144 results about "No-fly zone" patented technology

The invention provides an unmanned aerial vehicle low-altitude intelligent traffic dynamic airspace management and control method and system, and relates to the technical field of intelligent control, and the method comprises the steps: taking an electronic fence geographic coordinate set as a monitoring reference boundary, fusing ADS-B data, meteorological information and an unmanned aerial vehicle equipment state, generating a real-time risk thermodynamic diagram, and outputting a grading alarm instruction; receiving a real-time risk thermodynamic diagram and a grading alarm instruction, and combining wind speed prediction and dynamic airspace occupation data; when the grading alarm instruction is triggered, executing the following operations: constructing a route feasible solution space by taking a no-fly zone and a high-risk zone in the risk thermodynamic diagram as constraint conditions; and iterating an evolutionary path population through selection, intersection and mutation operations of a genetic algorithm by taking the lowest energy consumption as an optimization target, so as to output a global final obstacle avoidance bypassing path, and issuing a route updating instruction to an unmanned aerial vehicle flight control system. According to the invention, the utilization of airspace resources is maximized on the premise of ensuring safety.

The invention provides an unmanned aerial vehicle intrusion real-time interception method and system based on an airspace electronic fence. The method comprises the steps of firstly obtaining real-time flight monitoring data of an unmanned aerial vehicle in a target airspace, then analyzing predefined airspace electronic fence configuration information to generate a virtual boundary constraint set, and then combining three-dimensional space coordinates and the virtual boundary constraint set to judge whether the unmanned aerial vehicle invades a no-fly zone or not. When it is judged that the unmanned aerial vehicle invades the no-fly zone, a collaborative interception instruction sequence is generated, finally, the collaborative interception instruction sequence is sent to the unmanned aerial vehicle through a radio frequency communication link, the unmanned aerial vehicle is driven to execute flight path correction, and real-time interception of the unmanned aerial vehicle is completed; according to the technical scheme, the real-time performance and safety of sensitive airspace protection are improved, meanwhile, the risk of mistakenly intercepting legal aircrafts is avoided, and non-lethal precise expelling is completed on the premise of completely eradicating the crash risk.

The invention relates to an unmanned aerial vehicle flight path planning method in a complex city low-altitude environment. The method comprises the following steps: S1, acquiring geographic information data of a target city area; s2, constructing a three-dimensional grid model of a target city region according to the geographic information data; s3, extracting obstacle boundary and no-fly zone information from the three-dimensional grid model, initializing the flight path of the unmanned aerial vehicle by adopting an A * algorithm, and obtaining a preliminary flight path planning result; s4, performing global optimization on the preliminary route planning result to obtain an optimized route planning result; and S5, if the optimized flight path planning result satisfies a preset condition, outputting the optimized flight path planning result, and if the optimized flight path planning result satisfies the preset condition, returning to S4 until the preset condition is satisfied. According to the invention, safe and efficient flight of the unmanned aerial vehicle in a complex dynamic urban low-altitude environment is realized.

The present application belongs to the technical field of co-delivery center site selection. Disclosed are an urban-end co-distribution center site selection method and system based on air-ground coordination, which are used for solving the technical problems of an existing air-ground coordination co-delivery center site selection model being insufficiently integrated with an unmanned aerial vehicle delivery technique, failing to take into consideration constraint conditions on unmanned aerial vehicles, and the solving efficiency being low. The method comprises: establishing a planned layout set of an air-ground coordination co-delivery center; taking the minimization of the overall delivery time and the minimization of the total network operation cost as objectives to construct an air-ground coordination layout planning model; setting constraint conditions of the air-ground coordination layout planning model; by means of a grey wolf population algorithm, generating an initial site selection solution set for a pre-selected point set of the co-delivery center; filtering out invalid solutions in the initial site selection solution set on the basis of the constraint conditions; and performing an individual iterative update on the filtered initial site selection solution set, and performing a fitness assessment and no-fly zone crossing determination on a new solution set obtained after each iteration, so as to obtain a final site selection scheme.

The invention relates to the technical field of unmanned aerial vehicle path planning, in particular to a multi-aerial vehicle cooperative path planning method, system and device in a city and a storage medium. Comprising an information acquisition module, a path generation module, a clustering updating module and an optimal judgment module. According to the method, the initial position, the target position and the obstacle information of each unmanned aerial vehicle are acquired, an urban low-altitude airspace task scene is defined, the MP-GWO algorithm is utilized to generate a multi-aerial-vehicle cooperative initial path, differential penalty coefficients are set for different types of no-fly zones, a K-means clustering mechanism is embedded into a GWO main cycle, and the multi-aerial-vehicle cooperative initial path is obtained. According to the method, parallel sub-populations are divided according to a multi-target fitness vector, each sub-population independently executes an alpha, beta and delta guide updating strategy, a triple termination judgment mechanism integrating fixed iteration times, a convergence threshold value and elite stagnation is adopted, a current optimal planning path is output, efficient optimization of the path in a complex urban environment is achieved, and the path optimization efficiency is improved. The method is suitable for urban low-altitude airspace multi-unmanned aerial vehicle cooperative tasks.

The invention provides a multi-unmanned aerial vehicle adaptive migration method for a sudden no-fly zone, and relates to the technical field of unmanned aerial vehicles. And acquiring fusion environment data through cooperative sensing of multiple unmanned aerial vehicles, processing the data by adopting a semantic boundary extraction algorithm based on deep learning, and outputting a sudden no-fly zone map and unmanned aerial vehicle safety state codes. On the basis, the unmanned aerial vehicles are shunted according to the safety state codes and the sudden no-fly zone map, real-time obstacle avoidance tracks are generated for the non-intruding unmanned aerial vehicles, and cluster collaborative separation is executed for the intruding unmanned aerial vehicles. For unmanned aerial vehicles whose tasks are interrupted due to obstacle avoidance or separation, task decomposition is realized based on the sudden no-fly zone map and space-time isolation, and continuous execution of cluster tasks is realized through an energy consumption constraint auction mechanism, so that a plurality of unmanned aerial vehicles can better cope with a complex and changeable sudden no-fly zone environment.

The invention discloses a low-altitude airspace planning method and system based on a micro-terminal area, and relates to the field of low-altitude airspace planning, and the method comprises the steps: generating a corresponding take-off and landing area for a low-altitude take-off and landing point or a take-off and landing field, and generating a take-off and landing hub area for an adjacent take-off and landing point or a take-off and landing field, so as to construct the micro-terminal area of the low-altitude airspace; constructing a risk area, and forming a restricted area of the low-altitude airline network together with the control area and the no-fly area; on the basis of the restricted area, generating alternative intermediate points connected with the take-off and landing points or the take-off and landing fields; based on the data of the alternative intermediate points and the data of the micro-terminal area, constructing an initial low-altitude airline network connected with all the points; calculating a weight corresponding to each side line in the initial low-altitude airline network, and optimizing the initial low-altitude airline network based on a weighted network; and removing redundant intermediate points based on the optimized network, constructing access points of the airline network and each micro-terminal area, and generating a final low-altitude airline network. According to the invention, a more reliable technical basis is provided for low-altitude route network planning.

The invention relates to the technical field of electric power, in particular to an unmanned aerial vehicle route automatic planning method and system for a complex space of a transformer substation. Analyzing at least one inspection task instruction input by a user to obtain a task type corresponding to each inspection task instruction and a data acquisition requirement corresponding to the task type; according to a preset three-dimensional semantic map of the transformer substation and the data acquisition requirement of each inspection task instruction, a flight route of at least one unmanned aerial vehicle is automatically generated by adopting a path planning algorithm, and the flight route comprises a waypoint sequence, a flight height, a shooting angle and a holder action instruction; the three-dimensional semantic map comprises no-fly zone information in the transformer substation, a plurality of devices, the position of each device, the device type, the electrification attribute and the safety rule label. And controlling the corresponding unmanned aerial vehicle to inspect target equipment in the transformer substation according to the flight route of each unmanned aerial vehicle. And large-scale and standardized inspection operation is realized.

The invention discloses an intelligent flight route planning method and system for a low-altitude logistics aircraft, and the method comprises the steps: obtaining the three-dimensional space map data of the current position of the aircraft, including the coordinate information of a building and a telegraph pole, and the boundary range of a no-fly zone; acquiring wind speed, wind direction and rainfall data of the current area from a meteorological data source, and calculating meteorological impact factors by combining aircraft performance parameters; dynamically adjusting the candidate flight routes according to the maneuvering characteristic parameters of the aircraft, and calculating the flight time, the energy consumption cost and the safety risk score of each route; meteorological changes in the flight process are monitored in real time, and if the meteorological conditions exceed a preset threshold value, the meteorological data are obtained again, and the meteorological influence factors are updated; and carrying out local optimization adjustment on the current flight route according to the updated meteorological influence factor, generating a new flight route segment and replacing the original segment.

The invention relates to the technical field of forest steppe fire emergency command, and discloses a forest steppe fire comprehensive monitoring and emergency command method and system. The method comprises the following steps: acquiring multi-source monitoring data of a satellite, an unmanned aerial vehicle and a ground sensor, and constructing a fire scene multi-dimensional feature vector through cooperative training and feature fusion; inputting the feature vectors into a physical simulation model to generate fire scene spreading speed and temperature gradient data; analyzing a terrain obstacle coefficient based on the spreading speed data and generating a helicopter no-fly zone coordinate and a passing attenuation factor; and solving and outputting a rescue unit deployment instruction through the scheduling matrix, and projecting a holographic image by using an augmented reality terminal to realize dynamic closed-loop feedback. Through deep fusion of a physical mechanism and reinforcement learning, the problem of separation of traditional fire prediction and resource scheduling is solved, intelligent decision-making of fire accurate prediction and emergency response is realized, and the accuracy and timeliness of fire prevention and control are remarkably improved.

The invention relates to the technical field of unmanned aerial vehicle cluster navigation, and discloses an unmanned aerial vehicle cluster navigation method based on man-machine interaction. The method comprises the steps that cluster task parameters and environment constraint conditions input by an operator are efficiently received through a multi-modal interaction interface, the cluster task parameters comprise a target point coordinate set and formation form identification, and the environment constraint conditions cover no-fly zone coordinates and meteorological interference levels. And the system calls a pre-stored topological relation template according to the formation form identifier to generate an initial track, completes space conflict detection in combination with the no-fly zone coordinates, and outputs a corrected track point sequence. And inputting the meteorological interference level into a dynamic anti-interference model to calculate a course correction amount, and superposing the course correction amount to a corrected track point sequence to generate an anti-interference navigation instruction set. And acquiring position data of the unmanned aerial vehicle in real time to calculate a trajectory deviation degree, triggering a manual intervention request if the trajectory deviation degree exceeds a dynamic threshold value, calling a correction instruction, fusing to generate a hybrid control strategy, and distributing the hybrid control strategy to each node of the cluster to realize reliable man-machine collaborative navigation.

The invention provides a master-slave distributed synchronous satellite navigation decoy system and a control method, and belongs to the field of satellite navigation. The system is composed of a master control station and a plurality of synchronous deception signal generators arranged in different directions. And the master control station plans a deception trajectory by using a closed-loop control principle according to modes and parameters set by a user, satellite signal parameters output by the common-view GNSS receiver and target position and speed information transmitted by the detection system, generates a satellite number distribution and power control strategy, and generates a control instruction. And the master control station controls the deception signal generator to generate and emit a navigation deception signal causing false GNSS positioning according to the flow of the GNSS navigation signal simulator. When the signal reaches a target GNSS receiver antenna, the signal is synchronized with a GNSS satellite signal received by a target so as to control and decoy an integrated navigation system carried on the target, so that the target deviates from a preset course and track, and the purpose of hiding and efficiently preventing the target from invading a no-fly zone is achieved.

The invention relates to the technical field of unmanned aerial vehicle navigation and control, in particular to an improved sparrow searching method for three-dimensional unmanned aerial vehicle path planning. According to the method, a three-dimensional mountain terrain model is constructed through a Gaussian function superposition method, obstacles and no-fly zones are defined by adopting a cylindrical geometric model, and obstacle avoidance constraints, take-off and landing safety constraints and flight height constraints are set; a comprehensive cost function with path length, threat penalty, flight safety height and path smoothness as sub-targets is constructed, an improved sparrow search algorithm is introduced, and a sine and cosine strategy is adopted in discoverer position updating to dynamically balance horizontal exploration and vertical obstacle avoidance. A Levy flight mechanism is introduced in follower position updating so as to enhance the capability of local development and jumping out of local optimum; the method comprises the steps of population initialization, role division, iterative optimization, collision detection and an elitist retention strategy. According to the method, a safe and smooth three-dimensional flight path with the optimal comprehensive cost is output, and the method is suitable for an actual unmanned aerial vehicle navigation task.

The invention discloses a multi-unmanned aerial vehicle area coverage path planning method with no-fly zone avoidance. The method comprises the following steps: converting an input operation area boundary and longitude and latitude coordinates of a no-fly zone into a UTM plane rectangular coordinate system, carrying out safety buffer area expansion on all no-fly zones, and calculating a difference set between the operation area and the safety buffer areas of all no-fly zones to obtain a final available operation area; segmenting the final available operation region to generate a plurality of sub-regions with balanced areas; for each sub-region, generating a parallel scanning route covering the region; and each sub-region line segment generates a parallel scanning route covering the region according to a preset interval. The method can ensure that the path avoids the no-fly zone, the zone distribution is balanced, and the calculation is efficient.

The invention relates to the technical field of scheme design of an unmanned aerial vehicle automatic fly-around no-fly zone, in particular to a method and system for an unmanned aerial vehicle to automatically fly around a no-fly zone. The method comprises the following steps: identifying a mountainous area environment based on topographic features (roughness, elevation standard deviation and a continuous climbing section), and constructing a safe path skeleton; generating an initial path by adopting an A * algorithm fused with an energy consumption factor, and optimizing a climbing rate through a dynamic gradient control model (in combination with a real-time pitch angle, a roll angle and a terrain gradient); a Bezier curve is used for achieving track smoothing; and responding to the no-fly zone change based on the local re-planning strategy. By means of terrain feature recognition and dynamic constraint cooperative control, mountain area low-climbing-rate path optimization is achieved. According to the method, the problems of insufficient path physical feasibility, dynamic environment response lag and the like under complex terrains are solved, and the safety and energy efficiency of the unmanned aerial vehicle flying in a no-fly zone and a mountainous area are remarkably improved.

The invention discloses an airborne visible light image automatic splicing method, and relates to the field of unmanned aerial vehicle image processing, and the method comprises the steps: obtaining a plurality of images collected in the flight process of an unmanned aerial vehicle, and the corresponding spatial position information and attitude information; on the basis of the spatial position relation between the images and the image overlapping information, determining image pairs capable of being registered, and constructing a connection map with the images as nodes and the image pairs capable of being registered as edges; detecting whether spatial connection fracture caused by image missing exists in the atlas or not, if so, inserting a virtual node and constructing a virtual image comprising an edge region and a transition region; and further calculating geometric transformation parameters between the images, resampling all image contents to a unified coordinate system, and executing pixel-level fusion processing in an image overlapping region. According to the invention, the problem of discontinuous image splicing of the unmanned aerial vehicle due to the existence of a no-fly zone, a privacy protection zone and the like of the unmanned aerial vehicle is solved.

The invention discloses a dynamic planning method and system for a photovoltaic multi-unmanned aerial vehicle cooperative inspection route, and belongs to the technical field of photovoltaic power station inspection, and the method comprises the steps: carrying out the three-dimensional modeling, dividing a no-fly area and a flight area, and building a multi-unmanned aerial vehicle ad hoc network communication network; analyzing parameters of the intruding aircraft based on a prediction algorithm, and predicting a future path of the intruding aircraft; the ground control center receives and shares flight state information of each unmanned aerial vehicle in real time, allocates inspection layers of different heights according to parameters of the unmanned aerial vehicles, introduces an avoidance mechanism to adjust flight parameters, generates a global optimal route based on a dynamic planning algorithm of heuristic search, and performs routing inspection on the unmanned aerial vehicles. And the safe distance model converts unmanned aerial vehicle flight limitation, environmental factors and anti-collision constraints into a cost function, and dynamically adjusts an inspection route. According to the invention, the limitation of the unmanned aerial vehicle in a complex environment can be effectively improved, the adaptability of the photovoltaic power station unmanned aerial vehicle to environment change in patrol inspection is improved, and the safety of the whole patrol inspection process is ensured while the patrol inspection efficiency is ensured.

The invention provides an aerial survey unmanned aerial vehicle route planning method and system, and the method mainly comprises four steps: map coordinate conversion, polygon processing, polygon decomposition, and path planning, and through the four steps, the aerial survey unmanned aerial vehicle route planning method employs a full-coverage path planning algorithm. After the boundary of the operation area and the coordinate information of the no-fly area are obtained, the air route is automatically generated to avoid the no-fly area and the path is shortest, so that the method is really applied to aerial photogrammetry operation, the reasonable shortest path can be planned for the operation area in any shape, the operation area cannot fly to the no-fly area, the turning frequency is reduced, and the working efficiency is improved. The phenomenon of repeated flight is avoided, and the operation efficiency of the aerial survey unmanned aerial vehicle is improved.

The invention relates to the technical field of wind power plant inspection, and discloses an unmanned aerial vehicle inspection path planning method and device for a wind power plant, equipment and a medium, and the method comprises the steps: building an inspection scene of the wind power plant and an unmanned aerial vehicle no-fly zone in the inspection scene, and determining a fan inspection point based on the unmanned aerial vehicle no-fly zone; taking the minimum inspection path cost as a target, and enabling a preset unmanned aerial vehicle global inspection task to be equivalent to a traveling salesman problem without a fixed starting point based on a fan inspection point; solving a feasible inspection path and a corresponding path length in the traveling salesman problem without a fixed starting point by adopting a target offset fast search tree algorithm of strategy interaction; and solving an optimal inspection path by adopting a genetic algorithm based on the feasible inspection path and the corresponding path length. The routing inspection path can avoid mountain obstacles and no-fly zones and deviates to the target point, the routing inspection efficiency is high, and the problem that unmanned aerial vehicle routing inspection path planning is not carried out for the wind power plant scene in the mountain land is solved.

The invention discloses a three-dimensional point cloud-based intelligent management and control method and system for non-power-cut operation of a distribution network, and relates to the technical field of power operation management and control, and the method comprises the steps: integrating distribution network line data through a GIS, and eliminating a no-fly zone and an interference zone to generate an unmanned plane inspection route; a high-definition camera and a laser radar are used for collecting images and environment parameters, and a three-dimensional point cloud model is constructed. And calculating a shooting angle and classifying images based on the position relationship between the unmanned aerial vehicle and the tower, and fusing multi-source data to optimize the model precision. Effective images are screened, optimal angle parameters are determined, an optimal route is generated, the abnormal state of equipment is automatically recognized according to a route real-time collection data comparison model, fault alarm is triggered, maintenance resources are dispatched, and dynamic monitoring and closed-loop management and control are achieved. The method has the advantages that three-dimensional modeling, intelligent path planning and real-time analysis are integrated, the inspection efficiency and safety are remarkably improved, the manual intervention requirement is reduced, and the method is suitable for complex environment distribution network operation and maintenance.

The invention discloses a method and a system for planning a route of an unmanned aerial vehicle over a lake by fusing meteorological data, and belongs to the technical field of unmanned aerial vehicle navigation. The method comprises the following steps: acquiring an initial route according to an unmanned aerial vehicle flight starting place and no-fly zone data; obtaining current meteorological data of an area corresponding to the initial route of the unmanned aerial vehicle, inputting the current meteorological data into the climate risk model, outputting a risk entropy value, and judging whether the unmanned aerial vehicle passes through a high-risk field; meanwhile, the flight safety of the unmanned aerial vehicle is judged according to the stability function; if the initial route passes through the high-risk field and the flight safety of the unmanned aerial vehicle is dangerous, taking a cost function to obtain a minimum value as a target, and optimizing the initial route to obtain a target route; and if the flight safety of the unmanned aerial vehicle is safe, taking the initial route as a target route. And safe flight and compliance control in a complex airspace above a lake are realized.

The invention relates to takeoff and landing field management and control, in particular to a traffic light management and control method and device suitable for a low-altitude multi-aircraft mixed takeoff and landing field, an airspace is divided into a plurality of three-dimensional grid units, the three-dimensional grid units suitable for flight are represented by green, and the three-dimensional grid units not suitable for flight are represented by red; three-dimensional grid units passed by the manned aircraft within a certain time period are prompted in a striking mode, it is determined that the corresponding airspace is a strict no-fly zone within a certain time period, and an improved fast and adaptive perception planning algorithm is adopted to plan a flight path for the unmanned aerial vehicle; according to the technical scheme, the defects that in the prior art, visual and refined expression is lacked in the aspect of airspace state management, and the requirements of a low-altitude multi-aircraft mixed take-off and landing field for flight safety and efficient operation are difficult to meet in the aspect of unmanned aerial vehicle flight path planning can be effectively overcome.

The invention discloses a highway inspection unmanned aerial vehicle task planning monitoring system based on a knowledge graph, particularly relates to the technical field of unmanned aerial vehicle intelligent inspection, and is used for solving the problem that an existing system cannot generate a feasible decision scheme when an airspace control rule conflicts with an emergency timeliness requirement. The method comprises the following steps: constructing a knowledge graph integrating geographic no-fly zone space coordinates, an aging constraint time threshold and a traffic flow thermodynamic map layer, triggering a rule conflict state when detecting that an overlapping region exists between an aging constraint target position and a no-fly zone, and further fusing a real-time traffic control instruction and unmanned aerial vehicle maneuvering characteristic parameters to generate an elastic space domain; and after verification of a high-flow area overlapping rate threshold value or approval of a forced passing instruction, creating a temporary channel entity which covers the overlapping area coordinates and is associated with a time threshold value, and finally generating an inspection route which penetrates through a conflict area and meets a passing time limit based on the entity, thereby realizing coordination of dynamic rule conflict resolution and safety emergency inspection.

The invention discloses an unmanned aerial vehicle voyage cost estimation method, and relates to the field of multi-unmanned aerial vehicle cooperative task planning. The method comprises the following steps: firstly, initializing a map, marking positions of all parts, and then constructing a vertical cutting surface to obtain height values of all terrain intersection points; finally, whether the flight path passes through a threat area or a no-fly area is judged, and the pre-estimated flight path length is calculated by adopting a terrain following method for a conventional flight path section; for the defense penetration flight path section of the threat area, calculating an estimated flight path length by adopting a flight path planning method combining dynamic terrain shielding and a reverse A * algorithm; and calculating an estimated flight path length by adopting a flight path planning method combining an improved pigeon inspired optimization algorithm and an A * algorithm aiming at a bypassing flight path section of the no-fly zone. According to the method, defense penetration of the threat area and bypassing of the no-fly area are considered, and compared with two-dimensional voyage cost in many literatures, the method is more reasonable, and the reasonability of subsequent task allocation work is better facilitated.

The invention discloses an unmanned aerial vehicle non-inductive safety supervision and inspection method and system based on three-dimensional point cloud route automatic planning. The method comprises the following steps: collecting ledger data; issuing a non-inductive supervision inspection work order; scheduling an optimal airport; marking a no-fly zone and potential obstacles according to the point cloud data of the tower line; constructing an outbound route; according to the inspection type of the inspection work order, constructing an inspection operation area point route, if the inspection type is general inspection, the inspection operation area point route is an S-shaped route, and if the inspection type is key inspection, the inspection operation area point route is a surrounding route; constructing a return route according to the reverse order of the forward route; generating a complete safety supervision route by combining the go route, the supervision operation area point route and the return route; and carrying out three-dimensional point cloud collision detection, if the detection is passed, issuing the detection result to the unmanned aerial vehicle to execute a complete safety supervision route, otherwise, carrying out fine adjustment on the complete safety supervision route until the detection is passed. According to the invention, the efficiency and accuracy of route planning are improved.

The invention discloses a multi-unmanned aerial vehicle cooperation-oriented low-altitude Internet of Things secure communication method and system, and belongs to the technical field of low-altitude Internet of Things. The method comprises the following steps: constructing a multi-unmanned aerial vehicle collaborative optimization model integrating a no-fly zone, a ground obstacle zone, communication security and energy consumption constraint; aiming at a high-dimensional non-convex characteristic of the model, a solution algorithm based on a multi-agent depth deterministic strategy gradient framework is adopted, and a local observation space containing a self state, environment information and a channel state and an action space containing speed adjustment and power adjustment are designed for each unmanned aerial vehicle agent through a centralized training decentralized execution mechanism; and a multi-target reward function is defined, so that the intelligent agent autonomously learns a cooperative strategy in a complex environment through training, and an optimized unmanned aerial vehicle track and transmitting power control instruction is jointly output. According to the invention, on the premise of strictly ensuring flight safety and physical layer safety, the sum of long-term safety communication rates of the low-altitude Internet of Things is effectively improved, and the method has good dynamic adaptability and expandability.

The invention discloses a safety supervision method and system for the flight state of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle safety supervision. Flight behavior characteristics are compared with a global reference generated through federal learning, and when a malicious unmanned aerial vehicle passes authentication through a forged electronic identifier, a positioning verification mechanism is triggered in real time; illegal invasion is effectively identified and intercepted, and the problem of response delay caused by dependence on manual checking in the prior art is solved; meanwhile, the judgment standard is automatically tightened according to the safety level of the no-fly zone, the core zone adopts a stricter threshold amplitude, and the disguise unmanned aerial vehicle is forced to be exposed abnormally; the threshold value is in smooth transition during cross-regional flight, so that the misoperation risk caused by sudden change of a judgment standard in a traditional scheme is avoided; a hardware isolation area operation behavior analysis model of the unmanned aerial vehicle flight control chip is reused, and a calculation module does not need to be newly added; existing positioning base stations are dynamically dispatched to construct a verification network, and the reconstruction cost of supervision infrastructures is remarkably reduced.

The invention discloses an unmanned aerial vehicle autonomous route planning method and system capable of adapting to environmental changes. The method comprises the steps of obtaining a dynamic three-dimensional situation map of a flight area of an unmanned aerial vehicle based on multi-source data of the flight area of the unmanned aerial vehicle; acquiring a current no-fly zone and weather forecast information of the flight area of the unmanned aerial vehicle, and analyzing and acquiring a flight risk distribution condition of the flight area of the unmanned aerial vehicle based on the dynamic three-dimensional situation map; considering the flight risk distribution condition of the unmanned aerial vehicle flight area, the unmanned aerial vehicle flight task and the unmanned aerial vehicle self-state information to generate an unmanned aerial vehicle reference route; and automatically adjusting the flight speed, the flight height and the flight course of the unmanned aerial vehicle according to a preset flight parameter adjustment model based on the acquired multi-source data and the state information of the unmanned aerial vehicle in the process of flying along the reference route. According to the invention, the reliability and safety of flight task execution of the unmanned aerial vehicle in a complex dynamic environment can be improved.

The invention provides a multi-unmanned aerial vehicle dynamic path planning system and method, and the system comprises a coordinate conversion module which is used for carrying out the bidirectional conversion of latitude and longitude coordinates and three-dimensional grid coordinates, so as to establish a unified space-time coordinate conversion reference; the map module is used for constructing a three-dimensional airspace representation model; the three-dimensional airspace representation model records position information of an obstacle and boundary range information of the temporary no-fly zone so as to provide real-time airspace information; the route module is used for delimiting an exclusive safety area for each unmanned aerial vehicle in the air; the path planning module is used for performing multi-machine path planning based on the real-time airspace information and the space-time occupancy state; the map module, the route module and the path planning module work cooperatively based on a unified space-time coordinate conversion reference. Through unified three-dimensional grid map representation and a space-time occupation management system, integrated coordination optimization of the whole process from flight plan approval to flight execution is realized, and real-time dynamic management of a large-scale multi-machine system is supported.

The embodiment of the invention provides an unmanned aerial vehicle route early warning method, system and device for a no-fly zone and a medium, and belongs to the field of unmanned aerial vehicles. The method comprises the following steps: establishing a no-fly zone spatial database, and storing electronic fence boundaries and security level attributes of each zone; the method comprises the following steps: acquiring detection data, tracking an unmanned aerial vehicle entering a no-fly zone, generating a real-time flight path, performing compliance verification on the real-time flight path by taking a reported planned route of the unmanned aerial vehicle as a reference, marking the unmanned aerial vehicle deviating from the planned route as a suspicious target, associating identity information of the unmanned aerial vehicle with pilot information, and triggering primary early warning at the same time; and for a suspicious target, carrying out spatial superposition calculation on the flight path of the suspicious target and the electronic fence of the no-fly zone, determining an intrusion risk level according to a security level attribute, and generating an intrusion event and advanced early warning information. Accurate monitoring and track traceability management and control of the unmanned aerial vehicles in key areas are realized, and the accuracy of safety prevention and control of the unmanned aerial vehicles in the areas is improved.