Visual management system for air route and route of unmanned aerial vehicle

Abstract

The invention provides an unmanned aerial vehicle air route visual management system, and belongs to the technical field of unmanned aerial vehicle visual management, and the system comprises a collection module which obtains the model of a target unmanned aerial vehicle, determines a corresponding sensor, and collects the flight data of the unmanned aerial vehicle in real time; the first determination module is used for processing the flight data and determining the optimal route of the unmanned aerial vehicle based on a path planning algorithm; the dynamic adjustment module is used for acquiring surrounding environment parameters of the unmanned aerial vehicle and dynamically adjusting the optimal route of the unmanned aerial vehicle; the display module is used for visually displaying the flight path and the meteorological condition of the unmanned aerial vehicle according to the GIS technology, and obtaining the dynamic flight situation monitoring of the unmanned aerial vehicle; and the triggering module is used for setting a safety threshold according to the performance of the unmanned aerial vehicle and the real-time environment condition, triggering an alarm according to the safety threshold, and realizing visual management of the air route of the unmanned aerial vehicle according to the alarm information. The problems that the route planning is inaccurate, the visualization effect is poor and the real-time performance of acquiring the flight data cannot be ensured due to manual operation are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) visual management, and in particular to a UAV route visual management system. Background Art

[0002] With the development of my country's economy, the demand for transportation is increasing. Among various means of transportation, drones, as a new mode of transportation, have received extensive attention and research. The traditional drone route visualization management system requires manual operation, which can easily lead to untimely and inaccurate route planning, especially in complex environments. This untimely and inaccurate planning may cause serious flight accidents. At the same time, the visualization effect of the traditional drone route visualization management system is usually poor, and it cannot clearly reflect the actual position and speed of the drone, and cannot guarantee the real-time acquisition of flight data, resulting in the inability to issue timely warnings and flight hazards.

[0003] Therefore, the present invention proposes a UAV route visualization management system. Summary of the invention

[0004] The present invention provides a UAV route visualization management system to solve the problem that the existing technology requires manual operation, which easily leads to untimely and inaccurate route planning, especially in complex environments. Such untimely and inaccurate planning may cause serious flight accidents. At the same time, the visualization effect of traditional UAV route visualization management systems is usually poor, and the actual position and speed of the UAV cannot be clearly reflected, and the real-time acquisition of flight data cannot be guaranteed, resulting in the defect that timely warning cannot be issued and flight hazards occur.

[0005] In one aspect, the present invention provides a UAV route visualization management system, comprising: Collection module: obtains the model of the target UAV, determines the corresponding sensor according to the model, and collects the flight data of the UAV in real time based on the sensor; The first determination module processes the flight data according to the data fusion technology, and determines the optimal route of the UAV based on the processing result and the path planning algorithm; Dynamic adjustment module: obtains the real-time surrounding environment parameters of the target UAV, and dynamically adjusts the optimal route of the UAV according to the real-time surrounding environment parameters; Display module: Based on GIS technology, the adjusted flight trajectory and weather conditions of the drone are visualized and updated in real time to obtain dynamic flight situation monitoring of the drone; Trigger module: Sets a safety threshold based on the UAV's performance and real-time environmental conditions based on the UAV's dynamic flight situation monitoring, triggers an alarm based on the safety threshold, and implements visual management of the UAV's route based on the alarm information.

[0006] According to the present invention, a UAV route visualization management system, a collection module, includes: A first determination unit: obtaining structure and appearance characteristics of the target UAV, and determining the model of the target UAV according to the structure and appearance characteristics; A first acquisition unit: determining a sensor specification and a compatibility requirement according to the model, and acquiring a corresponding sensor based on the sensor specification and the compatibility requirement; Configuration unit: Configure the sensor interface and communication protocol according to the product manual to obtain the real-time flight data of the drone.

[0007] According to a UAV route visualization management system provided by the present invention, the first determination module includes: Data fusion unit: fuses the flight data acquired by different sensors based on fusion algorithms; The first generation unit generates the flight path points and flight path of the UAV based on the fused data and predefined navigation rules; Comparison unit: Use the fused data to determine the distance between each adjacent path point, compare the length of each path according to the distance between each path point, and obtain the comparison result; The second acquisition unit: according to the comparison result, based on the obstacle avoidance algorithm, the optimal route of the UAV is obtained by minimizing the path length and the time to avoid obstacles.

[0008] According to the present invention, a UAV route visualization management system and a dynamic adjustment module include: The third acquisition unit: acquires the real-time surrounding environment parameters of the target UAV according to sensors related to environmental perception; Identification and filtering unit: identifying and filtering the surrounding environment parameters to obtain key environmental parameters; Adjustment unit: adjusts the flight mode and safety parameters of the drone based on the heuristic algorithm according to the pre-set destination information and current environmental conditions; Dynamic adjustment unit: dynamically adjust the optimal route of the drone based on the adjustment results.

[0009] According to the present invention, a UAV route visualization management system and a display module are provided, including: A second determination unit: obtaining an adjusted flight trajectory of the UAV according to the fuel consumption and time delay of the UAV, and determining the position information of the UAV according to the flight trajectory; The second generating unit is used to obtain real-time changes in meteorological conditions and generate real-time UAV mission planning in combination with the position information of the UAV; Display unit: Generate a visual map based on GIS technology according to the UAV mission planning for visual display and update in real time; The fourth acquisition unit generates a real-time task scheduling suggestion according to the update result, and acquires the dynamic flight situation monitoring of the UAV according to the task scheduling suggestion.

[0010] According to the present invention, a UAV route visualization management system, a trigger module, includes: The fifth acquisition unit: acquires the performance data and restriction parameters of the drone according to the drone document; A sixth acquisition unit: acquiring real-time environmental condition parameters of the UAV according to multiple devices of the UAV; A third determination unit: establishing a model based on a machine learning algorithm according to the performance parameters of the UAV and the real-time environmental condition parameters to determine the optimal flight parameters of the UAV; Setting unit: setting a safety threshold for the flight of the UAV based on the optimal flight parameters of the UAV and the dynamic flight situation monitoring of the UAV; A judgment unit: judging the real-time flight status and real-time flight parameters of the UAV according to the safety threshold of the UAV flight; Extraction unit: If the judgment result exceeds the safety threshold, an alarm is triggered, key feature information in the alarm information is extracted, and visual management of the UAV route is achieved based on the key feature information.

[0011] A UAV route visualization management system according to the present invention also includes: Query module: determine the corresponding operation interface according to the user's needs and usage habits, and conduct multi-angle and multi-form queries based on the operation interface; Permission authentication module: obtains the identity information of the querying user, performs permission authentication based on the identity information, and determines whether the user is an internal user of the data access object based on the authentication result. If not, obtains the external user access security policy in the data access scenario; The second determination module: determines the data description parameters within the user's access permission range according to the external user access security policy; Retrieval module: retrieves relevant permission data from the data repository of the data access object according to the data description parameters and the type of data to be retrieved by the user.

[0012] According to the present invention, a UAV route visualization management system, a setting unit includes: The first determination subunit: obtains the flight area review parameters of the UAV, and determines the macro flight situation index set and the micro flight situation index set of the UAV according to the review parameters; Generating subunit: generating the flight point sequence of the UAV based on the UAV's macroscopic flight situation index set and microscopic flight situation index set according to the optimal flight parameters of the UAV; The first acquisition subunit: maps the UAV's mapped flight point sequence to obtain the UAV's flight status heat map; The second determination subunit: determines the flight altitude and flight attitude information of the UAV according to the flight status thermal map; The third determination subunit determines the flight threat source information and the flight power source information of the UAV based on the flight altitude information and the flight attitude information combined with the environmental parameter information of the flight area; Establish subunits: establish threat situation quantification matrix and power situation quantification matrix according to flight threat source information and flight power source information; The fourth determination subunit: determines multiple flight decision indicators and specific indicator reference values ​​through the threat situation quantification matrix and the power situation quantification matrix; Setting subunit: Setting the safety threshold of UAV flight based on flight decision indicators and specific indicator reference values.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The optimal route of the drone is determined based on the path planning algorithm based on the flight data of the drone, and the optimal route is dynamically adjusted and visualized, and early warning is issued according to the performance of the drone and real-time environmental conditions, avoiding serious flight accidents caused by untimely and inaccurate route planning caused by manual operation. At the same time, the visualization effect of the visualization management system is improved, and the actual position and speed of the drone are clearly reflected, ensuring the real-time acquisition of flight data, and timely warning is issued to avoid flight hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1 This is one of the structural schematic diagrams of the UAV route visualization management system provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of the process structure of the collection module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Embodiment 1: An embodiment of the present invention provides a visual management system for unmanned aerial vehicle routes, such as Figure 1 As shown, the system mainly includes the following modules: Collection module: obtains the model of the target UAV, determines the corresponding sensor according to the model, and collects the flight data of the UAV in real time based on the sensor; The first determination module processes the flight data according to the data fusion technology, and determines the optimal route of the UAV based on the processing result and the path planning algorithm; Dynamic adjustment module: obtains the real-time surrounding environment parameters of the target UAV, and dynamically adjusts the optimal route of the UAV according to the real-time surrounding environment parameters; Display module: Based on GIS technology, the adjusted flight trajectory and weather conditions of the drone are visualized and updated in real time to obtain dynamic flight situation monitoring of the drone; Trigger module: Sets a safety threshold based on the UAV's performance and real-time environmental conditions based on the UAV's dynamic flight situation monitoring, triggers an alarm based on the safety threshold, and implements visual management of the UAV's route based on the alarm information.

[0018] In this embodiment, the sensor is a device that can sense and measure various environmental quantities, including: a gyroscope, an accelerometer, an altimeter, a barometer, and an electronic compass.

[0019] In this embodiment, the flight data of the UAV includes: aircraft attitude changes, aircraft acceleration changes, air pressure, temperature, altitude, and direction.

[0020] In this embodiment, data fusion technology refers to a technology that integrates and processes information from multiple data sources to obtain more accurate and reliable decision support and information extraction, such as: Kalman filter, Bayesian network, neural network.

[0021] In this embodiment, the path planning algorithm is an algorithm for solving the shortest path problem from an initial position to a target position in an unknown environment, such as Dijkstra algorithm and A* algorithm.

[0022] In this embodiment, the optimal route of the drone refers to the optimal route that the drone should fly when performing a specific mission.

[0023] In this embodiment, the real-time surrounding environment parameters of the drone include: altitude, wind speed and direction, positioning, and temperature.

[0024] In this embodiment, dynamic adjustment refers to real-time monitoring of the flight parameters, attitude, etc. of the drone during flight and automatic adjustment based on actual conditions, including adjustments in speed control, position maintenance, and attitude stabilization.

[0025] In this embodiment, GIS technology, namely geographic information system technology, is a technical system for collecting, storing, managing, calculating, analyzing, displaying and describing geographic spatial data through computer hardware, software and data sharing.

[0026] In this embodiment, the flight trajectory refers to the route that the drone travels throughout the entire process from take-off to landing, and can be drawn by recording the GPS positioning point and flight time of the drone.

[0027] In this embodiment, meteorological conditions refer to various weather phenomena and atmospheric conditions that affect aircraft flight in a specific area and time period, such as visibility, wind direction and speed, clouds, and atmospheric pressure.

[0028] In this embodiment, the dynamic flight status monitoring of the UAV refers to real-time monitoring of the flight status of the UAV through a remote controller or a ground station to ensure that the UAV is always within a controllable range during the flight.

[0029] In this embodiment, the performance of the UAV includes: flight altitude, flight speed, wind resistance, and control radius.

[0030] In this embodiment, the real-time environmental conditions refer to various parameters of the current surrounding environment, such as temperature, humidity, air pressure, wind direction, and wind speed.

[0031] In this embodiment, the safety threshold is a range set during the design and operation of the drone to ensure that the drone can operate normally and safely under various weather conditions and operating conditions. For example, the maximum flight altitude is 1,000 meters. If it exceeds 1,000 meters, an early warning alert will be issued.

[0032] The beneficial effects of the above technical solution are: by determining the optimal route of the UAV based on the path planning algorithm based on the flight data of the UAV, dynamically adjusting the optimal route, visually displaying it, and issuing early warnings based on the performance of the UAV and real-time environmental conditions, serious flight accidents caused by untimely and inaccurate route planning caused by manual operation are avoided. At the same time, the visualization effect of the visualization management system is improved, and the actual position and speed information of the UAV are clearly reflected, ensuring the real-time acquisition of flight data, and timely warnings are issued to avoid flight hazards.

[0033] Embodiment 2: Based on Example 1, the collection module of the embodiment of the present invention is as follows: Figure 2 As shown, including: A first determination unit: obtaining structure and appearance characteristics of the target UAV, and determining the model of the target UAV according to the structure and appearance characteristics; A first acquisition unit: determining a sensor specification and a compatibility requirement according to the model, and acquiring a corresponding sensor based on the sensor specification and the compatibility requirement; Configuration unit: Configure the sensor interface and communication protocol according to the product manual to obtain the real-time flight data of the drone.

[0034] In this embodiment, the structure of the drone includes: a flight controller, a power system, a navigation system, and a remote controller.

[0035] In this embodiment, the appearance features of the drone include: fuselage material, rotor and tail, sensor cabin, and electronic equipment cabin.

[0036] In this embodiment, the specifications of the sensor refer to its performance parameters on the drone, including: Resolution: refers to the minimum resolvable size of the sensor. For example, camera resolution can be divided into several percentage levels. For example, 4K means that 4096 points (pixels) can be distinguished in every inch of visible area.

[0037] Frame rate: This is how many photos or videos can be taken per second. A higher frame rate can make the movement smoother.

[0038] Distance measurement accuracy: used to describe the accuracy of the sensor in measuring distance. For example, using HDR technology can improve distance measurement accuracy.

[0039] Field of view angle: refers to the range that the sensor can see on the horizontal plane. The larger the viewing angle, the wider the field of view.

[0040] Anti-interference: refers to the ability of the sensor to continue to work normally when encountering obstructions or electromagnetic interference.

[0041] In this embodiment, the compatibility requirements include: integration with the UAV system and compatibility with the ground station.

[0042] In this embodiment, the sensor interface refers to a channel for data exchange or communication between the sensor and other electronic devices or systems.

[0043] In this embodiment, the communication protocol is the agreement or specification followed when the drone interacts with the ground station, other unmanned systems and various sensors, and defines the format, encoding method and synchronization method of the data, such as: RC protocol and FUTABA protocol.

[0044] The beneficial effects of the above technical solution are: determining the corresponding sensor according to the sensor specifications and compatibility requirements of the drone model, and obtaining the real-time flight data of the drone, can ensure that all sensors follow the same standards and specifications, avoiding equipment waste or functional limitations due to interface or protocol incompatibility, and further avoiding confusion and inaccuracy in data acquisition.

[0045] Embodiment 3: Based on Example 2, the first determination module in this embodiment of the present invention includes: Data fusion unit: fuses the flight data acquired by different sensors based on fusion algorithms; The first generation unit generates the flight path points and flight path of the UAV based on the fused data and predefined navigation rules; Comparison unit: Use the fused data to determine the distance between each adjacent path point, compare the length of each path according to the distance between each path point, and obtain the comparison result; The second acquisition unit: according to the comparison result, based on the obstacle avoidance algorithm, the optimal route of the UAV is obtained by minimizing the path length and the time to avoid obstacles.

[0046] In this embodiment, data fusion technology refers to a technology that integrates and processes information from multiple data sources to obtain more accurate and reliable decision support and information extraction, such as: Kalman filter, Bayesian network, neural network.

[0047] In this embodiment, the predefined navigation rules refer to rules set in advance in the flight mission of the drone to ensure that the drone flies autonomously according to the predetermined trajectory, such as: Waypoint planning: The mission area is divided into several fixed waypoints. The drone needs to complete the scanning and landing tasks of these waypoints in sequence within the specified time and fuel consumption.

[0048] Obstacle avoidance strategy: During the navigation process of the drone, it is necessary to take into account the obstacles in the surrounding environment, such as buildings, trees, etc., to avoid collisions with them.

[0049] Time limit: Set a reasonable operating time range for the drone to ensure that the mission can be completed within the specified time limit.

[0050] In this embodiment, the flight path points of the drone refer to a series of predetermined paths followed by the drone when performing a flight mission.

[0051] In this embodiment, the obstacle avoidance algorithm is a technology for autonomous navigation of a UAV, and its main purpose is to enable the UAV to avoid collision with other objects during flight, such as: visual obstacle avoidance algorithm, lidar obstacle avoidance algorithm.

[0052] The beneficial effects of the above technical solution are: generating the flight path points and flight path of the UAV according to the fused flight data combined with the pre-defined navigation rules, comparing the length of each path according to the distance of each path point, and obtaining the optimal route based on the obstacle avoidance algorithm, so that the UAV can avoid obstacles and other risk factors, thereby improving the safety of flight. At the same time, determining the optimal route can improve the flight efficiency of the UAV.

[0053] Embodiment 4: Based on Example 3, the dynamic adjustment module of the embodiment of the present invention includes: The third acquisition unit: acquires the real-time surrounding environment parameters of the target UAV according to sensors related to environmental perception; Identification and filtering unit: identifying and filtering the surrounding environment parameters to obtain key environmental parameters; Adjustment unit: adjusts the flight mode and safety parameters of the drone based on the heuristic algorithm according to the pre-set destination information and current environmental conditions; Dynamic adjustment unit: dynamically adjust the optimal route of the drone based on the adjustment results.

[0054] In this embodiment, sensors related to environmental perception include: distance sensor, laser radar, camera, and barometer.

[0055] In this embodiment, the environmental parameters include: altitude, speed, direction, and weather.

[0056] In this embodiment, the heuristic algorithm refers to a type of algorithm that is not guaranteed to be absolutely correct but can usually obtain a satisfactory solution.

[0057] In this embodiment, the flight mode of the drone refers to the behavior of the drone in different states in the air, such as autonomous flight mode, remote control mode, and autonomous navigation mode.

[0058] In this embodiment, the safety parameters of the drone are important indicators for evaluating the safety performance of the drone, such as: flight speed, battery life, and obstacle avoidance capability.

[0059] The beneficial effects of the above technical solution are: the flight mode and safety parameters of the UAV are adjusted based on the heuristic algorithm according to the pre-set destination information and current environmental conditions, so as to dynamically adjust the optimal route of the UAV, and the flight path of the UAV can be adjusted in real time according to the actual environmental conditions, and respond to environmental changes in real time, making the flight of the UAV more flexible and adaptable, thereby improving flight safety.

[0060] Embodiment 5: Based on Example 4, the display module of the embodiment of the present invention includes: A second determination unit: obtaining an adjusted flight trajectory of the UAV according to the fuel consumption and time delay of the UAV, and determining the position information of the UAV according to the flight trajectory; The second generating unit is used to obtain real-time changes in meteorological conditions and generate real-time UAV mission planning in combination with the position information of the UAV; Display unit: Generate a visual map based on GIS technology according to the UAV mission planning for visual display and update in real time; The fourth acquisition unit generates a real-time task scheduling suggestion according to the update result, and acquires the dynamic flight situation monitoring of the UAV according to the task scheduling suggestion.

[0061] In this embodiment, time delay refers to the situation where the UAV fails to complete the flight mission on time due to various reasons.

[0062] In this embodiment, the location information of the drone refers to data for determining the geographical location of the drone during its flight in the air, including longitude, latitude, and altitude information.

[0063] In this embodiment, UAV mission planning refers to specifying a specific flight plan for the UAV to ensure that it can complete the expected mission safely and efficiently.

[0064] In this embodiment, the task scheduling suggestion refers to a suggestion for formulating a detailed action plan for the drone when performing a specific task, such as: determining the mission type and purpose of the drone, and determining the operation mode of the drone.

[0065] The beneficial effects of the above technical solution are: generating real-time drone mission planning based on the drone's location information combined with real-time changes in meteorological conditions, and visually displaying and updating it in real time through a visual map, obtaining dynamic flight status monitoring of the drone. The visual map can clearly display the terrain, topography and other information of the mission area, which is convenient for drone pilots to perform tasks and improve mission efficiency. At the same time, the operating status of the drone can be grasped in real time to optimize the scheduling and management of the drone.

[0066] Embodiment 6: Based on Example 5, the trigger module of this embodiment of the present invention includes: The fifth acquisition unit: acquires the performance data and restriction parameters of the drone according to the drone document; A sixth acquisition unit: acquiring real-time environmental condition parameters of the UAV according to multiple devices of the UAV; A third determination unit: establishing a model based on a machine learning algorithm according to the performance parameters of the UAV and the real-time environmental condition parameters to determine the optimal flight parameters of the UAV; Setting unit: setting a safety threshold for the flight of the UAV based on the optimal flight parameters of the UAV and the dynamic flight situation monitoring of the UAV; A judgment unit: judging the real-time flight status and real-time flight parameters of the UAV according to the safety threshold of the UAV flight; Extraction unit: If the judgment result exceeds the safety threshold, an alarm is triggered, key feature information in the alarm information is extracted, and visual management of the UAV route is achieved based on the key feature information.

[0067] In this embodiment, the performance data includes: maximum load capacity, maximum speed, and battery power.

[0068] In this embodiment, the limiting parameters include: a maximum allowable tilt angle and a maximum tolerable wind speed.

[0069] In this embodiment, the real-time environmental condition parameters include: current temperature, air pressure, wind direction, and wind speed.

[0070] In this embodiment, the optimal flight parameters refer to a set of flight settings that can maximize the performance and safety of the drone, including: the aircraft's flight mode, speed controller settings, attitude control settings, battery charging settings, and GPS settings.

[0071] In this embodiment, in the alarm information, key characteristic information includes: location information, time information, and description information.

[0072] The beneficial effects of the above technical solution are: determining the optimal flight parameters of the UAV based on the performance parameters of the UAV and the real-time environmental condition parameters, setting the safety threshold of the UAV and judging the real-time flight status and real-time flight parameters of the UAV, triggering an alarm based on the judgment result, and being able to timely determine abnormal flight status and abnormal flight parameters during the flight process, issuing an alarm when abnormal behavior is detected, thereby improving flight safety.

[0073] Embodiment 7: Based on Example 6, the embodiment of the present invention further includes: Query module: determine the corresponding operation interface according to the user's needs and usage habits, and conduct multi-angle and multi-form queries based on the operation interface; Permission authentication module: obtains the identity information of the querying user, performs permission authentication based on the identity information, and determines whether the user is an internal user of the data access object based on the authentication result. If not, obtains the external user access security policy in the data access scenario; The second determination module: determines the data description parameters within the user's access permission range according to the external user access security policy; Retrieval module: retrieves relevant permission data from the data repository of the data access object according to the data description parameters and the type of data to be retrieved by the user.

[0074] In this embodiment, multi-angle means that it can be filtered by task name, type, time range, etc., and it can also support functions such as fuzzy query and advanced search. The query results can be displayed in the form of lists, tables, etc., and can be sorted and filtered.

[0075] In this embodiment, multiple formats refer to the possibility of inputting via voice or uploading pictures.

[0076] In this embodiment, user identity information refers to personal sensitive information such as the user's name, ID number, mobile phone number, etc.

[0077] In this embodiment, permission authentication is a security mechanism that verifies the identity of a user and authorizes the user to access specific resources or perform specific operations.

[0078] In this embodiment, the internal user of the data access object refers to a person or organization that uses the software system to perform operations, and may be an employee, partner or other third-party user of the company.

[0079] In this embodiment, the external user access security policy is a security measure taken to prevent access by unauthorized users or unauthorized devices, applications, and data.

[0080] In this embodiment, the data description parameter refers to a parameter representing the characteristics of the input data, such as data quantity, data size, and data format.

[0081] The beneficial effects of the above technical solution are: determining the corresponding operation interface according to the user's habits, and authenticating the user, determining the data description parameters within the user's retrieval authority range to retrieve relevant authority data, which can ensure the security and privacy of the data and improve the reliability of the UAV route visualization management system.

[0082] Embodiment 8: Based on Example 7, the setting unit in this embodiment of the present invention includes: The first determination subunit: obtains the flight area review parameters of the UAV, and determines the macro flight situation index set and the micro flight situation index set of the UAV according to the review parameters; Generating subunit: generating the flight point sequence of the UAV based on the UAV's macroscopic flight situation index set and microscopic flight situation index set according to the optimal flight parameters of the UAV; The first acquisition subunit: maps the UAV's mapped flight point sequence to obtain the UAV's flight status heat map; The second determination subunit: determines the flight altitude and flight attitude information of the UAV according to the flight status thermal map; The third determination subunit determines the flight threat source information and the flight power source information of the UAV based on the flight altitude information and the flight attitude information combined with the environmental parameter information of the flight area; Establish subunits: establish threat situation quantification matrix and power situation quantification matrix according to flight threat source information and flight power source information; The fourth determination subunit: determines multiple flight decision indicators and specific indicator reference values ​​through the threat situation quantification matrix and the power situation quantification matrix; Setting subunit: Setting the safety threshold of UAV flight based on flight decision indicators and specific indicator reference values.

[0083] In this embodiment, the UAV flight area review parameters refer to a series of parameters for identifying and planning the flyable airspace of the UAV in the UAV system, including: no-fly zones, airspace restrictions, weather conditions, and obstacle detection.

[0084] In this embodiment, the macroscopic flight situation indicator set of the UAV refers to a set of indicators for monitoring and evaluating the entire flight process of the UAV, such as: position, heading angle and roll angle, attitude, and remote control signal strength.

[0085] In this embodiment, the microscopic flight situation indicator set of the drone refers to a set of indicators for monitoring and evaluating small changes in the drone's flight process, such as acceleration, yaw rate, pitch rate, and roll rate.

[0086] In this embodiment, the flight point sequence of the drone refers to a sequence of multiple control points determined when planning the flight path of the drone, including: a take-off point, a hovering point, a landing point, and a return point.

[0087] In this embodiment, the heat map of the flight status of the drone is a visualization tool for visualizing the movement status of the drone at different times, locations and altitudes. The heat map presents the location information of the drone in a color-coded manner, where the depth of the color represents the number of drones in the area.

[0088] In this embodiment, the drone flight threat source information refers to various factors and sources that may pose a threat to the drone flight, such as: Human interference: For example, an illegal intruder attempts to damage or interfere with the operation of a drone, or a drone operator accidentally presses the wrong button, causing the drone to lose control.

[0089] Natural environment: such as bad weather, natural disasters (such as floods, earthquakes, typhoons, etc.) and terrain obstacles.

[0090] Electronic interference: such as electromagnetic pulses, laser interference and communications interference.

[0091] Other aircraft and aerial vehicles: such as military aircraft, private aircraft and other drones.

[0092] In this embodiment, the flight power source information of the drone refers to the parameters of the equipment and technology that can provide power and control for the drone, such as: battery capacity and voltage, motor power, sensor data, GPS and inertial navigation system.

[0093] In this embodiment, the threat situation quantification matrix is ​​a method for evaluating the degree of threat in different situations. Various threat factors are scored and classified to determine their impact and priority on the drone. The matrix uses a table consisting of multiple threat factors to represent the threat level and assigns a numerical score to each factor. Each factor may be scored based on factors such as its severity in the situation, the possibility of occurrence, and the impact on the drone, ultimately forming a threat situation quantification matrix.

[0094] In this embodiment, the power status quantification matrix is ​​a method for evaluating and comparing the power status of a UAV, which is usually a table consisting of multiple power status factors. Each factor is scored according to its importance, frequency of occurrence, and impact on the system, and is classified as good, medium, or poor. By scoring and classifying these factors, a power status quantification matrix can be obtained.

[0095] In this embodiment, the multiple flight decision indicators are multiple parameters used to evaluate and determine whether the drone can safely take off and perform the mission, such as: location information, route design, and remote control.

[0096] The beneficial effects of the above technical solution are: by determining multiple flight decision indicators and specific indicator reference values ​​through the threat situation quantification matrix and the power situation quantification matrix, the safety threshold of the UAV flight is set, which can ensure that the UAV can comply with safety standards and regulations in various situations, avoid unexpected situations when the UAV is performing tasks, and reduce human errors. It ensures that the UAV can remain stable and safe in all situations, further improving the flight safety of the UAV.

[0097] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A visual management system for unmanned aerial vehicle routes, characterized in that: include: Collection module: obtains the model of the target UAV, determines the corresponding sensor according to the model, and collects the flight data of the UAV in real time based on the sensor; The first determination module processes the flight data according to the data fusion technology, and determines the optimal route of the UAV based on the processing result and the path planning algorithm; Dynamic adjustment module: obtains the real-time surrounding environment parameters of the target UAV, and dynamically adjusts the optimal route of the UAV according to the real-time surrounding environment parameters; Display module: Based on GIS technology, the adjusted flight trajectory and weather conditions of the drone are visualized and updated in real time to obtain dynamic flight situation monitoring of the drone; Trigger module: Sets a safety threshold based on the UAV's performance and real-time environmental conditions based on the UAV's dynamic flight situation monitoring, triggers an alarm based on the safety threshold, and implements visual management of the UAV's route based on the alarm information.

2. The UAV route visualization management system according to claim 1 is characterized in that: Collection modules, including: A first determination unit: obtaining structure and appearance characteristics of the target UAV, and determining the model of the target UAV according to the structure and appearance characteristics; A first acquisition unit: determining a sensor specification and a compatibility requirement according to the model, and acquiring a corresponding sensor based on the sensor specification and the compatibility requirement; Configuration unit: Configure the sensor interface and communication protocol according to the product manual to obtain the real-time flight data of the drone.

3. The UAV route visualization management system according to claim 1 is characterized in that: The first determination module includes: Data fusion unit: fuses the flight data acquired by different sensors based on fusion algorithms; The first generation unit generates the flight path points and flight path of the UAV based on the fused data and predefined navigation rules; Comparison unit: Use the fused data to determine the distance between each adjacent path point, compare the length of each path according to the distance between each path point, and obtain the comparison result; The second acquisition unit: according to the comparison result, based on the obstacle avoidance algorithm, the optimal route of the UAV is obtained by minimizing the path length and the time to avoid obstacles.

4. The UAV route visualization management system according to claim 1 is characterized in that: Dynamic adjustment modules, including: The third acquisition unit: acquires the real-time surrounding environment parameters of the target UAV according to sensors related to environmental perception; Identification and filtering unit: identifying and filtering the surrounding environment parameters to obtain key environmental parameters; Adjustment unit: adjusts the flight mode and safety parameters of the drone based on the heuristic algorithm according to the pre-set destination information and current environmental conditions; Dynamic adjustment unit: dynamically adjust the optimal route of the drone based on the adjustment results.

5. The UAV route visualization management system according to claim 1 is characterized in that: Display module, including: A second determination unit: obtaining an adjusted flight trajectory of the UAV according to the fuel consumption and time delay of the UAV, and determining the position information of the UAV according to the flight trajectory; The second generation unit is used to obtain real-time changes in meteorological conditions and generate real-time UAV mission planning in combination with the position information of the UAV; Display unit: Generate a visual map based on GIS technology according to the UAV mission planning for visual display and update in real time; The fourth acquisition unit generates a real-time task scheduling suggestion according to the update result, and acquires the dynamic flight situation monitoring of the UAV according to the task scheduling suggestion.

6. The UAV route visualization management system according to claim 1 is characterized in that: Trigger module, including: The fifth acquisition unit: acquires the performance data and restriction parameters of the drone according to the drone document; A sixth acquisition unit: acquiring real-time environmental condition parameters of the UAV according to multiple devices of the UAV; A third determination unit: establishing a model based on a machine learning algorithm according to the performance parameters of the UAV and the real-time environmental condition parameters to determine the optimal flight parameters of the UAV; Setting unit: setting a safety threshold for the flight of the UAV based on the optimal flight parameters of the UAV and the dynamic flight situation monitoring of the UAV; A judgment unit: judging the real-time flight status and real-time flight parameters of the UAV according to the safety threshold of the UAV flight; Extraction unit: If the judgment result exceeds the safety threshold, an alarm is triggered, key feature information in the alarm information is extracted, and visual management of the UAV route is achieved based on the key feature information.

7. The UAV route visualization management system according to claim 1, characterized in that: Also includes: Query module: determine the corresponding operation interface according to the user's needs and usage habits, and conduct multi-angle and multi-form queries based on the operation interface; Permission authentication module: obtains the identity information of the querying user, performs permission authentication based on the identity information, and determines whether the user is an internal user of the data access object based on the authentication result. If not, obtains the external user access security policy in the data access scenario; The second determination module: determines the data description parameters within the user's access permission range according to the external user access security policy; Retrieval module: retrieves relevant permission data from the data repository of the data access object according to the data description parameters and the type of data to be retrieved by the user.

8. The UAV route visualization management system according to claim 6, characterized in that: Setting unit, comprising: The first determination subunit: obtains the flight area review parameters of the UAV, and determines the macro flight situation index set and the micro flight situation index set of the UAV according to the review parameters; Generating subunit: generating the flight point sequence of the UAV based on the UAV's macroscopic flight situation index set and microscopic flight situation index set according to the optimal flight parameters of the UAV; The first acquisition subunit: maps the UAV's mapped flight point sequence to obtain the UAV's flight status heat map; The second determination subunit: determines the flight altitude and flight attitude information of the UAV according to the flight status thermal map; The third determination subunit determines the flight threat source information and the flight power source information of the UAV based on the flight altitude information and the flight attitude information combined with the environmental parameter information of the flight area; Establish subunits: establish threat situation quantification matrix and power situation quantification matrix according to flight threat source information and flight power source information; The fourth determination subunit: determines multiple flight decision indicators and specific indicator reference values ​​through the threat situation quantification matrix and the power situation quantification matrix; Setting subunit: Setting the safety threshold of UAV flight based on flight decision indicators and specific indicator reference values.

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