152results about How to "Improve flight efficiency" patented technology

The invention provides an unmanned aerial vehicle multi-target tracking method and system based on visual and millimeter-wave radar information fusion, and the method comprises the steps: obtaining an association result through employing a space-time consistency model, constructing a self-adaptive joint probability data association frame according to the association result, so as to obtain an initial target state estimation value, and carrying out the recognition of the initial target state estimation value. A prospective path planning algorithm is adopted to obtain an optimal observation angle flight path, a Bayesian network is utilized to obtain initial observation data, based on the initial observation data, an optimal target state estimation value is generated, a distributed cooperative sensing mechanism is used to generate an initial tracking task allocation scheme, and an intelligent resource allocation strategy is implemented. Generating an initial resource allocation scheme, starting a quick response protocol to obtain an optimal tracking task allocation scheme, and generating an optimal resource allocation scheme based on the optimal tracking task allocation scheme; according to the technical scheme provided by the invention, the accuracy of target identification is improved, the environmental adaptability is enhanced, the tracking efficiency is improved, and the working time is prolonged.

The invention relates to the technical field of expressway unmanned aerial vehicle route planning, in particular to an intelligent route planning method and system for an expressway unmanned aerial vehicle, and the method specifically comprises the steps: planning unmanned aerial vehicle waypoints on an expressway based on a target three-dimensional model, and obtaining a waypoint set of the expressway; historical route data of the expressway are obtained, a deep learning algorithm is used for analyzing the historical route data, safe flight path features are extracted, a route safety evaluation model is constructed, and the route safety evaluation model is used for evaluating the route safety level of the route of the unmanned aerial vehicle; and determining route planning parameters according to the unmanned aerial vehicle task type, and determining an unmanned aerial vehicle route through the waypoint set, the route safety evaluation model and the waypoint planning parameters based on a multi-objective optimization algorithm. According to the invention, the safety and efficiency of the unmanned aerial vehicle in highway inspection and monitoring tasks are improved, and automatic planning and dynamic adjustment of the route of the unmanned aerial vehicle based on real-time data analysis are realized.

The invention discloses an efficient flight control system of a low-altitude manned unmanned aerial vehicle based on tilting composite wings, and relates to the technical field of unmanned aerial vehicle control systems. The low-altitude manned unmanned aerial vehicle efficient flight control system based on the tilting composite wings comprises an initialization and pre-check module, a vertical take-off and landing control module, a transition flight control module, an obstacle avoidance and path planning module and a landing control module. Through integration of vertical take-off and landing, smooth transition to cruise, intelligent obstacle avoidance, path planning and other modules, autonomous and efficient flight in a complex environment is realized, and the application scene of the unmanned aerial vehicle is greatly widened. Meanwhile, the accurate flight control and data post-processing analysis capability not only guarantees the safety and comfort of passengers, but also promotes the continuous optimization of the system performance through the real-time performance evaluation and feedback mechanism. In addition, the aerial refueling / charging technology is supported, the cruising ability is prolonged, and the task execution continuity and flexibility are enhanced.

The invention relates to the technical field of space positioning and path planning, in particular to a three-dimensional space positioning and path planning method for an unmanned aerial vehicle tower. The method comprises the following steps of performing accurate longitude and latitude height data acquisition based on a laser range finder to generate accurate longitude and latitude height data; obtaining tower equipment parameters; performing inspection point three-dimensional coordinate calculation according to the tower equipment parameters and the tower three-dimensional coordinate system to generate inspection point three-dimensional coordinate data; cruise point comprehensive constraint range data are obtained according to the unmanned aerial vehicle flight association data and the polling area terrain data, and cruise point comprehensive constraint range data are generated; performing cruise node three-dimensional coordinate design on the three-dimensional coordinate data of the inspection point according to the cruise point comprehensive constraint range data to generate cruise point three-dimensional coordinate data; and performing optimized cruise path planning processing according to the cruise point three-dimensional coordinate data to generate optimized cruise path data. According to the invention, more accurate unmanned aerial vehicle tower space positioning and path planning are realized.

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 embodiment of the invention provides an unmanned aerial vehicle dynamic deployment method and equipment, and the method comprises the steps: introducing a flight plan, a flight path line and a space-time envelope of flight, predicting the flight path of an unmanned aerial vehicle at a specific time, mastering the full view of the flight process in the whole flight plan, and carrying out the management and control of the capacity of the flight path as a resource, thereby achieving the dynamic deployment of the unmanned aerial vehicle. According to the method, the flight plan is deployed based on the capacity control result, conflict detection is carried out on space-time conflicts possibly existing in the flight process in combination with the flight control area and the flight plans of other unmanned aerial vehicles, and the flight plan is further adjusted in combination with the conflict detection result, so that accurate deployment of the flight of the unmanned aerial vehicles is realized. And the flight efficiency and the airspace utilization rate of the unmanned aerial vehicle are effectively 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 an unmanned aerial vehicle safety scheduling optimization algorithm, and relates to the technical field of storage scheduling, and the algorithm comprises the steps: carrying out the modeling of a storage environment based on the position, shape and size information of goods shelves and mechanical equipment in a warehouse, and building a preliminary environment model; and scanning the environment by using a laser radar carried by the unmanned aerial vehicle to obtain environment data in the warehouse, and updating the environment model in real time in combination with the preliminary environment model. According to the unmanned aerial vehicle safety scheduling optimization algorithm, the accuracy and efficiency of a flight path are remarkably improved through an integrated path planning technology, the optimal flight path is customized for the unmanned aerial vehicle in combination with actual conditions of topography and landform of a storage area and obstacle distribution, redundancy and waste in the flight process are reduced, and meanwhile, the unmanned aerial vehicle safety scheduling optimization algorithm has good application prospects. And the path can be dynamically adjusted according to the real-time environment change to effectively deal with emergencies, so that the flight efficiency and safety are further improved.

The invention discloses an unmanned aerial vehicle visual guidance obstacle avoidance system and method based on polarization information, and relates to the technical field of unmanned aerial vehicle navigation and obstacle avoidance. Polarization image information in a flight scene is collected in real time through a polarization sensor, and the perception capability of a complex environment is enhanced. Polarization parameters are extracted through a compression observation method, the efficiency and accuracy of feature extraction are improved, a visual attention mechanism is combined, an obstacle background area is accurately recognized, a self-adaptive decision fusion model is constructed, the feature weight is optimized, and the reliability of target contour features is enhanced. Preliminary path search is carried out based on target contour features, and a centralized optimization sampling method is adopted, so that the probability of generating an optimal flight path in a complex environment is effectively improved. And the obstacle avoidance flight module is used for smoothing the flight path, so that the smoothness and controllability of the flight path are ensured, and the navigation and obstacle avoidance capabilities of the unmanned aerial vehicle in a complex environment are effectively improved.

The invention relates to a vector propulsion spherical airship with an adjustable structure. The spherical airship is mainly composed of a vector propelling device, an airship capsule, an airship framework, a flight control module, a posture detection module, an environment monitoring module, a battery and the like. By adjusting the thrust direction of the vector propulsion device and the included angle between the airship framework and the capsule body, accurate control over the attitude and the flight path of the airship is effectively achieved. The design has the advantages of being small in size and compact in structure, and the propelling device is installed on the framework with the adjustable included angle, so that the control process is more flexible. Meanwhile, the propelling device achieves dynamic position adjustment through a framework structure and is prevented from being located in the airship movement direction, and potential safety hazards of a traditional external propeller are overcome. Although only two propelling devices are configured, the system can still provide fine control capability through seven controllable degrees of freedom, and the precision and flexibility of flight control are remarkably enhanced.

The invention discloses an unmanned aerial vehicle flight path planning method capable of completely avoiding a no-fly zone, which belongs to the field of unmanned aerial vehicle flight path planning and comprises an application scene of the unmanned aerial vehicle flight path planning method in the no-fly zone, and the application scene of the unmanned aerial vehicle flight path planning method in the no-fly zone comprises a communication scene of an unmanned aerial vehicle and a terminal user in the no-fly zone. According to the invention, the unmanned aerial vehicle can be absolutely prevented from entering any no-fly zone in the flight process; a plurality of straight lines are adopted to approximate the actual flight path of the unmanned aerial vehicle, and the distance from the intersection point of two adjacent straight lines to the center point of the no-fly zone is calculated, so that the flight path of the unmanned aerial vehicle is strictly monitored and planned, and the accuracy of flight path planning and the flight efficiency and task execution effect of the unmanned aerial vehicle are improved; according to the method, the constraint of the adjacent time slots on the continuous trajectory is increased, and the safety and robustness of the system are further improved through approximation of multiple straight lines and accurate intersection calculation.

The invention relates to a low-altitude unmanned aerial vehicle flight path planning method and system, and relates to the field of unmanned aerial vehicle navigation and control, and the method comprises the steps: carrying out the primary planning of a flight path according to the information of a plurality of obstacles, and obtaining a primary planning path domain; according to the obstacle information and the bird feature information, bird flight path density analysis between obstacles is carried out, and bird flight path density distribution is obtained; and performing secondary path planning optimization in the primary planning path domain according to bird flight path density distribution to obtain an optimal planning path. According to the invention, the technical problem that the existing method cannot effectively solve the problems of obstacle avoidance and bird interference in the flight process of the low-altitude unmanned aerial vehicle, resulting in insufficient flight safety and poor flight efficiency of the unmanned aerial vehicle can be solved; the flight path with the shortest distance can be selected on the premise of effectively avoiding obstacles and high-bird-density areas, so that the safety and the flight efficiency of the unmanned aerial vehicle during low-altitude flight are remarkably improved.

The invention relates to the technical field of pilot state monitoring, in particular to a pilot state monitoring and flight data real-time synchronous fusion system, which comprises an information acquisition module used for acquiring physiological state information of a pilot and flight data information of an airplane in real time; the intelligent control module is used for controlling the operation of the camera, the electroencephalogram acquisition device and the electrocardiograph; the information processing module is used for carrying out preprocessing operation on the collected pilot physiological state information and the collected aircraft flight data; and the data fusion module is used for fusing the physiological state information of the pilot and the flight data parameters of the aircraft. The early warning assistance module is used for immediately sending out an early warning signal when an abnormality is found; and positioning information and rescue guidance are provided for a pilot under the emergency condition that the aircraft encounters danger. According to the current attention state and the task requirement of the pilot, the system can dynamically adjust the collection frequency and the collection position of the electroencephalogram collection device so as to improve the efficiency and the pertinence of data collection.

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 provides an unmanned aerial vehicle control system and method based on information collaboration, and the system comprises the steps: carrying out the processing of multi-source sensing data of an unmanned aerial vehicle based on real-time data fusion and an intelligent decision algorithm, and carrying out the flight path planning through employing a collaboration control strategy, and obtaining the flight path of the unmanned aerial vehicle; key control points are determined in the flight path of the unmanned aerial vehicle, a cooperative control framework is constructed according to the key control points, the unmanned aerial vehicle is cooperatively controlled in the target direction, and cooperative control data are acquired; setting control parameters according to the cooperative control data, and limiting the decision range of the intelligent decision algorithm; and under the criteria of meeting task requirements and minimizing energy consumption, based on an optimization algorithm and an energy management strategy, searching an optimal flight path and an energy distribution scheme, and carrying out collaborative optimization on the flight state of the unmanned aerial vehicle. According to the invention, the autonomy and energy efficiency of the unmanned aerial vehicle in a complex environment can be improved, and meanwhile, the flight safety and the task flexibility are ensured.

The invention discloses an unmanned aerial vehicle self-adaptive inspection method based on multi-layer characterization learning, which comprises two stages of automatic coarse inspection and self-adaptive fine inspection, and learns the space structure, component characteristics and disease characteristics of a bridge layer by layer. In the automatic rough detection stage, in combination with a spatial clustering post-processing method and a point cloud semantic segmentation network, instance attributes of bridge components are quickly learned. Then, the point cloud space is compressed and converted by using a simulation view field model and a dimension reduction technology, and the unmanned aerial vehicle is guided to carry out efficient and comprehensive space patrol in plane geometry. In the adaptive fine detection stage, a space-channel two-dimensional optimized hybrid convolution structure Light-PVIT is utilized to learn and extract disease features in the automatic coarse detection stage as prior information. The information guides the unmanned aerial vehicle to carry out fine detection on a disease area in a small field of view. According to the unmanned aerial vehicle self-adaptive inspection method, the bridge inspection efficiency and precision are remarkably improved, and reliable technical support is provided for bridge maintenance work.

The invention provides a highway unmanned aerial vehicle autonomous inspection method and system, and relates to the technical field of data processing, and the method comprises the steps: receiving a preset inspection path from an inspection starting point to an inspection terminal point; unmanned aerial vehicle sensor information and unmanned aerial vehicle angular velocity information in the inspection process are collected; when an obstacle is detected by the unmanned aerial vehicle sensor information, obstacle avoidance is carried out, and otherwise, whether yawing is carried out or not is detected; generating an obstacle avoidance direction based on a potential field principle, and performing obstacle avoidance according to the obstacle avoidance direction; calculating a yaw angle of the unmanned aerial vehicle according to the angular velocity information of the unmanned aerial vehicle, and judging whether to yaw based on the yaw angle of the unmanned aerial vehicle; correcting the course of the unmanned aerial vehicle according to the yaw angle, and performing inspection along the adjusted course of the unmanned aerial vehicle; collecting real-time video frames of the expressway; constructing a highway abnormal scene recognition model, and outputting an abnormal scene; and uploading the abnormal scene to the holder, and sending out an abnormal prompt. The autonomous inspection efficiency and inspection precision are improved, and the manual intervention frequency and deployment cost are 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 present invention discloses a beacon system and a navigation method for unmanned aerial vehicle navigation, and the present invention relates to the field of unmanned aerial vehicle navigation technology. The method comprises the following steps: collecting performance parameters generated by the beacon node closest to the unmanned aerial vehicle based on the initial position; in the target area where the unmanned aerial vehicle flies, calculating the beacon node setting interval according to the performance parameters, and arranging a plurality of beacon nodes on the ground in an equidistant manner; monitoring the signal strength received by the beacon node according to the performance parameters and signal loss, comparing the received signal strength with the signal strength threshold, and when the received signal strength is less than the signal strength threshold, recording the current beacon node position, detecting the obstacle position, and adjusting the beacon node to the target position according to the obstacle position; collecting the unmanned aerial vehicle position information through the beacon node at the target position, selecting the path according to the current unmanned aerial vehicle position information through the particle swarm optimization algorithm, and the unmanned aerial vehicle reaches the destination according to the selected optimal path.

The invention provides an unmanned aerial vehicle flight integrated management method and system, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: obtaining task information of a target unmanned aerial vehicle, and determining a first route according to the task information; optimizing the first route to obtain an optimized route; and monitoring the flight condition of the target unmanned aerial vehicle flying according to the optimized route in real time, and responding to a corresponding strategy to perform exception handling when an exception is detected. The method comprises the following steps: optimizing a first route determined according to task information of a target unmanned aerial vehicle to obtain an optimized route; and the flight condition of the target unmanned aerial vehicle flying according to the optimized route is monitored in real time, and when abnormity is detected, the corresponding strategy is responded to carry out abnormity processing, so that the flight safety and the flight efficiency of the unmanned aerial vehicle can be effectively enhanced, and the task execution efficiency is further improved.

The invention discloses a flight-oriented fan wing trailing edge adjusting device, and relates to the technical field of aircrafts, the flight-oriented fan wing trailing edge adjusting device comprises a trailing edge angle adjusting mechanism, a rectification angle adjusting mechanism, a circular end plate and a rectification plate, the trailing edge angle adjusting mechanism comprises a steering engine, a first connecting rod mechanism, a trailing edge plate and a rotating shaft; the steering engine is fixedly installed on the circular end plate and controls the rear edge plate to move through the first connecting rod mechanism, the rotating shaft is arranged on one side of the rear edge plate, and the rear edge plate is hinged to the rectifying plate through the rotating shaft. By freely adjusting the trailing edge angle and the rectification angle, the aerodynamic force of the fan-wing aircraft is changed, the lift force and thrust distribution is improved, the aerodynamic effect is enhanced, the energy consumption is reduced, and the flight efficiency is improved. The fan wing trailing edge adjusting device is applied to a serial fan wing, forward coupling gain between two wings is achieved by changing the size of a trailing edge angle and a rectification angle, different flight conditions are met, various flight requirements are flexibly met, and the load performance and the endurance are optimized.

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 belongs to the technical field of unmanned aerial vehicles, and discloses a reconfigurable antenna array based on a combinable and separable unmanned aerial vehicle group, the antenna array is carried on the unmanned aerial vehicle group, and the unmanned aerial vehicle group comprises a plurality of carrying antenna transmitting systems, antenna receiving systems and a plurality of unmanned aerial vehicle units which do not contain antenna sub-arrays but carry other functions. Through three arrangement modes of the antenna array, multi-functionalization of the airborne antenna array of the unmanned aerial vehicle is realized, such as high-resolution two-dimensional imaging, high-resolution three-dimensional imaging, accurate positioning of a specified target, tracking of the specified target, monitoring of a specified airspace and the like. The first unmanned aerial vehicle group is linearly arranged in a single layer, and an antenna array forms a synthetic aperture radar antenna in the movement of the unmanned aerial vehicle group, so that a high-resolution two-dimensional imaging function can be realized; the second type of unmanned aerial vehicle group is arranged in a single-layer two-dimensional array, and the specified target can be accurately positioned when the unmanned aerial vehicle group hovers.

The propaganda display device belongs to the technical field of propaganda display, not only can passively display propaganda materials, but also can display learning conditions through the status bar arranged on the edge of the propaganda column, so that the learning conditions displayed in the status bar can be obtained, learning objects can select learning time and content, and the learning efficiency is improved. The display rack can send a learning site to the display rack, after receiving learning related information, the display rack can send a propaganda unmanned aerial vehicle to convey related learning materials and a projector with propaganda content in place for learning, and after learning is completed, the display rack can report the learning situation back to the display rack; and then the corresponding learning condition is updated through the status bar, so that the functions of supervising and conveying learning materials are added.

The invention discloses a full-scene adaptive flight method, device and equipment and a storage medium, and relates to the technical field of unmanned aerial vehicles. The technical scheme provided by the invention comprises the following steps: determining a real-time control strategy according to first scene information, wherein the real-time control strategy comprises a speed priority control strategy and a terrain priority control strategy; acquiring topographic information collected by the perception sensor in real time, and planning a flight path according to the topographic information and the real-time control strategy; when the unmanned aerial vehicle flies based on the flight path, second scene information is determined according to the terrain information, and a real-time control strategy is adjusted according to the second scene information; and re-planning a flight path according to the adjusted real-time control strategy and terrain information. Through the technical means, autonomous flight of the unmanned aerial vehicle in any terrain scene is achieved, the problem that in the prior art, a user needs to judge terrain features and control the unmanned aerial vehicle to switch the terrain simulation mode is solved, the operation difficulty of the user is simplified, and potential safety hazards caused by misoperation are avoided.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle route real-time planning method and system, a storage medium and an unmanned aerial vehicle. Determining a target distance between a target unmanned aerial vehicle and a target object in the target area; and according to the target distance, determining a current operation parameter of the target unmanned aerial vehicle, and according to the current operation parameter, adjusting a route of the target unmanned aerial vehicle. According to the invention, the terrain features of the regional three-dimensional point cloud data can be combined to realize real-time planning of the route of the unmanned aerial vehicle, and the flight safety and the flight efficiency are improved.

The invention discloses a traffic infrastructure inspection unmanned aerial vehicle and a system thereof, and relates to the technical field of inspection unmanned aerial vehicles, the traffic infrastructure inspection unmanned aerial vehicle comprises a driving integrated machine body, a regulation and control assembly is installed in the driving integrated machine body, and the side end of the regulation and control assembly is fixedly connected with a side wing regulation and control assembly; according to the unmanned aerial vehicle, under the cooperation of the side wing regulation and control assembly and the regulation and control assembly, the light high-strength auxiliary wing structure capable of reducing wind resistance is adopted, so that the unmanned aerial vehicle is effectively kept in a more stable flight attitude, the image stability and the data accuracy during inspection are improved, the flight performance of the unmanned aerial vehicle is adjusted according to actual requirements in the flight process, and the unmanned aerial vehicle is more stable in flight. When long-distance inspection is carried out in an open zone, the regulation and control assembly can drive the side wing regulation and control assembly to retract, so that the overall flight resistance is reduced, energy is saved, the flight efficiency is improved, the situation that the unmanned aerial vehicle is limited due to the fact that the state of the unmanned aerial vehicle is affected by the construction operation environment is reduced, and the detection effect of the unmanned aerial vehicle is guaranteed.

The invention discloses a tilting folding wing and a vertical take-off and landing aircraft. Comprising a central wing (2), outer wings (3) capable of being folded / unfolded in a tilting mode are symmetrically connected to the two ends of the central wing (2), and tilting rotating shafts (501) of the outer wings (3) are located at the outer ends of the central wing (2) and located at the positions, close to the rear portions, of the front edges of the outer wings (3); the two outer wings are driven by the same folding driving mechanism (4) to be folded / unfolded in a tilting mode, and the connecting line of points on the outer wings (3) before and after tilting is perpendicular to the rotating shaft (501). The device has the advantages of being simple in structure, good in synchronism and high in safety.