A management platform for low-altitude drones

Abstract

The present invention relates to the field of unmanned aerial vehicle management technology, and in particular to a management platform for low-altitude unmanned aerial vehicles. In order to solve the problem that the effectiveness of terrain data monitoring and the flight safety of low-altitude unmanned aerial vehicles in the prior art are difficult to ensure; the present invention is provided with a route management module to optimize the flight route of low-altitude unmanned aerial vehicles, a terrain feature monitoring module to identify terrain features, a dynamic obstacle recognition module to identify and avoid dynamic obstacles in real time in the survey area, an environmental adaptation module to dynamically adjust the flight parameters of low-altitude unmanned aerial vehicles, a task switching module to manage and switch the terrain information of low-altitude unmanned aerial vehicles that is being executed or not yet executed, a data integration module to integrate terrain information, a resource scheduling module to coordinate the collaborative operation of multiple unmanned aerial vehicles, and a user interface to provide a visual operation interface. The present invention not only greatly improves the efficiency of terrain surveys and reduces manual input, but also improves the accuracy of data collection and provides more accurate terrain information support.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle management, and in particular to a management platform for low-altitude unmanned aerial vehicles. Background Art

[0002] In traditional terrain surveys, regional monitoring and terrain analysis mainly rely on manual field surveys and fixed equipment, such as surveying instruments and manual patrols. This method is not only inefficient, but also often limits the timeliness and accuracy of information. With the development of science and technology, drone technology has gradually been introduced into the field of terrain surveys as an emerging intelligent management tool.

[0003] At present, most drones are mainly focused on data collection in terrain surveys. However, most existing drone management systems lack a comprehensive integrated management system and are unable to optimize flight paths, perform dynamic obstacle identification, and adjust environmental adaptability. This makes it difficult to ensure the effectiveness of terrain data monitoring and the flight safety of low-altitude drones in complex terrain environments.

[0004] Therefore, there is an urgent need to develop a management platform for low-altitude UAVs to overcome the shortcomings of the existing technology. Summary of the invention

[0005] In order to solve the problem that the effectiveness of terrain data monitoring and the flight safety of low-altitude UAVs in the prior art are difficult to ensure, the present invention provides such a low-altitude UAV management platform, including a route management module, a terrain feature monitoring module, a dynamic obstacle recognition module, an environment adaptation module, a task switching module, a data integration module, a resource scheduling module and a user interface;

[0006] The route management module is used to formulate, monitor and optimize the flight route of the low-altitude UAV;

[0007] The terrain feature monitoring module is used to identify and analyze terrain features, landform changes and surface cover types;

[0008] The dynamic obstacle recognition module is used to recognize and avoid dynamic obstacles in the inspection area in real time;

[0009] The environmental adaptation module is used to dynamically adjust the flight parameters of the low-altitude UAV according to the current environmental conditions of the inspection area;

[0010] The task switching module is used to switch the terrain survey task of the low-altitude UAV in different terrain information to ensure that the low-altitude UAV completes the requirements of multiple terrain survey tasks;

[0011] The data integration module is used to integrate terrain information and provide decision support for terrain survey activities;

[0012] The resource scheduling module is used to coordinate the collaborative operation of multiple low-altitude drones and optimize resource allocation and management efficiency;

[0013] The user interface is used to provide a visual operation interface, simplify platform operation and management processes, and support daily use by terrain survey personnel.

[0014] Furthermore, the route management module formulates, monitors and optimizes the flight route of the low-altitude UAV, specifically including:

[0015] The scope of the survey area is obtained through the data integration module, and the survey area is divided into a plurality of sub-areas; the sub-areas are set with terrain type, geomorphic features and geological condition information;

[0016] For the sub-region, based on the area, shape and terrain, an optimal flight route for the sub-region is generated based on the D* algorithm and the genetic algorithm;

[0017] During the actual flight of the low-altitude UAV, the position and heading of the low-altitude UAV are monitored in real time and compared with the predetermined route;

[0018] The scheduled flight route is optimized regularly based on the actual flight data of the low-altitude UAV and combined with the terrain monitoring data in the terrain feature monitoring module.

[0019] Furthermore, dividing the inspection area into a plurality of sub-areas specifically includes:

[0020] Acquiring geospatial data and environmental data of the survey area through the data integration module;

[0021] The entire survey area is preliminarily gridded at a large scale based on the geographic information system to identify the overall outline and distribution of the survey area. The large scale is a grid of 100 meters by 100 meters.

[0022] Irregular boundaries of the survey area are identified through boundary detection algorithms. Based on the identification results of irregular boundaries, the large-scale grid is adjusted to a 50m × 50m grid, and the irregular boundaries are refined into smaller-sized grids.

[0023] Extract characteristic indicators for each grid cell, including terrain type, geomorphic features and land cover type;

[0024] Classify the weight of each characteristic index and classify the grid units by clustering algorithm;

[0025] Based on the classification results of the grid cells, adjacent grid cells are merged to form a continuous sub-region;

[0026] During the merging process of the grid units, it is determined whether the formed sub-area exceeds the maximum merged unit area threshold. If yes, the merging of the grid units is stopped and the next merging of the grid units is started until all the grid units are merged.

[0027] Furthermore, the terrain feature monitoring module identifies and analyzes terrain features, landform changes and surface cover types, specifically including:

[0028] By equipping the low-altitude UAV with a multispectral camera and a laser radar, the ground surface in different bands is imaged and measured, the terrain undulation index is calculated, and the terrain characteristics and landform changes are evaluated; the ground cover type is identified through an image recognition algorithm; and a three-dimensional terrain model is generated through data fusion;

[0029] Based on geographic information systems and historical terrain data, clustering algorithms are used to analyze terrain features, landform changes, and land cover types to identify key areas with anomalies or changes;

[0030] The analysis results are compared with historical data to generate a terrain change report, which is provided to terrain survey personnel through the user interface.

[0031] Furthermore, the dynamic obstacle recognition module recognizes and avoids dynamic obstacles in real time in the inspection area, specifically including:

[0032] The low-altitude drone is equipped with a variety of sensors for acquiring real-time three-dimensional information of the survey area;

[0033] The dynamic obstacle recognition module performs target detection based on the data acquired by the sensor, identifies dynamic obstacles in the inspection area, and uses Kalman filtering to track the dynamic obstacles in real time and predict the movement trajectory of the dynamic obstacles;

[0034] Based on the motion trajectory of the dynamic obstacle and the predetermined route provided by the route management module, a path planning algorithm is used to perform path planning to generate an obstacle avoidance route;

[0035] During the actual flight of the low-altitude UAV, the motion state of the dynamic obstacle is monitored in real time, and the obstacle avoidance route is adjusted according to the motion trajectory of the dynamic obstacle;

[0036] The dynamic obstacle recognition module also sets a safety distance threshold according to the moving direction and speed of the dynamic obstacle. When the distance between the low-altitude UAV and the dynamic obstacle is less than the safety distance threshold, the low-altitude UAV is controlled to take obstacle avoidance measures.

[0037] Furthermore, the environmental adaptation module dynamically adjusts the flight parameters of the low-altitude UAV specifically including:

[0038] The environmental adaptation module obtains the current meteorological data of the survey area in real time through the sensors installed on the low-altitude UAV and the ground meteorological station;

[0039] The environmental adaptation module inputs the current meteorological data into the pre-trained environmental impact model, determines the impact of the current weather on the low-altitude UAV performing the terrain survey task, and selects a suitable operation mode according to the determination result;

[0040] Based on the judgment result of the environmental impact model and the selection result of the operation mode, the flight parameters of the low-altitude UAV are dynamically adjusted, and the flight parameters include flight altitude, speed and route.

[0041] Furthermore, the environmental impact model is constructed based on a machine learning algorithm, taking the current meteorological data as input to obtain the predicted task impact value , including task efficiency rating and flight stability rating ;

[0042] Based on the task impact value , dynamically adjust the flight parameters of the low-altitude UAV, wherein the mission efficiency is adjusted as follows:

[0043]

[0044] The adjustment of the flight stability is:

[0045]

[0046] in, is the adjusted efficiency of the task, is the efficiency of the task under normal operating conditions, To determine the efficiency of the task Changes in task efficiency ratings The sensitivity adjustment factor is Rate the task efficiency, Set a benchmark value for task efficiency scoring; is the flight stability after adjustment, For the stated flight stability set under normal operating conditions, For determining the flight stability Scoring flight stability changes The adjustment factor of the response strength, Score the flight stability, The flight stability score benchmark value is set;

[0047] The environmental adaptation module adjusts the flight altitude, speed and route of the low-altitude UAV accordingly according to the adjusted mission efficiency and flight stability, so as to ensure the effective execution and flight safety of the low-altitude UAV when performing the terrain survey mission.

[0048] Furthermore, the task switching module ensures that the low-altitude UAV completes the requirements of the various terrain survey tasks, including:

[0049] The task switching module generates the terrain survey task based on the monitoring results of the terrain feature monitoring module and the environment adaptation module; classifies the terrain survey task and sets the task objectives, priorities and required resources;

[0050] The task switching module stores the terrain survey tasks that have been generated and are to be executed in a terrain information library that is updated in real time, and dynamically adjusts the priority of the terrain survey tasks according to changes in the environment and terrain characteristics;

[0051] The task switching module monitors the status of the low-altitude UAV in real time and determines whether to adjust the task parameters and execution strategy.

[0052] Furthermore, the task switching module determines whether to adjust the task parameters and execution strategy specifically including:

[0053] The task switching module sets key monitoring indicators, which include the battery power, flight altitude and speed, current environmental conditions, terrain change monitoring results, and the priority and predicted completion time of the established terrain survey task of the low-altitude UAV;

[0054] A dynamic evaluation model is established based on a machine learning algorithm to conduct a comprehensive analysis of the key monitoring indicators, including whether the low-altitude UAV can safely complete the current task, the impact of the current environmental conditions on the terrain survey task, and whether the terrain survey task needs to be re-prioritized;

[0055] Based on the analysis results of the dynamic evaluation model, it is determined whether the task parameters and execution strategy need to be adjusted through preset judgment criteria, wherein the judgment criteria include whether the task completion time threshold, battery power critical value or environmental condition change threshold is exceeded;

[0056] When one of the analysis contents does not meet the judgment criteria, adjust the task parameters or execution strategy;

[0057] After the adjustment is completed, the new execution results are compared with the preset goals to obtain feedback on the adjustment effect, and the evaluation criteria and adjustment strategies are optimized.

[0058] Furthermore, the resource scheduling module coordinates the collaborative operation of the multiple low-altitude drones, specifically including:

[0059] The resource scheduling module obtains the requirements of the current different terrain survey tasks and the available status of the low-altitude UAV by integrating the real-time data of the terrain feature monitoring module, the environment adaptation module and the task switching module;

[0060] Based on the task objectives and priorities of the terrain survey tasks, a genetic algorithm is used to prioritize the terrain survey tasks;

[0061] When the terrain survey mission is performed in a complex terrain or environment beyond the normal area, the resource scheduling module generates a coordinated operation plan for multiple low-altitude UAVs according to the performance, safety distance and operation type of the low-altitude UAVs;

[0062] During the operation of the low-altitude UAV, the resource scheduling module monitors the complex terrain environment and the status of the low-altitude UAV in real time. When changes in external conditions are detected, the resource scheduling module adjusts the operation plan and resource allocation in combination with the evaluation information in the environmental adaptation module.

[0063] The beneficial effects of the present invention are:

[0064] 1. The module functions provided in the present invention can effectively plan the flight path of low-altitude UAVs, monitor environmental changes in real time, and avoid dynamic obstacles in time, ensuring that the UAVs can accurately and efficiently complete terrain survey tasks, which not only greatly improves the efficiency of terrain surveys and reduces manual input, but also improves the accuracy of data collection and provides more accurate terrain information support;

[0065] 2. The present invention maximizes the effectiveness of low-altitude UAVs in terrain surveys by combining a route management module with a terrain feature monitoring module. The route management module ensures that low-altitude UAVs achieve accurate flight coverage in a specific area. By real-time monitoring and optimizing scheduled routes, it ensures that low-altitude UAVs can efficiently patrol land and resource changes, identify geological anomalies, and obtain terrain feature data. The terrain feature monitoring module, which complements this, obtains terrain change indicator data in real time through advanced technologies such as multi-spectral cameras, which not only improves resource management efficiency, but also effectively reduces resource waste. It can discover and deal with potential geological problems in a relatively short period of time, thereby ensuring the sustainability of terrain surveys and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 is a flow chart of the method of the present invention;

[0067] Figure 2 Flow chart of dividing the investigation area into multiple sub-areas according to the present invention. DETAILED DESCRIPTION

[0068] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0069] As attached Figure 1 As shown, the present invention discloses a management platform for low-altitude UAVs, which specifically includes: a route management module, a terrain feature monitoring module, a dynamic obstacle recognition module, an environment adaptation module, a task switching module, a data integration module, a resource scheduling module and a user interface.

[0070] In this embodiment, the route management module is used to formulate, monitor and optimize the flight route of the low-altitude UAV to ensure that the low-altitude UAV has effective coverage in the predetermined area.

[0071] Specifically, the route management module ensures that low-altitude drones have effective coverage within the predetermined area, including:

[0072] The scope of the survey area is obtained through the data integration module, and the survey area is divided into multiple sub-areas; the sub-areas are set with terrain type, geomorphic features and geological conditions information.

[0073] Among them, as attached Figure 2 As shown, the route management module divides the inspection area into multiple sub-areas, including:

[0074] S101: Acquire geographic spatial data and environmental data of the survey area through a data integration module;

[0075] S102: Preliminary gridding of the entire survey area at a large scale based on the geographic information system to identify the overall outline and distribution of the survey area, with the large scale being a grid of 100 m × 100 m;

[0076] S103: Identify irregular boundaries of the survey area through a boundary detection algorithm, and based on the identification result of the irregular boundaries, adjust the large-scale grid to a grid of 50 meters × 50 meters, and refine the irregular boundaries into smaller-sized grids;

[0077] S104: extracting characteristic indicators for each grid cell, including terrain type, landform characteristics and surface cover type;

[0078] S105: classifying weights for each characteristic index, and classifying grid units through a clustering algorithm;

[0079] S106: Based on the classification results of the grid cells, adjacent grid cells are merged to form a continuous sub-region;

[0080] S107: During the process of merging the grid units, it is determined whether the formed sub-area exceeds the maximum merged unit area threshold. If yes, the merging of the grid units is stopped and the next grid unit is started, until all the grid units are merged.

[0081] For the divided sub-areas, according to the area, shape, terrain and other characteristics of the sub-areas, based on the D* algorithm and genetic algorithm, the sub-areas are divided into grids, and the optimal route is generated according to the distance between the grid points and the flight time to generate the optimal flight route for the sub-area.

[0082] During the actual flight of the low-altitude UAV, the position and heading of the low-altitude UAV are monitored in real time, compared with the planned route, and the deviation between the actual flight trajectory of the low-altitude UAV and the planned route is calculated, and an alarm is issued or the flight parameters are adjusted according to the size of the deviation.

[0083] Based on the actual flight data of low-altitude UAVs, combined with the terrain monitoring data in the terrain feature monitoring module, machine learning algorithms are used to regularly optimize the scheduled routes. The optimization goals include but are not limited to reducing flight distance, shortening flight time, improving survey efficiency, reducing survey costs, and improving survey accuracy.

[0084] After the terrain feature monitoring module detects a special terrain area and the task switching module generates a terrain survey task for the special terrain area, the route management module determines the location, area, features and other information of the special terrain area based on the task;

[0085] Based on this information, the route management module will further divide the special terrain area into multiple small grids. The size of each grid is dynamically adjusted according to the complexity of the terrain. The higher the complexity of the terrain, the smaller the grid.

[0086] For each small grid, the route management module will plan a flight route covering the grid. This route takes into account factors such as grid size, flight altitude and speed to ensure accurate inspection of the target area. For grids with more complex terrain, the route management module will arrange low-altitude UAVs to fly multiple times to ensure sufficient inspection. For grids with less complex terrain, the route management module will appropriately increase the flight altitude and speed of low-altitude UAVs to improve inspection efficiency.

[0087] When the low-altitude UAV is performing an inspection mission, the route management module will monitor the flight status and mission progress of the low-altitude UAV in real time; if it detects that the terrain features of a certain grid have changed, the route management module will dynamically adjust the flight route and parameters of the grid according to the changes to ensure the inspection effect; at the same time, the route management module will also adjust the flight route in real time according to the feedback from the dynamic obstacle recognition module to avoid collision accidents of low-altitude UAVs;

[0088] When the low-altitude UAV completes the survey mission, the route management module will evaluate the effectiveness of this operation, including but not limited to the survey coverage rate, terrain feature recognition accuracy, etc. Based on the evaluation results of this operation, when there are similar tasks, the route management module will adjust the route planning and parameter settings of the low-altitude UAV in the similar tasks to improve the survey efficiency and accuracy.

[0089] Through the above-mentioned plan planning for low-altitude UAVs in special terrain survey missions, the route management module can adopt accurate survey strategies according to the specific conditions of special terrain areas to ensure effective coverage of target areas and improve survey results; at the same time, the route management module also has the ability to implement monitoring and dynamic adjustment, and can cope with complex survey areas to ensure the flight safety of low-altitude UAVs. The same is true for other types of terrain survey missions and the plan planning for low-altitude UAVs in special terrain survey missions.

[0090] In this embodiment, the terrain feature monitoring module is used to identify and analyze data such as terrain features, landform changes, and surface cover types, so as to provide data support for accurate terrain surveys for low-altitude drones.

[0091] Specifically, the terrain feature monitoring module identifies and analyzes data such as terrain features, landform changes, and surface cover types, including:

[0092] By equipping low-altitude drones with multispectral cameras and lidars, the surface reflectance spectra and three-dimensional point cloud data in different bands are captured; the collected spectral data are processed using remote sensing image processing technology to calculate terrain indicators such as terrain undulation index, slope and aspect, and evaluate terrain characteristics and landform changes; at the same time, the collected surface images are analyzed through convolutional neural networks to identify surface cover types, which include but are not limited to equipment, water bodies, and buildings; finally, multispectral images and lidar point cloud data are combined to generate a high-precision three-dimensional terrain model.

[0093] The terrain feature monitoring module obtains the geographic information and historical terrain data of the survey area through the data integration module, and uses clustering algorithms such as K-means clustering analysis to analyze the terrain features, landform changes and surface cover types, and identify key areas with anomalies or changes, including but not limited to landslide areas, collapse areas and erosion areas.

[0094] The terrain feature monitoring module compares the analysis results with historical data, generates a terrain change report, and provides the terrain change report to terrain survey personnel through the user interface. The terrain change report includes detailed information on the terrain features, landform changes and surface cover types of each area, and assesses potential paper disaster risks.

[0095] In this embodiment, the dynamic obstacle recognition module is used to identify and avoid dynamic obstacles in the inspection area in real time to ensure the flight safety of the low-altitude UAV.

[0096] Specifically, the dynamic obstacle recognition module ensures the flight safety of low-altitude drones by:

[0097] Low-altitude drones are equipped with a variety of sensors including but not limited to depth cameras, lidars, and millimeter-wave radars, which are used to obtain real-time three-dimensional information of the survey area. Depth cameras are used to identify close obstacles, lidars are used to identify long-distance obstacles, and millimeter-wave radars are used to identify obstacles behind obstructions.

[0098] The dynamic obstacle recognition module performs target detection based on the data obtained by the sensor, identifies dynamic obstacles in the inspection area, and uses Kalman filtering to track dynamic obstacles in real time and predict the movement trajectory of dynamic obstacles. Dynamic obstacles include but are not limited to moving vehicles, people, and animals.

[0099] Based on the real-time detected obstacle information and the predicted motion trajectory, combined with the predetermined route provided by the route management module, the path planning algorithm is used for path planning to generate an obstacle avoidance route to ensure that the low-altitude drone passes through the obstacle area in the safest path.

[0100] During the actual flight of the low-altitude UAV, the movement status of dynamic obstacles is monitored in real time, and the obstacle avoidance route is adjusted according to the movement trajectory of the obstacles.

[0101] The dynamic obstacle recognition module also sets a safety distance threshold based on the moving direction and speed of the dynamic obstacle. When the distance between the low-altitude UAV and the dynamic obstacle is less than the safety distance threshold, the obstacle avoidance mechanism is triggered to adjust the low-altitude UAV's flight route or reduce the flight speed to ensure a safe distance.

[0102] When a dynamic obstacle is too close to a low-altitude drone or there is a potential risk of collision, the alarm mechanism is triggered to alert the operator or the dynamic obstacle to avoid accidents to the greatest extent possible.

[0103] In this embodiment, the environmental adaptation module is used to dynamically adjust the flight parameters of the low-altitude UAV according to the current environmental conditions of the survey area to ensure the accuracy of the low-altitude UAV in the terrain survey mission.

[0104] Specifically, the environmental adaptation module dynamically adjusts the flight parameters of the low-altitude UAV, including:

[0105] The environmental adaptation module obtains the current meteorological data of the survey area in real time through sensors installed in low-altitude drones and the survey area, including but not limited to temperature, wind speed and direction, and humidity. These meteorological factors will affect the flight stability, sensor performance, and data collection quality of low-altitude drones.

[0106] The environmental adaptation module inputs the current meteorological data into the pre-trained environmental impact model to determine the impact of the current weather on the low-altitude UAV's terrain survey mission, and selects the appropriate operation mode based on the judgment results.

[0107] The environmental impact model is built based on machine learning algorithms, including but not limited to random forests and support vector machines. The environmental impact model learns the relationship between historical meteorological data and low-altitude UAV mission efficiency and flight stability, and uses current meteorological data as input to obtain the predicted mission impact value. , including task efficiency rating and flight stability rating ;

[0108] Based on the mission impact value Y, the flight parameters of the UAV are dynamically adjusted, and the mission efficiency is adjusted to:

[0109]

[0110] Flight stability has been adjusted to:

[0111]

[0112] in, is the adjusted task efficiency, For mission efficiency set under normal operating conditions, To determine task efficiency Changes in task efficiency ratings The sensitivity adjustment factor is Rate the task efficiency, Set a benchmark value for task efficiency scoring; For the adjusted flight stability, To set the flight stability according to normal operating conditions, To determine flight stability Scoring flight stability changes The adjustment factor of the response strength, Score the flight stability, It is the benchmark value for setting flight stability score.

[0113] The environmental adaptation module adjusts the flight altitude, speed and route of the low-altitude UAV according to the adjusted mission efficiency and flight stability, ensuring the effective execution and flight safety of the low-altitude UAV when performing terrain survey missions.

[0114] By combining meteorological data and machine learning algorithms to learn trends and patterns in historical data, the environmental impact model can provide more accurate mission efficiency and flight stability assessments. It not only improves the responsiveness of low-altitude UAV operations in complex meteorological environments, but also improves the operational efficiency and safety of the low-altitude UAV management platform.

[0115] Based on the judgment results of the environmental impact model and the selection results of the mission mode, the flight parameters of the low-altitude UAV are dynamically adjusted to ensure that the low-altitude UAV can maintain a high degree of flight accuracy and stability in complex and changeable terrain environments; among which, flight parameter adjustments include but are not limited to flight altitude adjustment, flight speed adjustment and sensor parameter adjustment; sensor parameter adjustment includes dynamically adjusting the sensor's sampling frequency, resolution, sensitivity and other parameters according to environmental conditions to ensure high-quality terrain data in different environments.

[0116] In this embodiment, the task switching module is used to switch the terrain survey task of the low-altitude UAV in different terrain information to ensure that the low-altitude UAV can complete the requirements of various terrain survey tasks.

[0117] Specifically, the task switching module ensures that low-altitude UAVs can complete various terrain survey tasks, including:

[0118] The task switching module generates terrain survey tasks based on the monitoring results of the terrain feature monitoring module and the environmental adaptation module; classifies the terrain survey tasks and sets task objectives, priorities and required resources.

[0119] The task switching module stores the generated and pending terrain survey tasks in a real-time updated terrain information library, and dynamically adjusts the priority of terrain survey tasks according to environmental changes and terrain characteristics. The terrain information library is a database that stores all executable or completed terrain survey tasks, and each terrain survey task includes but is not limited to information such as task name, task parameters, task execution process, and task execution conditions.

[0120] The task switching module monitors the status and environmental changes of the low-altitude UAV in real time. If the low-altitude UAV completes its current terrain survey mission or encounters an emergency during the mission completion, the task switching module evaluates the current execution conditions of the low-altitude UAV and determines whether to adjust the mission parameters and execution strategy.

[0121] Specifically, the task switching module determines whether to adjust the task parameters and execution strategy, including:

[0122] The task switching module sets key monitoring indicators, which include but are not limited to the battery power of the low-altitude UAV, flight altitude and speed, current environmental conditions, terrain feature monitoring results, and the terrain's task priority and predicted completion time.

[0123] A dynamic evaluation model is established based on the machine learning algorithm to conduct a comprehensive analysis of key monitoring indicators, including reliability assessment, environmental adaptability assessment and mission effectiveness assessment. The reliability assessment is to determine whether the low-altitude UAV can safely complete the current task by analyzing the battery power and flight status. The environmental adaptability assessment is to evaluate the impact of current environmental conditions on the terrain survey task based on the data of the environmental adaptation module. The mission effectiveness assessment is to determine whether the terrain survey task needs to be re-prioritized by analyzing the comparison between the progress of the terrain survey task and the expected goals.

[0124] After obtaining the analysis results of the dynamic evaluation model, the preset judgment criteria are used to decide whether the task parameters and execution strategies need to be adjusted. The judgment criteria include whether the task completion time threshold, battery power critical value or environmental condition change threshold is exceeded.

[0125] When one of the analysis contents does not meet the judgment criteria, adjust the mission parameters or execution strategy. Adjusting the mission parameters includes but is not limited to modifying the operation area or time, adjusting the flight altitude and speed, and optimizing the flight path.

[0126] After the adjustment is completed, the new execution results are compared with the preset targets to obtain feedback on the adjustment effects, based on which the evaluation criteria and adjustment strategies are optimized.

[0127] In this embodiment, the data integration module is used to integrate terrain information and provide decision support for low-altitude UAVs to carry out terrain survey activities.

[0128] Specifically, the data integration module is connected to data sources related to terrain surveys through interfaces, including but not limited to data sources such as meteorological monitoring stations, historical terrain data, and geological information systems; through a series of preprocessing operations such as data cleaning, data format conversion, and data standardization, data from different sources are converted into a unified data structure.

[0129] At the same time, the data integration module integrates terrain information from different data sources, including but not limited to terrain features, geological structures, and hydrological information; it uses data mining and machine learning algorithms to extract valuable information and patterns from the integrated data. Based on the integration and analysis results, it generates terrain survey suggestions, including but not limited to the best survey route, key areas of concern, and potential risk areas.

[0130] In this embodiment, the resource scheduling module is used to coordinate the collaborative operations of multiple drones and optimize resource allocation and management efficiency.

[0131] Specifically, the resource scheduling module coordinates the collaborative operations of multiple low-altitude drones, including:

[0132] The resource scheduling module obtains the current requirements for different terrain survey tasks and the available status of low-altitude UAVs by integrating the real-time data of the terrain feature monitoring module, the environment adaptation module and the task switching module.

[0133] Based on the mission objectives and priorities of terrain survey tasks, a genetic algorithm is used to dynamically allocate terrain survey tasks, and resources including but not limited to low-altitude drones, operation time and other related equipment are preferentially allocated to areas with high mission urgency or great impact.

[0134] When the terrain survey mission is performed in a larger survey area or a complex environment, the resource scheduling module divides the operation area into multiple coverage areas according to the performance, safety distance and operation type of the low-altitude UAV, and formulates the specific tasks and routes of each low-altitude UAV through a collaborative algorithm, and generates a coordinated operation plan for multiple low-altitude UAVs, so as to maximize the use of working time, reduce repeated flights, and thus improve the overall mission efficiency.

[0135] During the low-altitude UAV operation, the resource scheduling module monitors the status of the survey area and the low-altitude UAV in real time. When changes in external conditions, including but not limited to bad weather, technical failures or terrain, are detected, the operation plan and resource allocation are adjusted in combination with the evaluation information in the environmental adaptation module.

[0136] At the same time, the resource scheduling module collects and analyzes resource usage data during different operations, uses machine learning algorithms to establish a resource efficiency evaluation model, and regularly evaluates the mission efficiency, rationality of resource allocation, and mission degree of low-altitude UAVs to optimize future resource allocation decisions, thereby forming a closed-loop feedback mechanism and continuously improving the management and scheduling strategies of low-altitude UAVs.

[0137] In this embodiment, the user interface is used to provide a visual operation interface to facilitate terrain survey personnel to view data analysis results, including but not limited to terrain feature maps, geological risk maps, and surface cover type distribution maps. At the same time, the user interface also provides an interactive operation interface for data query and analysis, simplifies platform operation and management processes, and supports daily use by terrain survey personnel.

[0138] The above-described embodiments only express the preferred implementation modes of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. It should be pointed out that, for those of ordinary skill in the art, several modifications, improvements and substitutions can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A low-altitude UAV management platform, characterized in that: It includes: route management module, terrain feature monitoring module, dynamic obstacle recognition module, environment adaptation module, task switching module, data integration module, resource scheduling module and user interface; The route management module is used to formulate, monitor and optimize the flight route of the low-altitude UAV; The terrain feature monitoring module is used to identify and analyze terrain features, landform changes and surface cover types; The dynamic obstacle recognition module is used to recognize and avoid dynamic obstacles in the inspection area in real time; The environmental adaptation module is used to dynamically adjust the flight parameters of the low-altitude UAV according to the current environmental conditions of the inspection area; The task switching module is used to switch the terrain survey task of the low-altitude UAV in different terrain information to ensure that the low-altitude UAV completes the requirements of multiple terrain survey tasks; The data integration module is used to integrate terrain information and provide decision support for terrain survey activities; The resource scheduling module is used to coordinate the collaborative operation of multiple low-altitude drones and optimize resource allocation and management efficiency; The user interface is used to provide a visual operation interface, simplify the platform operation and management process, and support the daily use of terrain survey personnel; The route management module formulates, monitors and optimizes the flight route of the low-altitude UAV, specifically including: The scope of the survey area is obtained through the data integration module, and the survey area is divided into a plurality of sub-areas; the sub-areas are set with terrain type, geomorphic features and geological condition information; For the sub-region, based on the area, shape and terrain, an optimal flight route for the sub-region is generated based on the D* algorithm and the genetic algorithm; During the actual flight of the low-altitude UAV, the position and heading of the low-altitude UAV are monitored in real time and compared with the predetermined route; Regularly optimize the scheduled flight route based on the actual flight data of the low-altitude UAV and the terrain monitoring data in the terrain feature monitoring module; The said dividing the inspection area into a plurality of sub-areas specifically comprises: Acquiring geospatial data and environmental data of the survey area through the data integration module; The entire survey area is preliminarily gridded at a large scale based on the geographic information system to identify the overall outline and distribution of the survey area. The large scale is a grid of 100 meters by 100 meters. Irregular boundaries of the survey area are identified through boundary detection algorithms. Based on the identification results of irregular boundaries, the large-scale grid is adjusted to a 50m × 50m grid, and the irregular boundaries are refined into smaller-sized grids. Extract characteristic indicators for each grid cell, including terrain type, geomorphic features and land cover type; Classify the weight of each characteristic index and classify the grid units by clustering algorithm; Based on the classification results of the grid cells, adjacent grid cells are merged to form a continuous sub-region; During the merging of the grid units, it is determined whether the formed sub-area exceeds the maximum merged unit area threshold, if yes, the merging of the grid units is stopped, and the next merging of the grid units is started, until all the grid units are merged; The terrain feature monitoring module identifies and analyzes terrain features, landform changes and surface cover types, including: By equipping the low-altitude UAV with a multispectral camera and a laser radar, the ground surface in different bands is imaged and measured, the terrain undulation index is calculated, and the terrain characteristics and landform changes are evaluated; the ground cover type is identified through an image recognition algorithm; and a three-dimensional terrain model is generated through data fusion; Based on geographic information systems and historical terrain data, clustering algorithms are used to analyze terrain features, landform changes, and land cover types to identify key areas with anomalies or changes; Compare the analysis results with historical data to generate a terrain change report, which is provided to terrain survey personnel through the user interface; The dynamic obstacle recognition module recognizes and avoids dynamic obstacles in real time in the inspection area, specifically including: The low-altitude drone is equipped with a variety of sensors for acquiring real-time three-dimensional information of the survey area; The dynamic obstacle recognition module performs target detection based on the data acquired by the sensor, identifies dynamic obstacles in the inspection area, and uses Kalman filtering to track the dynamic obstacles in real time and predict the movement trajectory of the dynamic obstacles; Based on the motion trajectory of the dynamic obstacle and the predetermined route provided by the route management module, a path planning algorithm is used to perform path planning to generate an obstacle avoidance route; During the actual flight of the low-altitude UAV, the motion state of the dynamic obstacle is monitored in real time, and the obstacle avoidance route is adjusted according to the motion trajectory of the dynamic obstacle; The dynamic obstacle recognition module also sets a safety distance threshold according to the moving direction and speed of the dynamic obstacle, and when the distance between the low-altitude UAV and the dynamic obstacle is less than the safety distance threshold, the low-altitude UAV is controlled to take obstacle avoidance measures; The environmental adaptation module dynamically adjusts the flight parameters of the low-altitude UAV specifically including: The environmental adaptation module obtains the current meteorological data of the survey area in real time through the sensors installed on the low-altitude UAV and the ground meteorological station; The environmental adaptation module inputs the current meteorological data into the pre-trained environmental impact model, determines the impact of the current weather on the low-altitude UAV performing the terrain survey task, and selects a suitable operation mode according to the determination result; Based on the judgment result of the environmental impact model and the selection result of the operation mode, dynamically adjust the flight parameters of the low-altitude UAV, wherein the flight parameters include flight altitude, speed and route; The environmental impact model is built based on a machine learning algorithm, taking the current meteorological data as input to obtain the predicted task impact value. , including task efficiency rating and flight stability rating ; Based on the task impact value , dynamically adjust the flight parameters of the low-altitude UAV, wherein the mission efficiency is adjusted as follows: The adjustment of the flight stability is: in, is the adjusted efficiency of the task, is the efficiency of the task under normal operating conditions, To determine the efficiency of the task Changes in task efficiency ratings The sensitivity adjustment factor is Rate the task efficiency, Set a benchmark value for task efficiency scoring; is the flight stability after adjustment, For the stated flight stability set under normal operating conditions, For determining the flight stability Scoring flight stability changes The adjustment factor of the response strength, Score the flight stability, The flight stability score benchmark value is set; The environmental adaptation module adjusts the flight altitude, speed and route of the low-altitude UAV accordingly according to the adjusted mission efficiency and flight stability, so as to ensure the effective execution and flight safety of the low-altitude UAV when performing the terrain survey mission.

2. A low-altitude UAV management platform according to claim 1, characterized in that: The task switching module ensures that the low-altitude UAV completes the requirements of the various terrain survey tasks, including: The task switching module generates the terrain survey task based on the monitoring results of the terrain feature monitoring module and the environment adaptation module; classifies the terrain survey task and sets the task objectives, priorities and required resources; The task switching module stores the terrain survey tasks that have been generated and are to be executed in a terrain information library that is updated in real time, and dynamically adjusts the priority of the terrain survey tasks according to changes in the environment and terrain characteristics; The task switching module monitors the status of the low-altitude UAV in real time and determines whether to adjust the task parameters and execution strategy.

3. A low-altitude UAV management platform according to claim 2, characterized in that: The task switching module determines whether to adjust the task parameters and execution strategy specifically including: The task switching module sets key monitoring indicators, which include the battery power, flight altitude and speed, current environmental conditions, terrain change monitoring results, and the priority and predicted completion time of the established terrain survey task of the low-altitude UAV; A dynamic evaluation model is established based on a machine learning algorithm to conduct a comprehensive analysis of the key monitoring indicators, including whether the low-altitude UAV can safely complete the current task, the impact of the current environmental conditions on the terrain survey task, and whether the terrain survey task needs to be re-prioritized; Based on the analysis results of the dynamic evaluation model, it is determined whether the task parameters and execution strategy need to be adjusted through preset judgment criteria, wherein the judgment criteria include whether the task completion time threshold, battery power critical value or environmental condition change threshold is exceeded; When one of the analysis contents does not meet the judgment criteria, adjust the task parameters or execution strategy; After the adjustment is completed, the new execution results are compared with the preset goals to obtain feedback on the adjustment effect, and the evaluation criteria and adjustment strategies are optimized.

4. A low-altitude UAV management platform according to claim 1, characterized in that: The resource scheduling module coordinates the collaborative operation of the multiple low-altitude UAVs, specifically including: The resource scheduling module obtains the requirements of the current different terrain survey tasks and the available status of the low-altitude UAV by integrating the real-time data of the terrain feature monitoring module, the environment adaptation module and the task switching module; Based on the task objectives and priorities of the terrain survey tasks, a genetic algorithm is used to prioritize the terrain survey tasks; When the terrain survey mission is performed in a complex terrain or environment beyond the normal area, the resource scheduling module generates a coordinated operation plan for multiple low-altitude UAVs according to the performance, safety distance and operation type of the low-altitude UAVs; During the operation of the low-altitude UAV, the resource scheduling module monitors the complex terrain environment and the status of the low-altitude UAV in real time. When changes in external conditions are detected, the resource scheduling module adjusts the operation plan and resource allocation in combination with the evaluation information in the environmental adaptation module.

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