Real-time acquisition method and system for surveying and mapping operation data in severe weather

Abstract

A real-time acquisition method and system for surveying and mapping operation data in severe weather relates to the field of surveying and mapping operation, and the method comprises the following steps: acquiring weather information of a target area; matching a data acquisition tool for surveying and mapping operation according to the weather information; determining the number of unmanned aerial vehicles and a first flight layout according to the area of the target region; in the real-time collection process of the surveying and mapping operation data, if it is detected that the unmanned aerial vehicle at the first position is abnormal, the area of an undetected area in the target area is obtained; adjusting the layout of the unmanned aerial vehicle at a second position according to the area of the undetected region to obtain a second flight layout; and controlling the unmanned aerial vehicle to continuously collect surveying and mapping operation data of the target area according to the second flight layout. By implementing the method, the accuracy and reliability of surveying and mapping operation data acquisition of the target area can be improved under severe weather conditions.

Description

Technical Field

[0001] The present application relates to the field of surveying and mapping operations, and in particular to a method and system for real-time collection of surveying and mapping operation data under severe weather conditions. Background Art

[0002] In severe weather such as snowstorms, heavy rains, and strong winds, in order to monitor the occurrence of natural disasters such as mudslides or landslides in real time, it is necessary to monitor target areas prone to natural disasters. Obtaining surveying and mapping data in target areas can better respond to emergencies, ensure safety, and provide high-quality data support for various decision-making and research work.

[0003] In related technologies, in extremely bad weather, in order to ensure the safety of personnel and improve the efficiency of data collection in surveying and mapping operations, drones equipped with various data collection tools are generally used for data collection.

[0004] However, traditional drone mapping methods are easily affected by the environment, and the accuracy and reliability of data collection are difficult to guarantee. In some cases, the mapping equipment may even fail. Summary of the invention

[0005] The present application provides a method and system for real-time acquisition of surveying and mapping operation data under severe weather conditions, which are used to improve the accuracy and reliability of surveying and mapping operation data acquisition for a target area under severe weather conditions.

[0006] In a first aspect, the present application provides a method for real-time collection of surveying and mapping operation data in severe weather, which is applied to a surveying and mapping operation data collection system, and the method comprises: Obtaining weather information for a target area, which is a geographical area for which surveying and mapping data collection is to be performed; According to the weather information, a data collection tool for surveying and mapping operations is matched, and the data collection tool is carried on the drone; Determining the number of drones and a first flight layout according to the area of ​​the target area, the number of drones being proportional to the area, the first flight layout being composed of the drones at the first position and the drones at the second position; During the real-time collection of surveying and mapping operation data, if an abnormality is detected in the drone at the first position, the area of ​​the undetected region in the target area is obtained; Adjusting the layout of the UAVs at the second position according to the area of ​​the undetected region to obtain a second flight layout; The UAV is controlled to continue collecting surveying and mapping data of the target area according to the second flight layout.

[0007] Through the above embodiments, the surveying and mapping operation data acquisition system improves the adaptability of surveying and mapping operations in bad weather by obtaining weather information of the target area and selecting appropriate data acquisition tools according to weather conditions. At the same time, the number of drones and flight layout are flexibly adjusted according to the area of ​​the target area, which not only ensures the surveying and mapping coverage but also improves efficiency. During the operation, if an abnormal situation is detected, the method can adjust the flight layout in real time to ensure the continuity and integrity of the surveying and mapping task. This dynamic adjustment mechanism greatly enhances the robustness of the surveying and mapping system, and can ensure the reliability and accuracy of the surveying and mapping data even under complex and changeable bad weather conditions.

[0008] In some embodiments, after the step of determining the number of drones and the first flight layout according to the area of ​​the target area, the method further includes: Obtain the positioning information sent by each drone in real time; Determining a predicted position of an adjacent UAV based on the first flight configuration and the positioning information; If it is detected that the predicted position does not match the positioning information of the corresponding drone, a positioning abnormality warning is issued.

[0009] Through the above embodiments, the surveying and mapping operation data acquisition system can timely detect the positioning anomaly of the drone by acquiring the positioning information of each drone in real time and comparing it with the preset flight layout. This real-time monitoring mechanism greatly improves the safety and reliability of the surveying and mapping system. By predicting the positions of adjacent drones and comparing them, the method can quickly detect the problem as soon as the positioning anomaly occurs, so that there is enough time to take corrective measures to avoid serious consequences such as data collection deviation or drone collision caused by positioning errors.

[0010] In some embodiments, before the step of determining the predicted position of the adjacent UAV according to the first flight configuration and the positioning information, the method further includes: During the flight of the drone, the distance between adjacent drones is monitored in real time; If it is detected that the distance value exceeds the preset deviation value, the flight trajectory of the drone is corrected.

[0011] Through the above embodiments, the surveying and mapping operation data acquisition system effectively improves the accuracy and safety of multi-UAV collaborative operations by monitoring the distance between adjacent UAVs in real time and correcting the flight trajectory when the distance is abnormal. In severe weather conditions, UAVs are easily affected by factors such as strong winds and deviate from the predetermined trajectory. By continuously monitoring and adjusting the distance between UAVs, this method can maintain the best surveying and mapping coverage effect and avoid repeated collection or missing areas. At the same time, maintaining appropriate UAV spacing can also reduce the risk of collision and improve system safety.

[0012] In some embodiments, after the step of issuing a positioning abnormality warning if it is detected that the predicted position does not match the positioning information of the corresponding drone, the method further includes: If it is detected that all predicted positions do not match the positioning information of the corresponding drone, the signal strength of multiple positioning systems is detected; Use the positioning system with the strongest signal strength to re-match the predicted position with the positioning information of the corresponding drone.

[0013] Through the above embodiments, the surveying and mapping data acquisition system detects the signal strength of multiple positioning systems and selects the system with the strongest signal for positioning matching, which effectively improves the accuracy and reliability of drone positioning in bad weather. Under extreme weather conditions, a single positioning system may be interfered with or signal attenuated, resulting in inaccurate positioning. By comparing the signal strengths of multiple positioning systems, the method can dynamically select the most reliable positioning data source, thereby maximizing positioning accuracy.

[0014] In some embodiments, during the real-time collection of surveying and mapping operation data, if an abnormality is detected in the drone at the first position, before the step of obtaining the area of ​​the undetected region in the target area, the step further includes: Get real-time access to self-diagnostic data sent by each drone; If the self-diagnosis data is detected to be abnormal, it is determined that the drone at the corresponding position is abnormal.

[0015] Through the above embodiments, the surveying and mapping operation data acquisition system can timely detect the abnormal state of the drone by acquiring the self-diagnosis data of each drone in real time, greatly improving the reliability and safety of the surveying and mapping system. Under severe weather conditions, drones are more prone to various failures or abnormal conditions. By continuously monitoring the self-diagnosis data, the method can quickly identify the problem as soon as it occurs, so that there is enough time to take countermeasures. It can not only prevent the interruption or degradation of data collection caused by drone failure, but also effectively avoid safety accidents caused by equipment failure.

[0016] In some embodiments, after the step of determining the number of drones and the first flight layout according to the area of ​​the target area, the method further includes: During the flight of the drone, the quality of the acquired pictures or videos can be evaluated in real time; If it is detected that the image or video quality does not meet the preset quality requirements, the corresponding data collection area is set as an abnormal area; After completing the surveying and mapping data collection in the target area, control the UAV to re-collect data in the abnormal area.

[0017] Through the above-mentioned embodiments, the surveying and mapping operation data acquisition system greatly improves the overall quality and integrity of the surveying and mapping data by evaluating the quality of the acquired pictures or videos in real time and re-collecting the areas that do not meet the requirements. Under severe weather conditions, there are many factors that affect the image quality. Through real-time quality evaluation, this method can promptly detect and mark areas that do not meet the quality standards. After completing the overall surveying and mapping, the system will specifically re-collect these abnormal areas to ensure that the quality of the final data set is balanced, complete and reliable. This quality control mechanism not only improves the overall quality of the surveying and mapping data, but also enhances the credibility and practicality of the surveying and mapping results.

[0018] In some embodiments, during the real-time collection of surveying and mapping operation data, if an abnormality is detected in the drone at the first position, after the step of obtaining the area of ​​the undetected area in the target area, the step further includes: Generate a return route based on the collected surveying and mapping data; The drone at the first position is controlled to fly according to the return route.

[0019] Through the above embodiments, the surveying and mapping operation data acquisition system greatly improves the safety and reliability of the surveying and mapping system by generating a return route based on the collected data for the abnormal drone. Under severe weather conditions, the drone may need to interrupt the mission and return for various reasons. By analyzing the collected surveying and mapping data to generate a return route, this method can plan the safest and most efficient return path for the abnormal drone. It can not only maximize the safety of the drone and reduce the risk exposure time in harsh environments, but also avoid repeated interference with the surveyed area during the return process.

[0020] In a second aspect, the present application provides a surveying and mapping operation data collection system, the surveying and mapping operation data collection system comprising: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program code, which includes computer instructions. The one or more processors call the computer instructions so that the surveying and mapping operation data acquisition system can implement a real-time acquisition method for surveying and mapping operation data in severe weather provided in the above embodiment, which will not be repeated here.

[0021] In a third aspect, the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on a surveying and mapping operation data acquisition system, the surveying and mapping operation data acquisition system can implement a real-time acquisition method for surveying and mapping operation data in severe weather conditions provided in the above-mentioned embodiment, which will not be described in detail here.

[0022] In a fourth aspect, the present application provides a computer program product. When the computer program product is run on a surveying and mapping operation data acquisition system, the surveying and mapping operation data acquisition system can implement a real-time acquisition method for surveying and mapping operation data in severe weather conditions provided in the above-mentioned embodiment, which will not be repeated here.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By obtaining weather information, target area and drone status in real time, the number of drones and flight layout can be dynamically adjusted. This adaptive mechanism can not only optimize the surveying and mapping strategy in real time according to environmental changes, but also automatically adjust the flight plan when abnormal conditions are detected to ensure the continuity and integrity of the surveying and mapping tasks. This dynamic adjustment capability greatly improves the adaptability and robustness of the system in bad weather, allowing surveying and mapping operations to maintain high efficiency and accuracy in complex and changing environments.

[0024] 2. It integrates multi-level safety measures, including real-time monitoring of drone spacing and track correction, comparison of signal strength of multiple positioning systems, and analysis of drone self-diagnosis data. These mechanisms together build a comprehensive safety net that can promptly detect and respond to various potential risks, such as positioning anomalies and equipment failures. Especially in severe weather conditions, this multi-level safety mechanism greatly improves the reliability and safety of the entire surveying and mapping system and effectively reduces operational risks.

[0025] 3. Real-time image quality assessment and intelligent compensation mechanism are introduced. By performing real-time quality assessment on the collected pictures or videos, the system can promptly mark areas with substandard quality and re-collect these areas after the surveying and mapping task is completed. This intelligent quality control not only ensures the balance and integrity of the final data set, but also greatly improves the credibility and practicality of the surveying and mapping results. For application scenarios that require high-precision data, such as disaster monitoring and assessment, this method provides more reliable data support and lays a solid foundation for subsequent analysis and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of a method for real-time collection of surveying and mapping operation data under severe weather conditions in an embodiment of the present application; Figure 2 This is another flow chart of a method for real-time collection of surveying and mapping operation data under severe weather conditions in an embodiment of the present application; Figure 3 It is a flow chart of the quality assessment of the collected surveying and mapping data by the surveying and mapping operation data collection system in the embodiment of the present application; Figure 4It is a schematic diagram of the structure of a physical device of the surveying and mapping operation data acquisition system in the embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] For ease of understanding, application scenarios of relevant embodiments are introduced below.

[0030] A county was hit by a torrential rainstorm that has not been seen in a century. The continuous heavy rainfall caused landslides and mud-rock flows in many places, threatening the lives and property of local residents. The local meteorological department predicted that the heavy rain will continue in the next week. In order to better assess the disaster and formulate response strategies, the local government urgently needs to conduct comprehensive topographic mapping of the disaster-stricken areas. However, the continuous bad weather makes it difficult to implement traditional ground mapping methods. Heavy rain and strong winds not only hinder the field operations of surveyors, but also greatly reduce the accuracy and reliability of measuring equipment. At the same time, the constantly changing terrain conditions also increase the difficulty of mapping. In this case, how to quickly and accurately obtain a large range of terrain data under bad weather conditions has become an urgent problem to be solved.

[0031] Faced with the county's emergency, the local surveying and mapping department decided to use drone aerial photography technology for topographic mapping. They used a high-performance fixed-wing drone equipped with a high-resolution camera and GPS positioning system. However, in actual operation, this method exposed many problems. First, the continuous heavy rainfall seriously affected the flight stability of the drone, resulting in multiple mission interruptions. Second, strong winds made it difficult for the drone to maintain the predetermined flight route, resulting in duplication or omission of data collection. In addition, high humidity caused the camera lens to fog frequently, affecting the image quality. GPS signals also often interrupted or drifted in mountainous areas and in bad weather, affecting the geolocation accuracy of the data. These problems seriously affected the efficiency of surveying and mapping and the quality of data, making it impossible to carry out disaster assessment and the formulation of response measures in a timely manner.

[0032] Assume that the county has adopted a real-time data collection method and system for surveying and mapping operations in severe weather conditions provided by this application. The surveying and mapping operation data collection system improves the adaptability of surveying and mapping operations in severe weather conditions by obtaining weather information of the target area and selecting appropriate data collection tools according to weather conditions. At the same time, the number of drones and flight layout are flexibly adjusted according to the area of ​​the target area, which not only ensures the surveying and mapping coverage rate, but also improves efficiency. During the operation, if an abnormal situation is detected, the method can adjust the flight layout in real time to ensure the continuity and integrity of the surveying and mapping task. This dynamic adjustment mechanism greatly enhances the robustness of the surveying and mapping system, and can ensure the reliability and accuracy of the surveying and mapping data even under complex and changeable severe weather conditions.

[0033] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 The figure is a flow chart of a method for real-time collection of surveying and mapping operation data under severe weather conditions in an embodiment of the present application.

[0034] S101. Obtain weather information of a target area.

[0035] Because weather conditions directly affect the feasibility, safety and quality of data collection of surveying and mapping operations, the surveying and mapping data collection system first needs to obtain weather information of the target area. Specifically, the system can obtain real-time and forecast weather information through a variety of channels, including but not limited to API interfaces provided by meteorological departments, satellite meteorological data, ground meteorological station data, etc. Among them, the weather information obtained usually includes key parameters such as temperature, humidity, wind speed, wind direction, precipitation, visibility, etc., which are not limited here.

[0036] S102. Matching data collection tools for surveying and mapping operations based on weather information.

[0037] The surveying and mapping data collection system selects the most suitable equipment combination from the pre-set data collection tool library based on the weather parameters such as temperature, humidity, wind speed, visibility and other weather information. For example, in strong wind conditions, the system may choose a drone model with stronger wind resistance and a sensor with lighter weight but stable performance; in a low temperature environment, the system may choose a device casing with heat preservation function to ensure the normal operation of the instrument.

[0038] It should be noted that the matching relationship between weather data and data collection tools can be set or adjusted according to actual conditions and is not limited here.

[0039] S103: Determine the number of drones and the first flight layout according to the area of ​​the target area.

[0040] After selecting the appropriate data collection tool, the surveying and mapping operation data collection system needs to determine the required number of drones and the initial flight layout (i.e., the first flight layout) according to the area of ​​the target area. Specifically, the system stores the corresponding relationship between different area ranges and the number of drones in the database, so the system can match the required number of drones from the database according to the area of ​​the target area.

[0041] Furthermore, the system also stores the corresponding relationship between the number of drones and the flight layout of the drones in the database. After determining the number of drones, the system can match the flight layout of the drones from the database according to the number of drones to obtain the first flight layout. The drones are controlled in the target area and data collection for surveying and mapping operations is performed according to the first flight layout.

[0042] S104. During the real-time collection of surveying and mapping operation data, if an abnormality is detected in the UAV at the first position, the area of ​​the undetected region in the target area is obtained.

[0043] The surveying and mapping data collection system needs to continuously monitor the status of all drones during the surveying and mapping task. When the system detects that the drone at the first location is abnormal, the emergency response mechanism is immediately activated.

[0044] Specifically, the system can monitor the status of each drone in real time through a variety of sensors and communication links. This includes but is not limited to GPS positioning information, flight attitude data, battery power, communication signal strength, camera status, etc. In this process, anomaly detection can use a variety of technologies, such as statistical process control (SPC), anomaly detection algorithms (such as isolation forests or autoencoders), etc. These methods can quickly identify drones that deviate from normal working conditions, which are not limited here.

[0045] If an abnormality is detected in the drone at the first location, the system will immediately evaluate how much area in the area covered by one or more drones at the first location has not been mapped. Specifically, the system can compare the flight trajectory of the drone, the coverage of the collected data, and the predetermined mapping area to calculate the area of ​​the undetected area.

[0046] S105. Adjust the layout of the UAVs at the second position according to the area of ​​the undetected region to obtain a second flight layout.

[0047] After obtaining the area of ​​the undetected area, the surveying and mapping data collection system needs to quickly adjust the flight layout of the remaining drones to make up for the coverage gap caused by the withdrawal of abnormal drones.

[0048] Specifically, the system counts the number of remaining drones, and then re-matches the drone flight layout from the database according to the number of remaining drones to obtain a second flight layout. The drone is controlled to fly according to the second flight layout to complete the data collection of the undetected area surveying and mapping operation.

[0049] S106: Control the UAV to continue collecting surveying and mapping data of the target area according to the second flight layout.

[0050] After generating the second flight layout, the surveying and mapping data acquisition system needs to accurately control the remaining UAVs to execute the new flight plan to continue to complete the surveying and mapping mission of the target area.

[0051] Specifically, the system first needs to decompose the second flight layout into specific flight paths and mission instructions for each UAV, and send the specific flight paths and mission instructions to the corresponding UAVs, thereby achieving flight control of the UAVs in the second flight layout.

[0052] In the above embodiment, the surveying and mapping operation data acquisition system improves the adaptability of surveying and mapping operations in bad weather by obtaining weather information of the target area and selecting appropriate data acquisition tools according to weather conditions. At the same time, the number of drones and flight layout are flexibly adjusted according to the area of ​​the target area, which not only ensures the surveying and mapping coverage but also improves efficiency. During the operation, if an abnormal situation is detected, the method can adjust the flight layout in real time to ensure the continuity and integrity of the surveying and mapping task. This dynamic adjustment mechanism greatly enhances the robustness of the surveying and mapping system, and can ensure the reliability and accuracy of the surveying and mapping data even under complex and changeable bad weather conditions.

[0053] The following is a more detailed description of the process of the method provided by this embodiment. Figure 2 As shown, it is another flow chart of a method for real-time collection of surveying and mapping operation data under severe weather conditions in an embodiment of the present application.

[0054] S201. Acquire the positioning information sent by each UAV in real time.

[0055] The surveying and mapping data collection system continuously receives positioning information from each drone through a wireless communication network. This positioning information usually includes key information such as latitude and longitude coordinates, altitude, flight speed and heading. Among them, the surveying and mapping data collection system uses a high-precision global navigation satellite system (GNSS) receiver combined with inertial measurement unit (IMU) data to achieve centimeter-level positioning accuracy.

[0056] In addition, in order to improve the reliability of UAV positioning information under severe weather conditions, the surveying and mapping data acquisition system can also use multiple positioning technologies at the same time. For example, in addition to conventional GPS positioning, the Beidou satellite navigation system, ground-based augmentation system (GBAS) or pseudo-satellite technology may also be used. After the fusion processing of these multi-source positioning data, the accuracy and stability of UAV positioning can be greatly improved.

[0057] For example, in a specific embodiment, suppose that in a mountain surveying and mapping mission under heavy rain, the surveying and mapping operation data acquisition system deploys 10 drones. Each drone sends positioning information to the surveying and mapping operation data acquisition system once a second. These positioning information include: 30°12'15.6" north latitude, 120°08'42.3" east longitude, 1258 meters above sea level, flight speed 15 meters / second, heading 45°. By analyzing these positioning information in real time, the surveying and mapping operation data acquisition system can not only accurately grasp the position of each drone, but also calculate the flight trajectory based on the continuous positioning information, providing an important basis for subsequent mission planning and anomaly detection.

[0058] S202: During the flight of the drone, the distance between adjacent drones is monitored in real time.

[0059] In the scenario of multiple drones working together, the surveying and mapping operation data collection system calculates the three-dimensional space distance between adjacent drones in real time to ensure that they always remain within a safe and effective working range. Specifically, the surveying and mapping operation data collection system uses the precise positioning information of the drones obtained in step S201, combined with laser ranging equipment, etc., to complete the distance calculation within milliseconds.

[0060] In order to cope with emergencies that may occur under severe weather conditions, the surveying and mapping data collection system can also dynamically adjust the safety distance threshold according to weather conditions. For example, in strong winds, the system will appropriately increase the minimum safety distance between drones to cope with possible flight trajectory deviations. At the same time, the surveying and mapping data collection system will also consider terrain factors and automatically adjust the vertical spacing of drones in complex terrain areas.

[0061] For example, in a specific embodiment, in a coastline mapping mission under strong winds, the mapping operation data acquisition system deployed 5 drones to fly in an echelon. Under normal circumstances, the mapping operation data acquisition system sets the horizontal safety distance of adjacent drones to 100 meters and the vertical safety distance to 50 meters. However, considering the strong winds, the mapping operation data acquisition system automatically adjusts the horizontal safety distance to 150 meters and the vertical safety distance to 80 meters. The mapping operation data acquisition system calculates the distance between adjacent drones every 0.1 seconds and compares the result with the adjusted safety distance to ensure flight safety.

[0062] S203: If the detected distance value exceeds the preset deviation value, the flight trajectory of the UAV is corrected.

[0063] When the surveying and mapping data acquisition system detects that the distance between adjacent drones exceeds the preset deviation value, the flight trajectory correction program will be immediately started to correct the flight trajectory. Specifically, a drone in the first flight layout is selected as a reference point, and the theoretical position data of other drones is calculated based on the flight spacing corresponding to the first flight layout. Then, the adjustment parameters of each other drone are determined based on the theoretical position data, and then the corresponding flight control instructions are generated to adjust the flight trajectory of the corresponding drone.

[0064] It should be noted that, in this step, the theoretical position data of other UAVs are calculated based on the flight spacing corresponding to the first flight layout and the flight trajectory of each UAV is adjusted accordingly. The purpose is to maintain the UAV in the target area always using the first flight layout for surveying and mapping data collection.

[0065] S204: Determine the predicted position of the adjacent UAV according to the first flight configuration and the positioning information.

[0066] In a complex surveying and mapping environment, any UAV in the first flight layout is selected as the reference point (generally the UAV at the center position is selected as the reference point), and the predicted positions of adjacent UAVs are calculated based on the flight spacing corresponding to the first flight layout.

[0067] It should be noted that this step is performed on the basis of step S203. Specifically, in step S203, the system can control the drones to always maintain the first flight layout during the flight, that is, to keep the distance between adjacent drones unchanged. On this basis, the system can calculate the predicted position of each drone in the first flight layout based on the GPS coordinates of any one of the drones, combined with the corresponding distance and direction. Then, in step S205, the predicted position is compared with the GPS coordinates of each drone itself to verify the accuracy of the GPS coordinates.

[0068] S205: Whether the predicted position matches the positioning information.

[0069] After obtaining the predicted position, the surveying and mapping data acquisition system will immediately compare it with the actual positioning information received.

[0070] Specifically, the surveying and mapping data acquisition system will set an allowable error range, which will be dynamically adjusted according to the current weather conditions, terrain characteristics and surveying and mapping task requirements. For example, under strong wind conditions, the allowable error range may be appropriately relaxed, which is not limited here. Then, it is determined whether the coordinate difference corresponding to the predicted position and the positioning information is within the preset error range. If so, the subsequent steps such as step S208 are executed. Otherwise, it enters step S206 and issues a positioning abnormality warning.

[0071] S206: Issue a positioning abnormality warning and detect the signal strength of multiple positioning systems.

[0072] When the surveying and mapping data acquisition system detects that the predicted position does not match the positioning information and the deviation continues to exceed the allowable error range, the positioning abnormality warning mechanism will be immediately triggered.

[0073] Specifically, the surveying and mapping data collection system makes a preliminary classification of abnormal situations. Possible causes include, but are not limited to: positioning system failure, external interference, drone hardware problems, or extreme weather effects. Based on this preliminary judgment, the surveying and mapping data collection system will select a corresponding processing strategy.

[0074] In addition, the surveying and mapping data collection system will immediately start to detect the signal strength of multiple positioning systems. Modern surveying and mapping drones are usually equipped with multiple positioning systems, which may include global navigation satellite systems such as GPS, GLONASS, Beidou, Galileo, and ground-based augmentation systems (such as RTK). The surveying and mapping data collection system will monitor the signal quality of these different positioning sources in real time, including parameters such as signal strength, number of satellites, and geometric distribution.

[0075] S207: Use the positioning system with the largest signal strength to reacquire the predicted position and the positioning information of the corresponding UAV.

[0076] After determining the positioning system with the strongest signal, the surveying and mapping data acquisition system will immediately start the re-positioning process, that is, re-acquire the position information of the drone through the new positioning system. After determining the position information of the drone, the predicted positions of other adjacent drones are calculated through the first flight layout.

[0077] S208: If it is detected that the self-diagnosis data of the drone is abnormal, it is determined that the drone at the corresponding position is abnormal.

[0078] In severe weather conditions, the surveying and mapping data acquisition system will dynamically adjust the thresholds and judgment criteria for abnormal detection. For example, in a low temperature environment, battery performance may decline, and the system will adjust the power warning threshold accordingly. Similarly, in strong wind conditions, the motor load may increase, and the system will appropriately relax the judgment criteria for motor performance. When the system determines that a drone has an abnormality based on the self-diagnostic data sent by the drone (that is, there is a certain detection data that exceeds the corresponding threshold or judgment standard), it will immediately initiate a series of preset emergency procedures. This may include attempting a remote reset, adjusting flight parameters, or even initiating an emergency return procedure, which is not limited here.

[0079] S209: Generate a return route based on the collected surveying and mapping operation data.

[0080] When the system determines that a drone needs to return, whether due to mission completion, anomalies, or deteriorating weather conditions, the return route generation process will be initiated. During this process, the system will check the collected surveying data to determine which areas have been surveyed and which areas have not yet been covered. This helps the system avoid surveyed areas as much as possible when generating the return route, prevent duplicate data collection, and improve overall mission efficiency.

[0081] S210, controlling the UAV at the first position to fly along the return route.

[0082] After the return route is generated, the system will transmit the return route data in an appropriate format to the flight control system of the target drone. In addition, during the return process, the system will continue to monitor the actual flight status of the drone, including parameters such as position, speed, and attitude, and compare these real-time data with the predetermined return route. If a deviation is detected, the system will immediately make fine adjustments.

[0083] Below Figure 3 The following is a flow chart of quality assessment of collected surveying and mapping data by a surveying and mapping operation data acquisition system in an embodiment of the present application.

[0084] S301. During the flight of the UAV, the quality of the acquired pictures or videos is evaluated in real time.

[0085] The surveying and mapping data acquisition system continuously performs real-time quality assessment of the acquired images or videos during the flight of the drone. Specifically, the system uses an integrated image processing algorithm to instantly analyze each frame of the image or video clip sent back by the drone. The evaluation indicators include but are not limited to image clarity, brightness balance, color saturation, noise level, and image distortion. For example, in windy weather, the system may detect image blur due to drone shaking; in rainy and snowy weather, it may detect occlusion and interference of the lens caused by water droplets or snowflakes. By setting the thresholds of these indicators, the system can objectively determine whether each frame of the image meets the preset quality standards.

[0086] S302: If it is detected that the image or video quality does not meet the preset quality requirement, the corresponding data collection area is set as an abnormal area.

[0087] When the surveying and mapping data collection system finds that the image or video quality does not meet the standards during real-time evaluation, it will immediately mark the corresponding data collection area as an abnormal area.

[0088] Specifically, the system will determine whether the image or video meets the requirements based on pre-set quality thresholds. These thresholds usually include multiple dimensions such as clarity index, signal-to-noise ratio, color saturation, etc. For example, if the clarity index of the image is lower than the preset value, or the noise level exceeds the acceptable range, the system will mark the area as an abnormality. In severe weather conditions, this anomaly may be due to reduced visibility caused by heavy fog, or camera shake caused by strong winds. After marking an area as an abnormality, the system will perform the following operations: First, the geographic coordinates and scope of the area are accurately marked on the internal map. Secondly, the system will record the specific reasons for the abnormality, such as "blurred image", "overexposure", etc.

[0089] S303: After completing the surveying and mapping data collection of the target area, control the UAV to re-collect data on the abnormal area.

[0090] After completing the initial survey of the entire target area, the surveying and mapping data collection system will enter the supplementary collection stage, specifically re-collecting data for previously marked abnormal areas.

[0091] Specifically, the system will first prioritize all marked abnormal areas, taking into account factors such as the degree of abnormality, regional importance, weather forecast, etc. For example, in a landslide monitoring task, areas with larger slopes may be given higher priority. Then, based on this priority list, the system will develop an optimized re-collection path to cover all abnormal areas in the most efficient way.

[0092] During the re-collection process, the system will dynamically adjust the collection strategy based on the previously recorded abnormal reasons. For example, if a certain area previously had poor image quality due to insufficient light, the system may adjust the camera's exposure parameters during re-collection, or choose to fly during a time period with better light conditions. At the same time, the system will also monitor weather changes in real time, and if conditions deteriorate further, it may decide to postpone the re-collection of certain areas.

[0093] The surveying and mapping operation data acquisition system of the embodiment of the present invention is an electronic device. Figure 4 A schematic diagram of the architecture of an electronic device suitable for implementing an embodiment of the present invention is shown.

[0094] It should be noted that Figure 4 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0095] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructions (computer programs), or by controlling related hardware through instructions (computer programs), and the instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. The electronic device of this embodiment includes a storage medium and a processor, wherein a plurality of instructions are stored in the storage medium, and the instructions can be loaded by the processor to execute any step of the method provided in the embodiment of the present invention.

[0096] Specifically, the storage medium and the processor are electrically connected directly or indirectly to realize data transmission or interaction. For example, these elements can be electrically connected to each other through one or more signal lines. The storage medium stores computer execution instructions for implementing the data access control method, including at least one software function module that can be stored in the storage medium in the form of software or firmware. The processor executes various functional applications and data processing by running the software program and module stored in the storage medium. The storage medium can be, but is not limited to, random access storage medium (Random Access Memory, referred to as: RAM), read-only storage medium (Read Only Memory, referred to as: ROM), programmable read-only storage medium (Programmable Read-Only Memory, referred to as: PROM), erasable read-only storage medium (Erasable Programmable Read-Only Memory, referred to as: EPROM), electrically erasable read-only storage medium (Electric Erasable Programmable Read-Only Memory, referred to as: EEPROM), etc. Among them, the storage medium is used to store programs, and the processor executes the program after receiving the execution instruction.

[0097] Furthermore, the software programs and modules in the above-mentioned storage medium may also include an operating system, which may include various software components and / or drivers for managing system tasks (such as memory management, storage device control, power management, etc.), and may communicate with various hardware or software components to provide an operating environment for other software components. The processor may be an integrated circuit chip having signal processing capabilities. The above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc., which may implement or execute the various methods, steps, and logic flow diagrams disclosed in this embodiment. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0098] Since the instructions stored in the storage medium can execute the steps in any method provided in the embodiments of the present invention, the beneficial effects of any method provided in the embodiments of the present invention can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0099] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A real-time data collection method for surveying and mapping operations in bad weather, applied to a surveying and mapping operation data collection system, characterized in that: The method comprises: Acquiring weather information of a target area, wherein the target area is a geographical area for which surveying and mapping operation data collection is to be performed; Matching a data collection tool for surveying and mapping operations according to the weather information, wherein the data collection tool is carried on a drone; Determining the number of drones and a first flight layout according to the area of ​​the target area, wherein the number of drones is proportional to the area, and the first flight layout is composed of drones at the first position and drones at the second position; During the real-time collection of surveying and mapping operation data, if an abnormality is detected in the drone at the first position, the area of ​​the undetected region in the target area is obtained; Adjusting the layout of the UAVs at the second position according to the area of ​​the undetected region to obtain a second flight layout; The UAV is controlled to continue collecting surveying and mapping operation data of the target area according to the second flight layout.

2. The method according to claim 1, characterized in that After the step of determining the number of drones and the first flight layout according to the area of ​​the target area, the method further includes: Obtain the positioning information sent by each drone in real time; Determining a predicted position of an adjacent UAV based on the first flight configuration and the positioning information; If it is detected that the predicted position does not match the positioning information of the corresponding drone, a positioning abnormality warning is issued.

3. The method according to claim 2, characterized in that Before the step of determining the predicted position of the adjacent UAV according to the first flight configuration and the positioning information, the method further includes: During the flight of the drone, the distance between adjacent drones is monitored in real time; If it is detected that the distance value exceeds the preset deviation value, the flight trajectory of the UAV is corrected.

4. The method according to claim 2, characterized in that: After the step of issuing a positioning abnormality warning if it is detected that the predicted position does not match the positioning information of the corresponding drone, the method further includes: If it is detected that all predicted positions do not match the positioning information of the corresponding drone, the signal strength of multiple positioning systems is detected; Use the positioning system with the strongest signal strength to re-match the predicted position with the positioning information of the corresponding drone.

5. The method according to claim 1, characterized in that In the real-time collection process of surveying and mapping operation data, if an abnormality is detected in the drone at the first position, before the step of obtaining the area of ​​the undetected area in the target area, the step further includes: Get real-time access to self-diagnostic data sent by each drone; If it is detected that the self-diagnosis data is abnormal, it is determined that the drone at the corresponding position is abnormal.

6. The method according to claim 1, characterized in that After the step of determining the number of drones and the first flight layout according to the area of ​​the target area, the method further includes: During the flight of the drone, the quality of the acquired pictures or videos can be evaluated in real time; If it is detected that the quality of the picture or video does not meet the preset quality requirements, the corresponding data collection area is set as an abnormal area; After completing the surveying and mapping data collection of the target area, the UAV is controlled to re-collect data on the abnormal area.

7. The method according to claim 1, characterized in that In the real-time collection process of surveying and mapping operation data, if an abnormality is detected in the drone at the first position, after the step of obtaining the area of ​​the undetected area in the target area, the method further includes: Generate a return route based on the collected surveying and mapping data; The UAV at the first position is controlled to fly according to the return route.

8. A surveying and mapping data acquisition system, characterized in that: The surveying and mapping operation data acquisition system includes: one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the surveying and mapping operation data acquisition system to execute the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a surveying and mapping operation data collection system, the surveying and mapping operation data collection system is enabled to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a surveying and mapping operation data collection system, the surveying and mapping operation data collection system is enabled to execute the method according to any one of claims 1 to 7.

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