a cropping window. A user interface is presented that provides options for a user to automatically convert a landscape video into a portrait video. The options include selecting one or more objects in the landscape video to track and tracking based on a flight plan used to capture the video. The automatic tracking uses a hierarchy of a person for tracking where a face is used if the person is close, an upper body is used if the person is farther away, and a whole body is used if the person is even farther away. A hierarchy of a person includes indications of which parts of the hierarchy to exclude first.

The invention provides a single microwave radiation driven unmanned aerial vehicle flight planning method with optimal energy utilization, and the method comprises the following steps: 1, obtaining unmanned aerial vehicle basic design parameters, state initial parameters, and an unmanned aerial vehicle lift-drag ratio relational expression for a given unmanned aerial vehicle; calculating a climbing angle boundary and a flight speed boundary of the unmanned aerial vehicle by adopting an aircraft performance estimation method; 2, establishing a mathematical relationship between the position, the roll angle, the pitch angle and the yaw angle of the unmanned aerial vehicle and the energy consumption of the unmanned aerial vehicle at the current time step; 3, calculating the position, the yaw angle and the flight speed of the unmanned aerial vehicle in the next time step from the initial state based on the basic design parameters and the initial state parameters of the unmanned aerial vehicle; based on the mathematical relation established in the second step and the minimum energy consumption of the current time step, the roll angle and the pitch angle of the unmanned aerial vehicle in the next time step are obtained, and the position, the attitude angle, the flight speed and the energy consumption of the unmanned aerial vehicle in each time step are recorded until the flight task is completed finally.

A system and method include a monitoring control unit configured to compare an initial flight plan, as generated by a flight planner for an aircraft, and an assessed flight plan, as determined by air traffic control. The monitoring control unit is configured to determine one or more differences between the initial flight plan and the assessed flight plan. The monitoring control unit is configured to output a notification signal to the flight planner regarding the one or more differences between the initial flight plan and the assessed flight plan.

The invention discloses an aircraft inspection control method, electronic equipment and an aircraft, and the aircraft inspection control method comprises the steps: determining a current inspection list corresponding to a current flight stage and / or a target inspection item in the current inspection list according to an inspection determination factor, the check determination factor comprises at least one of flight plan data and aircraft state data; preferentially displaying the current check list and / or the target check item in the current check list. Therefore, according to the technical scheme of the invention, the inspection list or the target inspection item which needs to be processed at present can be quickly determined according to the inspection determination factors (such as flight plan data and aircraft state data) so as to be preferentially displayed, so that an operator can perform interaction conveniently. Therefore, according to the technical scheme of the invention, display optimization can be carried out on the checklist, so that convenient interaction is realized.