27results about How to "Reduce flight time" patented technology

The invention discloses an unmanned aerial vehicle path planning method and system based on digital twinning. The method comprises the following steps: constructing a three-dimensional environment model based on first target environment data in first target multi-source environment perception data; constructing a digital twin based on the geometric model, the physical model, the control model, the target physical data hybrid dynamic model and the three-dimensional environment model; inputting the second target multi-source environment sensing data into the digital twin, and dynamically simulating the flight behavior of the physical unmanned aerial vehicle based on the second target multi-source environment sensing data to obtain simulated flight environment state data; and based on the simulated flight environment state data, performing path planning on the physical unmanned aerial vehicle in combination with a prediction control algorithm and a path planning algorithm to obtain a target flight path, transmitting the target flight path to the physical unmanned aerial vehicle, and controlling the flight of the physical unmanned aerial vehicle. The method can dynamically simulate the real-time change of the physical unmanned aerial vehicle, plan the optimal flight path and effectively avoid obstacles, and can be widely applied to the technical field of unmanned aerial vehicle path control.

The invention discloses an unmanned aerial vehicle flight control method and system based on a target image, and relates to the field of unmanned aerial vehicle flight control, and the method comprises the steps: obtaining the relative position of an unmanned aerial vehicle in a flight region based on the target image and a position calculation algorithm, and judging the yaw state of the unmanned aerial vehicle through a position comparison method; analyzing the target image by using an identification processing technology based on yaw state judgment to determine a flight yaw angle of the unmanned aerial vehicle, and generating a yaw control quantity according to the flight yaw angle to control the flight state of the unmanned aerial vehicle; collecting a real-time target image of the unmanned aerial vehicle after the flight state is adjusted, analyzing the flight height of the unmanned aerial vehicle according to the real-time target image, and planning a landing track of the unmanned aerial vehicle based on the flight height; and generating an autonomous landing control instruction according to the unmanned aerial vehicle landing trajectory and a preset flight demand to complete autonomous landing flight control of the unmanned aerial vehicle. By collecting the target image in real time and analyzing the flight height, the landing track of the unmanned aerial vehicle can be accurately planned.

The invention discloses an unmanned aerial vehicle full-coverage path planning method, system and device and a storage medium, and relates to the field of unmanned aerial vehicles. The method comprises the following steps: acquiring preset map information of a first target area, and determining a second target area for delivering materials according to the preset map information; determining a relay unmanned aerial vehicle set according to the data information, a preset starting point, a second target area, preset map information, a first communication distance of the first unmanned aerial vehicle and a second communication distance of the relay unmanned aerial vehicle, and determining a second initial path of the second unmanned aerial vehicle according to the first initial path; controlling the first unmanned aerial vehicle and the second unmanned aerial vehicle to fly according to a preset initial path, and adjusting the preset initial path according to the environmental data collected by the first unmanned aerial vehicle; and when the first unmanned aerial vehicle arrives at a preset terminal point, determining flight paths of other unmanned aerial vehicles according to the actual load weights and types of the other unmanned aerial vehicles in the transportation unmanned aerial vehicle group and the environment data. By implementing the technical scheme provided by the invention, the task execution efficiency of the unmanned aerial vehicle group is improved.

The invention relates to the field of weather modification, and discloses a catalyst scheduling control method applied to aircraft weather modification, comprising: acquiring target weather modification information, the target weather modification information comprising weather modification demand information and a target modification area; inputting the real-time cloud layer information of each job sub-region into a pre-trained deep learning model to obtain a cloud layer category corresponding to each job sub-region; screening the plurality of operation sub-regions according to the weather operation demand information and the cloud layer category corresponding to each operation sub-region to obtain a catalyst standard putting region group; adjusting the preset reference putting amount corresponding to each catalyst standard putting area to obtain the catalyst putting amount of each catalyst standard putting area; and according to the catalyst diffusion speed, determining a catalyst feeding speed corresponding to the catalyst standard feeding area. Therefore, the accuracy and the high efficiency of artificial influence weather operation are realized.

The invention provides a dynamic target tracking method and system based on image return, and relates to the technical field of image data processing, and the dynamic target tracking method based on image return comprises the following steps: collecting image data of a target scene, recognizing a to-be-tracked target and position information of the to-be-tracked target by using a double-layer random forest recognition algorithm, and predicting a motion track of the to-be-tracked target; according to the predicted motion track of the to-be-tracked target and the position information of the unmanned aerial vehicle, and based on a target function of the distance between the unmanned aerial vehicle and the to-be-tracked target, using a cooperative control strategy to adjust flight parameters of the unmanned aerial vehicle; and the unmanned aerial vehicle continuously tracks the to-be-tracked target, and after tracking is finished, the cloud server stores the position information and the movement track of the to-be-tracked target in the tracking process. The system has the advantages of real-time performance, high efficiency, intelligence, data storage and subsequent analysis, expansibility and flexibility, safety improvement, risk reduction and the like.

The invention discloses a 110KV power transmission line unmanned aerial vehicle cluster inspection control method and system, and relates to the technical field of power systems and automatic control, and the method comprises the steps: generating an inspection region three-dimensional map through first data, and carrying out the distributed task distribution through a first algorithm; performing path search based on three-dimensional expansion of a second algorithm; and a third control algorithm is adopted to realize unmanned aerial vehicle cluster coordinated flight, and a dynamic window method is combined to realize real-time obstacle avoidance. According to the method, the flight path of the unmanned aerial vehicle can be more accurately planned through three-dimensional expansion of an existing path planning algorithm in combination with topographic data, and unnecessary flight time and energy consumption are reduced; through cluster collaborative operation, multiple sections of power transmission lines can be inspected at the same time, the inspection time is greatly shortened, the operation efficiency is improved, all corners of the data lines are fully covered, and the blind area or missing detection problem is avoided.

The invention relates to the technical field of unmanned aerial vehicle electronic data processing, and provides an unmanned aerial vehicle flight risk assessment and quality monitoring method, which comprises the following steps of: acquiring diversified data acquired in a flight process of an unmanned aerial vehicle, establishing a data optimization group, performing optimization correction, extracting features and constructing a risk assessment model; real-time flight monitoring data is classified and corrected and then substituted into the model, and a comprehensive flight risk assessment result is obtained. The problems of sensor data errors and noise are solved, the evaluation accuracy is improved, decision support is provided for safe flight of the unmanned aerial vehicle, the flight safety and efficiency of the unmanned aerial vehicle are remarkably enhanced, and the flight risk evaluation and quality monitoring accuracy of the unmanned aerial vehicle is improved.

The invention discloses an electric power unmanned aerial vehicle investigation 3D imaging system and a measurement method, and relates to the field of unmanned aerial vehicle electric power investigation. An unmanned aerial vehicle carrying a visible light and thermal imaging camera is adopted to move in the air so as to investigate and collect visible light image data and thermal imaging image data of an electric power network; identifying network nodes and connecting lines through a deep learning algorithm, and constructing a two-dimensional topological graph; weight distribution is carried out on nodes in combination with temperature data in thermal imaging image data, an inspection path is planned by using an improved genetic algorithm, and the total inspection path is reduced while high-risk nodes are inspected preferentially; in the inspection process according to the inspection path, node three-dimensional coordinates and visible light and thermal imaging images are obtained through an unmanned aerial vehicle sensor, a power network three-dimensional topological graph is constructed, and fault nodes are marked. The method has the advantages that the three-dimensional topological graph is quickly generated, fault nodes are preferentially detected, and the total routing inspection distance is remarkably reduced.

The invention relates to the technical field of unmanned aerial vehicles, and discloses a method for regulating and controlling an unmanned aerial vehicle through positioning coordinates, which comprises the steps of evaluating the load capacity of the unmanned aerial vehicle and matching logistics tasks; planning an initial path according to the initial site and the target position of the unmanned aerial vehicle, and performing optimization by combining historical path data to obtain an optimal path; when approaching the target, judging the landing standard; if not, selecting a new landing point; and if yes, judging whether to accurately adjust the residual route, and adjusting according to the real-time information. According to the method, the safety and the stability of the unmanned aerial vehicle in the flight process can be guaranteed, the most suitable unmanned aerial vehicle can be automatically selected for distribution according to specific logistics task requirements, and the efficiency and the accuracy of logistics transportation are greatly improved.

The invention discloses an unmanned aerial vehicle autonomous flight control method based on a PID-LQR. The method comprises the following steps: acquiring environment data and unmanned aerial vehicle performance parameter data; communication between the unmanned aerial vehicle and a computing platform is established, and the computing platform plans a global flight path of the unmanned aerial vehicle according to the environment data and the unmanned aerial vehicle performance parameter data; performing path smoothing on the planned path by adopting a non-uniform B-spline; sampling the smoothed path to obtain discrete path points; converting the coordinates of the discrete path points from a body coordinate system to a world coordinate system; and inputting the path points converted into the world coordinate system and the state parameters of the unmanned aerial vehicle into a calculation platform, and outputting an unmanned aerial vehicle control instruction in combination with a PID-LQR algorithm to realize autonomous flight of the unmanned aerial vehicle. According to the method, the flight safety and efficiency of the unmanned aerial vehicle can be enhanced, the robustness of the system is improved through control of the PID-LQR algorithm, the method adapts to external interference and uncertainty, the method adapts to different flight tasks and environments through parameter adjustment, and the stability and response speed of the system are ensured.

The invention discloses an unmanned aerial vehicle route planning method based on capital construction data. The method comprises the following steps: step 1, data acquisition and arrangement; 2, performing three-dimensional modeling; step 3, preliminarily generating a route; 4, checking and optimizing the air route; and 5, simulating test flight. Through introduction of real-time dynamic data and application of an intelligent algorithm, the scheme effectively prevents the unmanned aerial vehicle from encountering obstacles and unsuitable areas in the flight process, significantly reduces the flight risk, can update the flight path plan in real time, ensures that the flight path of the unmanned aerial vehicle keeps adaptability under changing meteorological conditions and traffic flow, and improves the flight speed. The flight task is more flexible and efficient, and the flight time and energy consumption of the unmanned aerial vehicle can be reduced through an intelligent optimization algorithm and scheme, so that the task execution efficiency is improved, the operation cost is reduced, and higher economy and benefits are provided for the application of the unmanned aerial vehicle.

The invention discloses an unmanned aerial vehicle cooperative route planning system. The system belongs to the field of intelligent traffic and intelligent route planning and comprises a central control module, a sensing system, an algorithm module, an obstacle avoidance system, a positioning system, a power supply system, an analog simulation module, a communication and data module, a task planning module and a user interface. The central control module serves as the core of the system, is responsible for coordinating the sensing system, the algorithm module and the obstacle avoidance system, and realizes data fusion and provides an optimal route through data integration and screening. The sensing system is provided with temperature, humidity and wind speed sensors so as to monitor and adapt to external weather conditions in real time; the algorithm module adopts a DFS algorithm and a BFS algorithm, the two graph search algorithms can plan paths and explore problems, and support is provided for collaborative inspection of the unmanned aerial vehicle in a complex environment. Through the system, the DFS algorithm and the BFS algorithm can cooperate with a plurality of unmanned aerial vehicles.

The invention provides an unmanned aerial vehicle routing inspection method and system based on semantic guidance and an asset value cost graph, and the method comprises the steps: reasoning a possible distribution region of a target when the target is not directly observed through analyzing the structure law of semantic information, such as an equipment number, a function partition identifier and the like, in a transformer substation; generating a confidence map to guide the unmanned aerial vehicle to efficiently inspect; constructing a semantic cost graph fusing the static asset value and the dynamic operation risk, and quantifying potential loss of different regions when collision or falling occurs; according to the real-time health state of the unmanned aerial vehicle, semantic guidance is emphasized during normal inspection through a dual-guidance function fusion and switching mechanism, and the unmanned aerial vehicle is automatically switched to asset value cost minimization guidance in an abnormal or emergency state to realize safe disposal; the system adopts a framework of semantic reasoning, cost evaluation and flight control module decoupling, and guidance intelligence and control reliability are ensured. According to the invention, the inspection blindness of the unmanned aerial vehicle is obviously reduced, and the abnormality handling risk is reduced.

The invention discloses a basalt fiber unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles, the basalt fiber unmanned aerial vehicle comprises a basalt fiber unmanned aerial vehicle shell, a battery is arranged at the top of the basalt fiber unmanned aerial vehicle shell, supporting frames are uniformly arranged on the periphery of the basalt fiber unmanned aerial vehicle shell, and an adjusting assembly is arranged on one side of each supporting frame; a fan blade assembly is arranged on the side, away from the adjusting assembly, of the supporting frame. A mounting plate is arranged in the basalt fiber unmanned aerial vehicle shell, a controller is arranged on the inner top of the mounting plate, and a sensor is arranged on the top of the basalt fiber unmanned aerial vehicle shell. According to the invention, the environment sensing module and the flight path planning module are combined to extract the flight image of the unmanned aerial vehicle, the features of static and dynamic obstacles are accurately identified, and the scientific setting of the static path and the real-time tracking of the motion trail of the dynamic obstacle are realized.

The invention relates to the technical field of aircraft control, in particular to a simulation deformation aircraft and a control method. Comprising the following steps: S1, acquiring parameter data of an aircraft, dividing the moving form of the aircraft into a flight mode and a ground mode according to the parameter data, and then summarizing to establish an aircraft form database; s2, performing aerial measurement and investigation in the moving process of the aircraft, acquiring surrounding environment data of the aircraft, and then extracting a movable path by combining the surrounding environment data with the aircraft form database; s3, extracting a qualified moving form corresponding to the movable path; a navigation path is generated by combining a real-time position of an aircraft and a movable path selected by a user, and is continuously optimized in a simulation process, and an optimal moving path and form combination is selected by performing performance evaluation and comprehensive scoring on different moving forms, so that the most efficient flight is realized.

The invention discloses an intelligent fault studying and judging method for a distribution line of an unmanned aerial vehicle, and relates to the technical field of line detection, and the method comprises the steps: classifying each segment according to the environment and fault record of each segment in the distribution line, and determining a detection equipment set of each segment according to a classification result; meanwhile, according to the environment, the detection difficulty and the distance in each segment, the sequence of each segment is determined, then routing inspection is performed, after routing inspection is finished, whether data abnormity exists in each segment is analyzed by using routing inspection data, then associated data corresponding to the data abnormity is analyzed, then secondary routing inspection is performed, and targeted detection is performed on a line. The line inspection comprehensiveness and efficiency are improved, a more reliable basis is provided for fault analysis and diagnosis, the fault recognition accuracy is improved, and the unmanned aerial vehicle inspection effect is improved.

The present invention discloses a method and system for controlling a UAV flight based on a target image, and relates to the field of UAV flight control. The method comprises: obtaining the relative position of the UAV in the flight area based on the target image and the position calculation algorithm, and judging the yaw state of the UAV by the position comparison method; determining the flight yaw angle of the UAV by analyzing the target image using the recognition processing technology based on the yaw state judgment, and generating a yaw control amount according to the flight yaw angle to control the flight state of the UAV; collecting the real-time target image of the UAV after the flight state is adjusted, and analyzing the flight altitude of the UAV according to the real-time target image, and planning the landing trajectory of the UAV based on the flight altitude; generating an autonomous landing control instruction according to the landing trajectory of the UAV and the preset flight requirements to complete the autonomous landing flight control of the UAV. The present invention can accurately plan the landing trajectory of the UAV by collecting the target image in real time and analyzing the flight altitude.

A low-cost, high-frequency reusable, small-payload aerospace transportation system and method belongs to the technical field of overall design of aerospace transportation systems. The present invention solves the main problems existing in the existing reusable space-to-earth round-trip aircraft in terms of energy operation nature, aerodynamic thermal protection cost, and the way of passing through the atmosphere. The launch end of the ground electromagnetic boost launch system of the present invention is connected to a two-stage carrier, and the first-stage orbiter of the two-stage carrier is connected to the second-stage thruster. After the two-stage carrier is launched, the first-stage orbiter separates from the fairing connection cover and the second-stage thruster and enters the orbiter integrated platform. After the first-stage orbiter completes the orbital mission, it enters the orbiter integrated re-entry return platform. A low-cost, high-frequency reusable, small-payload aerospace transportation system and method of the present invention provides initial kinetic energy to achieve a higher take-off speed, which can effectively reduce the propellant and take-off mass, and reduce the wing area requirement.

The invention discloses a dynamic switching and adaptive compression system and method for multi-mode communication of a low-altitude Internet of Things, and belongs to the technical field of intelligent ad hoc networks of unmanned aerial vehicles. The airborne end comprises an NVIDIA Jetson Xavier NX embedded computing platform, an airborne Raspberry Pi CM4-5G expansion board, an airborne ad hoc network radio station, a flight control computer and an optical pod camera; the ground end comprises a ground Raspberry Pi CM4-5G expansion board and a ground ad hoc network radio station; according to the low-altitude intelligent networking multi-mode communication dynamic switching and adaptive compression system and method, the advantages that an ad hoc network radio station is farther in transmission distance, independent of ground infrastructure, flexible in deployment and the like are utilized, the ad hoc network radio station serves as a supplementary communication means of a 5G public network, and therefore real-time online of an unmanned aerial vehicle is guaranteed; information sharing and collaborative operation between the unmanned aerial vehicles can be effectively realized, and the overall efficiency and collaborative capability of the system are improved.

The invention discloses a low-cost and high-frequency reusable small-load aerospace transportation system and method, and belongs to the technical field of overall design of aerospace transportation systems. The main problems existing in the aspects of energy operation essence, aerodynamic thermal protection cost, atmosphere crossing modes and the like of an existing air and ground reciprocating reusable aircraft are solved. A transmitting end of the ground electromagnetic boosting transmitting system is connected with a two-stage carrier, a first-stage orbiter of the two-stage carrier is connected with a second-stage propeller, and after the two-stage carrier lifts off, the first-stage orbiter is separated from a rectification connecting cover and the second-stage propeller and then enters an orbiter integrated platform; the first-stage orbital device enters the orbital device integration and then enters the return platform after completing the orbital task. According to the low-cost, high-frequency and reusable small-load aerospace transportation system and method, initial kinetic energy is provided, the high take-off speed is achieved, the propellant and take-off mass can be effectively reduced, and the requirement for the wing area is reduced.

The invention provides an automatic track control simulation method and system for an army unmanned aerial vehicle simulation system. The automatic track control simulation method of the army unmanned aerial vehicle simulation system comprises the steps of obtaining longitude and latitude coordinates and a route deviation value according to a preset point selection logic in combination with the number of effective route points of an unmanned aerial vehicle; respectively and correspondingly acquiring a to-fly distance and a shortest distance of the unmanned aerial vehicle according to the longitude and latitude height coordinates and the route deviation value of the unmanned aerial vehicle; and acquiring the course of the unmanned aerial vehicle and a corrected expected course according to the longitude, latitude and height coordinates of the unmanned aerial vehicle, sending the corrected expected course to an autopilot, and controlling the unmanned aerial vehicle to fly along a track. The system comprises modules corresponding to the steps of the method.

The application relates to a UAV inspection path planning and optimization system and method, and relates to the technical field of visual detection. The system comprises a data acquisition module for acquiring trajectory data of a plurality of construction safety helmets and trajectory data of a plurality of inspection safety helmets; a site modeling module for collecting real-time modeling data of a construction site based on the trajectory data of the plurality of construction safety helmets, and constructing a real-time three-dimensional model of the construction site; a path constraint module for inputting a constraint condition set of a UAV inspection path; and a path optimization module for generating an optimal UAV inspection path based on the real-time three-dimensional model of the construction site, the constraint condition set of the UAV inspection path, the trajectory data of the plurality of construction safety helmets and the trajectory data of the plurality of inspection safety helmets. The application has the advantages of improving the comprehensiveness and safety of UAV inspection path planning.

The invention discloses a power inspection path determination method and device, an unmanned aerial vehicle and a storage medium. The method comprises the steps of performing three-dimensional modeling on a current flight area based on real-time flight data of an unmanned aerial vehicle, and determining a real-time distance between the unmanned aerial vehicle and an obstacle; determining a target distance threshold value through an interval range formed by a first threshold value and a second threshold value, and controlling the flight height of the unmanned aerial vehicle based on the real-time distance and the target distance threshold value; wherein the first threshold value is determined based on the displacement required by the unmanned aerial vehicle to decelerate to zero, and the second threshold value is determined based on the detection distance of a single-line laser radar carried by the unmanned aerial vehicle; and according to a result of the three-dimensional modeling, selecting a target flight sector from a plurality of flight sectors through which the unmanned aerial vehicle can pass, and determining the flight direction of the unmanned aerial vehicle based on the target flight sector. According to the scheme, the optimal flight path of the unmanned aerial vehicle during power inspection can be planned in real time, and the inspection flight precision and safety are improved.

The application relates to the field of unmanned aerial vehicle control, and discloses a cross-medium control method and system based on an unmanned aerial vehicle vision system and a storage medium. The method comprises the following steps: acquiring a first predicted time at which an unmanned aerial vehicle reaches a critical position between a first region and a second region and a current time at a current position in the first region; if a time difference is less than a first threshold, adjusting configuration parameters of the unmanned aerial vehicle; determining an optimal path of the unmanned aerial vehicle from the critical position to a target position in the second region, and setting a plurality of first positions on the optimal path; establishing a state control model, inputting a current image of the current position and a reference image of an adjacent first position, and outputting an estimated value of an unmanned aerial vehicle state adjustment amount; taking the adjacent first position as a new current position, repeating the step until the optimal path is traversed; when the unmanned aerial vehicle returns to the first region, obtaining a return critical time of reaching the critical position, and adjusting the configuration parameters, so that the stability of the unmanned aerial vehicle in different media is improved.

This invention discloses a bolt loosening detection method and system based on UAVs and multimodal analysis, belonging to the field of structural health monitoring technology. It includes acquiring structural data of towers to construct a three-dimensional virtual mapping and performing simulation to dynamically generate inspection tracks for the UAV; the UAV simultaneously collects high-definition video and sound field data of the bolts based on the tracks, forming a multimodal data stream; calculations are performed by fusing visual and acoustic features to output quantitative diagnostic results; an active verification process is initiated for abnormal or poorly quality results to obtain supplementary data for correction and form a final diagnosis; a detection report is generated based on the final diagnostic data, constructing a full lifecycle health record. This invention adopts a technical solution combining three-dimensional task planning, multimodal fusion diagnosis, active verification and correction, and full lifecycle management, which can improve detection accuracy and efficiency while achieving dynamic assessment and trend prediction of the health status of bolt components.

The invention relates to an unmanned aerial vehicle low-altitude public route network design method, system and device, computer equipment, a storage medium and a computer program product. Relates to the technical field of route planning. The method comprises the following steps: acquiring map information of a destination of an unmanned aerial vehicle, and collecting an image of the destination; generating low-altitude route information of the unmanned aerial vehicle based on the map information and the image of the destination; and under the condition that the low-altitude air route information does not conflict with the route in the historically generated low-altitude air route network, updating the historically generated low-altitude air route network through the low-altitude air route information to obtain a new low-altitude air route network. By adopting the method, the conflict of the running route can be effectively avoided.

The invention relates to the technical field of agricultural spraying equipment, in particular to a path planning and coverage optimization method for an agricultural fuel oil unmanned aerial vehicle spraying system, and aims to solve the problems of low path planning efficiency, insufficient coverage optimization capability, dynamic adjustment response lag and the like in the existing agricultural unmanned aerial vehicle spraying technology. According to the path planning and coverage optimization method for the agricultural fuel oil unmanned aerial vehicle spraying system, through organic combination of intelligent algorithms, high efficiency, accuracy and comprehensive coverage of spraying operation are achieved.