Unmanned aerial vehicle low-altitude inspection planning system and method based on dangerous case analysis

Abstract

The invention relates to the technical field of inspection planning, in particular to an unmanned aerial vehicle low-altitude inspection planning system and method based on dangerous case analysis. According to the method, multi-dimensional calculation including flight complexity assessment, flight height danger, building density danger and the like is carried out, dynamic and static risks are integrated, finally, building collision danger and risk assessment results of all areas are integrated to obtain a global route danger assessment result, and a route with the minimum danger is selected according to the global route danger assessment result. According to the whole scheme, multi-dimensional and comprehensive risk assessment is realized, various factors such as environment and building are considered, related standard requirements are met, and the flight risk of the unmanned aerial vehicle can be effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of inspection planning technology, and in particular to a low-altitude inspection planning system and method for unmanned aerial vehicles (UAVs) based on hazard analysis. Background Technology

[0002] In recent years, drones have been widely used in many fields due to their flexibility and efficiency, such as power line inspection, geographic surveying, logistics distribution, and disaster relief. Taking power line inspection as an example, drones can quickly fly to designated areas and use onboard high-definition cameras and other equipment to conduct a comprehensive and detailed inspection of power facilities, promptly identifying potential safety hazards and greatly improving inspection efficiency and accuracy. However, drones face many risks during flight, among which collisions with surrounding buildings are a significant issue. On the one hand, with the acceleration of urbanization, high-rise buildings are springing up in cities, and building density is constantly increasing, making the drone flight environment increasingly complex. On the other hand, drones are easily affected by environmental factors in dangerous areas (such as temperature, smoke, humidity, etc. in fire hazard areas) and dangerous areas (such as disaster relief), causing their flight paths to deviate. Once a deviation occurs, the drone may collide with surrounding buildings, causing not only damage to the drone itself but also secondary damage, such as broken building windows and personal injuries, resulting in serious safety hazards and economic losses.

[0003] Currently, the assessment of drone flight risks mainly focuses on the impact of environmental factors and dangerous areas. For example, meteorological data is used to monitor the impact of severe weather such as strong winds and heavy rain on the flight stability of drones, and geographic information system technology is used to mark dangerous areas and restrict drone access. However, these assessment methods often ignore the danger of drone trajectories colliding with surrounding buildings and do not incorporate building factors into the overall risk assessment system. Summary of the Invention

[0004] In order to overcome the defects and shortcomings of existing technologies, this invention provides a UAV low-altitude inspection planning system and method based on hazard analysis.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for planning low-altitude inspections of unmanned aerial vehicles (UAVs) based on hazard analysis, comprising the following steps: Step S1: Obtain data on the drone inspection route, the location of the corresponding hazard, and the safe zone. Step S2: Conduct a drone route risk assessment based on the situation data of the location of the hazard and the situation data of the safe range; Step S3: Determine the building collision risk of the drone based on the building conditions near the drone's trajectory; Step S4: Conduct a drone route hazard assessment based on the drone route risk assessment results and the building collision hazard of the drone trajectory; Step S5: Select the drone route based on the drone route hazard assessment results.

[0006] In one implementation of the present invention, the drone inspection route includes a pre-prepared inspection route trajectory, and simultaneously acquires data on the closest distance and height of buildings near the trajectory to the trajectory route, as well as data on the density of buildings along the trajectory. The building data can be obtained from the municipal system via a network connection. The data corresponding to the location of the hazard includes environmental data of the hazard location. The safety zone data includes the safety zone and hazard level defined by the emergency management department. By acquiring the safety zone defined by the emergency management department, the depth of the drone entering the hazardous area and the hazard level within the hazardous area can be determined.

[0007] In one implementation of the present invention, the UAV route risk assessment in step S2 includes the following specific steps: S21. Obtain information on alternative routes for drones, as well as the environmental conditions of each area along the route and the depth at which the drone enters dangerous areas; S22. Analyze the abnormal impact of the environmental conditions in each area of ​​the corresponding route on the flight of the UAV. S23. Obtain the depth of the UAV entering the danger zone in each area, that is, the distance from the danger zone to the center point of the accident. The smaller the distance, the higher the degree of danger. Divide the safe zone distance by the depth of the UAV entering the danger zone in each area to obtain the impact of the danger zone on the UAV. Use the ratio of the safe zone distance to the current position of the UAV to dynamically reflect the spatial proximity risk, based on the distance attenuation effect. S24. By weighted summing the abnormal impact of the regional environment on the drone flight and the impact of the dangerous area on the drone, the drone risk assessment result of the corresponding area is obtained. The environmental anomaly and the danger depth are weighted and integrated to realize multi-dimensional risk coupling analysis, which not only covers sudden environmental threats, but also identifies hidden spatial risks. When danger occurs, the drone is affected by the environment and the dangerous area. If it deviates from its course, it is very likely to collide with the surrounding buildings and cause secondary damage.

[0008] In one implementation of the present invention, the building collision hazard of the UAV trajectory in step S3 includes the following specific contents: S31. Obtain data on the flight trajectory of drones in each area, the shortest distance and height of buildings near the trajectory to the trajectory route, and the density of buildings along the trajectory. By obtaining data such as drone flight trajectory, building distance and height, and density, an environmental perception baseline can be established. This step provides basic spatial information for risk assessment. S32. Obtain the changes in the UAV's flight altitude and flight trajectory angle in the corresponding area of ​​the trajectory. Import the changes in flight altitude and flight trajectory angle into the UAV flight complexity assessment formula to obtain the altitude complexity assessment value and the trajectory angle complexity assessment value. Average the altitude complexity assessment value and trajectory angle complexity assessment value of the trajectory in the corresponding area to obtain the altitude complexity assessment value and trajectory angle complexity assessment value of the corresponding area. Weighted summation of the altitude complexity assessment value and trajectory angle complexity assessment value of the corresponding area to obtain the flight complexity assessment value of the corresponding area. Frequent changes in altitude or angle will increase the risk of loss of control. The difference method is used to quantify instantaneous changes and standardize them to separate the altitude and angle risk sources and avoid the influence of unit differences. The regional mean and weighted summation can comprehensively reflect the difficulty of flight operation and provide a quantitative basis for subsequent risk assessment. S33. Obtain the building height and UAV flight altitude of the flight area, and assess the flight altitude hazard value of the area based on the building height and UAV flight altitude of the flight area. That is, the flight altitude hazard value of the corresponding area is obtained by dividing the average building height of the flight area by the UAV flight altitude. S34. Obtain the building density data of the trajectory, and obtain the building density hazard value of the corresponding area by dividing the regional trajectory building density data by the density safety value. S35. The flight hazard value of the corresponding area is obtained by weighted summing of the flight complexity assessment value, flight altitude hazard value, and building density hazard value. S36. Obtain the shortest distance from the nearest building to the trajectory in the area. Divide the safe distance by the shortest distance from the nearest building to the trajectory to obtain the distance hazard value. Obtain the building collision hazard by weighted summing of the distance hazard value and the flight hazard value. Obtain the distance hazard value by dividing the safe distance by the distance to the nearest building. Combine this with the flight hazard value for weighted calculation to comprehensively reflect dynamic and static risks.

[0009] In one implementation of the present invention, the drone route hazard assessment in step S4 includes the following specific contents: S41. Obtain the building collision hazard results and UAV risk assessment results for each area along the path, sum them up to obtain the UAV route hazard for the corresponding area, divide the flight path into continuous areas, and quantify the comprehensive threat level of a single area by superimposing the building collision hazard values ​​and dynamic risk assessment results of each area. S42. Summing the drone route hazards in each area along the path yields the drone route hazard assessment result. Accumulating the hazard values ​​of all areas along the path generates a global route hazard assessment result. This step reflects the overall risk exposure level through linear aggregation and supports horizontal comparison of different route options.

[0010] In one implementation of the present invention, step S5, which involves selecting the drone route, includes the following specific details: Obtain the hazard assessment results for all routes, sort them in descending order, and select the planned route corresponding to the lowest hazard assessment result as the drone route.

[0011] Secondly, the present invention also provides a low-altitude unmanned aerial vehicle (UAV) inspection planning system based on hazard analysis, including: The data acquisition module acquires data on the drone inspection route, the location of the corresponding hazard, and the safe range. The route risk assessment module assesses the risk of drone routes based on data about the location of potential hazards and data about the safe range. The building collision hazard module assesses the building collision hazard of the drone's trajectory based on the building conditions near the drone's path. The route hazard assessment module assesses the hazard of the UAV route based on the results of the UAV route risk assessment and the building collision risk of the UAV trajectory. The route selection module selects drone routes based on the drone route hazard assessment results.

[0012] Thirdly, the present invention provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a UAV low-altitude inspection planning method based on hazard analysis by calling the computer program stored in the memory.

[0013] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to execute a UAV low-altitude inspection planning method based on hazard analysis.

[0014] Compared with the prior art, the present invention has the following advantages and beneficial effects: Firstly, in terms of data acquisition, comprehensive data on drone inspection routes, hazard locations, and safe zones are collected to lay the foundation for subsequent assessments. Secondly, regarding risk assessment, a detailed evaluation of the drone routes is conducted, taking into account the impact of environmental anomalies and hazardous areas, as well as building collision hazards. Calculations are performed from multiple dimensions, including flight complexity assessment, flight altitude hazard, and building density hazard, integrating both dynamic and static risks. Finally, the building collision hazards and risk assessment results for each area are combined to derive a global route hazard assessment result, and the route with the lowest risk is selected accordingly. The entire solution achieves a multi-dimensional and comprehensive risk assessment, taking into account various factors such as the environment and buildings, meeting relevant standards and requirements, and effectively reducing drone flight risks. Attached Figure Description

[0015] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the overall process of Embodiment 1 of the method of the present invention; Figure 2 This is a schematic diagram of step S2 of embodiment 1 of the method of the present invention; Figure 3 This is a schematic diagram of step S3 in embodiment 1 of the method of the present invention; Figure 4 This is a schematic diagram of the structure of embodiment 2 of the system of the present invention. Detailed Implementation

[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0017] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0018] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0019] Example 1

[0020] like Figures 1 to 3As shown, the technical problem solved by this embodiment is: analyzing the building collision hazard of the drone trajectory, integrating the influence of the environment and dangerous areas, assessing the risk of the drone being affected by the environment and dangerous areas, and the risk of secondary damage caused by yaw and collision with surrounding buildings. This embodiment provides a method for planning low-altitude UAV inspections based on hazard analysis, specifically including the following steps: Step S1: Obtain data on the drone inspection route, the location of the corresponding hazard, and the safe zone. In this embodiment, the drone inspection route includes a pre-prepared inspection route trajectory, and simultaneously acquires data on the closest distance and height of nearby buildings to the trajectory, as well as the density of buildings along the trajectory. The building data can be obtained from the municipal system via a network connection. Data corresponding to the location of the hazard includes environmental data such as temperature, smoke, and humidity in the fire hazard area, which affect drone flight safety. The safety zone data includes the safety zone and hazard level defined by the emergency management department. By acquiring the safety zone defined by the emergency management department, the depth of the drone entering the hazard zone and the hazard level within the hazard zone can be determined. For example, within 100 meters, the hazard level is level two; the core area of ​​the fire zone (radius 50m): hazard level one (explosion, high temperature, toxic gas); the buffer zone (50-150m): hazard level two (high temperature, smoke diffusion); the safe zone (>150m): a drone take-off and landing point. Step S2: Conduct a drone route risk assessment based on the situation data of the location of the hazard and the situation data of the safe range; In this embodiment, the drone route risk assessment in step S2 includes the following specific steps: S21. Obtain information on alternative routes for drones, as well as the environmental conditions of each area along the route and the depth at which the drone enters dangerous areas; S22. Analyze the abnormal impact of the environmental conditions in each area of ​​the corresponding route on the flight of the UAV. The specific content is as follows: obtain the environmental conditions of each region, obtain the standard deviation of each environmental condition in the region and the corresponding safe environmental conditions of the drone, obtain the anomalies of each environmental condition, and obtain the anomalies of each environmental condition by weighted summation to obtain the abnormal impact of the regional environment on the drone flight. By calculating the standard deviation of environmental parameters (wind speed, visibility, etc.) and safety thresholds and weighted summation, the risk of environmental mutation is quantified. The basis is the probabilistic risk assessment model. Historical data shows that environmental anomalies are the main cause of accidents. The weighting strategy can adjust the sensitivity for different drone models. The weight values ​​are obtained by testing based on historical data. S23. Obtain the depth of the UAV entering the danger zone in each area, that is, the distance from the danger zone to the center point of the accident. The smaller the distance, the higher the degree of danger. Divide the safe zone distance by the depth of the UAV entering the danger zone in each area to obtain the impact of the danger zone on the UAV. Use the ratio of the safe zone distance to the current position of the UAV to dynamically reflect the spatial proximity risk, based on the distance attenuation effect. S24. By weighted summing the impact of the regional environment on the drone's flight and the impact of the dangerous area on the drone, the corresponding drone risk assessment result is obtained. The weighted fusion of environmental anomalies and dangerous depth achieves multi-dimensional risk coupling analysis, which covers both sudden environmental threats and identifies hidden spatial risks. When a danger occurs, the drone is affected by the environment and the dangerous area, and deviation is very likely to cause collision with surrounding buildings, resulting in secondary damage. Therefore, the building collision risk of the drone trajectory is analyzed in step S3, and then fused with the impact of the environment and dangerous area in this step to assess the risk of the drone being affected by the environment and the dangerous area, and the deviation leading to collision with surrounding buildings and secondary damage. Specifically, a large amount of drone flight accident data is collected first, and the proportion of environmental anomalies and the depth of entering the dangerous area in the accidents is analyzed. For example, after analyzing 1,000 drone flight accident data, it is found that the proportion of accidents caused by environmental anomalies is 60%, and the proportion of accidents caused by the depth of entering the dangerous area is 40%. Then the weight of the abnormal impact of the regional environment on the drone flight can be set to 0.6, and the weight of the impact of the dangerous area on the drone can be set to 0.4. Step S3: Determine the building collision risk of the drone based on the building conditions near the drone's trajectory; In this embodiment, the building collision hazard of the drone trajectory in step S3 includes the following specific contents: S31. Obtain data on the flight trajectory of drones in each area, the shortest distance and height of buildings near the trajectory to the trajectory route, and the density of buildings along the trajectory. By obtaining data such as drone flight trajectory, building distance and height, and density, an environmental perception baseline can be established. This step provides basic spatial information for risk assessment. For example, high-risk areas such as urban canyons can be identified by the density of buildings, and potential collision risks can be predicted by combining building height and drone flight height to ensure the accuracy of subsequent assessments. S32. Obtain the changes in the UAV's flight altitude and flight trajectory angle in the corresponding area of ​​the trajectory. Import the changes in flight altitude and flight trajectory angle into the UAV flight complexity evaluation formula to obtain the altitude complexity evaluation value and the trajectory angle complexity evaluation value. The UAV flight complexity evaluation formula for the i-th position is: Here, si represents the flight altitude and flight trajectory angle at the i-th position, s(i-1) represents the flight altitude and flight trajectory angle at the previous position, and sc represents the set safety value for changes in flight altitude and flight trajectory angle that will not affect flight safety. Altitude data and trajectory angle data are substituted separately, not together. That is, the output of the substituted altitude data is the altitude complexity assessment value, and the output of the substituted trajectory angle data is the trajectory angle complexity assessment value. The altitude complexity assessment value and trajectory angle complexity assessment value of the corresponding region are averaged to obtain the altitude complexity assessment value and trajectory angle complexity assessment value of the corresponding region. The altitude complexity assessment value and trajectory angle complexity assessment value of the corresponding region are weighted and summed to obtain the flight complexity assessment value of the corresponding region. Frequent changes in altitude or angle will increase the risk of loss of control (such as sharp turns or wind speed interference). The difference method is used to quantify instantaneous changes and standardize them, which can separate the altitude and angle risk sources and avoid the influence of unit differences. The regional mean and weighted sum can comprehensively reflect the difficulty of flight operation and provide a quantitative basis for subsequent risk assessment. S33. Obtain the building height and drone flight altitude of the flight area. Based on the building height and drone flight altitude of the flight area, assess the flight altitude hazard value of the area. That is, divide the average building height of the flight area by the drone flight altitude to obtain the flight altitude hazard value of the corresponding area. When the drone height is lower than the average building height, the collision probability increases significantly. The risk of spatial compression is directly quantified by the ratio (average building height / drone height). S34. Obtain the building density data of the trajectory. Divide the building density data of the region by the density safety value to obtain the building density danger value of the corresponding region. Divide the actual density by the safety value (such as 10 buildings / km²) to dynamically quantify the environmental complexity. For example, in suburban areas, the safety threshold can be reduced to 5 buildings / km², so as to flexibly adapt to the obstacle avoidance needs of different scenarios. S35. The flight hazard value of the corresponding area is obtained by weighted summing of the flight complexity assessment value, flight altitude hazard value, and building density hazard value. S36. Obtain the shortest distance from the nearest building to the trajectory in the area. Divide the safe distance by the shortest distance from the nearest building to the trajectory to obtain the distance hazard value. Obtain the building collision hazard by weighted sum of the distance hazard value and the flight hazard value. Obtain the distance hazard value by dividing the safe distance by the nearest building distance. Combined with the flight hazard value for weighted calculation, it can comprehensively reflect dynamic and static risks. As for flight speed, the flight speed of the same type of drone is roughly the same in urban areas, so the influence of flight speed does not need to be considered. The weighting weight is also determined based on historical data and actual flight scenario tests. For the weighted average of flight complexity assessment value, flight altitude hazard value, and building density hazard value for the corresponding area, data on drone-building collision accidents in different scenarios were collected to analyze the role of each factor in the accidents. Assuming that in a densely populated urban area with high-rise buildings, after analyzing 500 collision accidents, the flight complexity assessment value accounted for 30% of the accidents, the flight altitude hazard value accounted for 40%, and the building density hazard value accounted for 30%, then the weight of the flight complexity assessment value was 0.3, the weight of the flight altitude hazard value was 0.4, and the weight of the building density hazard value was 0.3. For the weighted average of distance hazard value and flight hazard value, if the analysis found that the distance factor accounted for 60% of the collision accidents and the flight hazard value factor accounted for 40%, then the weight of the distance hazard value was 0.6, and the weight of the flight hazard value was 0.4. Step S4: Conduct a drone route hazard assessment based on the drone route risk assessment results and the building collision hazard of the drone trajectory; In this embodiment, the drone route hazard assessment in step S4 includes the following specific contents: S41. Obtain the building collision hazard results and UAV risk assessment results for each area along the path, sum them to obtain the corresponding UAV route hazard for each area, divide the flight path into continuous areas, and quantify the comprehensive threat level of a single area by superimposing the building collision hazard values ​​and dynamic risk assessment results (such as wind speed, visibility, etc.) of each area. The weighting can be obtained based on a comprehensive analysis of environmental, hazardous area, and building collision factors in flight accidents in different areas. For example, in an industrial park, after analyzing 300 UAV accidents, it was found that building collision factors accounted for 55% of the accidents, and environmental and hazardous area factors accounted for 45% of the accidents. Then, the weight of the building collision hazard result can be set to 0.55, and the weight of the UAV risk assessment result can be set to 0.45. S42. Summing up the drone route hazards in each area along the path yields the drone route hazard assessment result. Accumulating the hazard values ​​of all areas along the path generates a global route hazard assessment result. This step reflects the overall risk exposure level through linear aggregation (e.g., routes in densely populated urban areas have higher total scores) and supports horizontal comparison of different route schemes. Step S5: Select the drone route based on the drone route hazard assessment results; In this embodiment, step S5 involves selecting the drone route, including the following specific details: Obtain the hazard assessment results for all routes, sort them in descending order, and select the planned route corresponding to the lowest hazard assessment result as the drone route.

[0021] In this embodiment, it is important to note that it offers the following advantages: In terms of data acquisition, it comprehensively collects data on drone inspection routes, hazard locations, and safe zones, laying the foundation for subsequent assessments. Regarding risk assessment, it meticulously evaluates drone routes, considering the impact of environmental anomalies and hazardous areas, while also taking into account building collision risks. It calculates risks from multiple dimensions, including flight complexity assessment, flight altitude hazard, and building density hazard, integrating both dynamic and static risks. Finally, it combines the building collision risks of each area with the risk assessment results to arrive at a global route hazard assessment, selecting the route with the lowest risk accordingly. The entire solution achieves multi-dimensional and comprehensive risk assessment, taking into account various factors such as the environment and buildings, meeting relevant standards, and effectively reducing drone flight risks.

[0022] Example 2

[0023] like Figure 3 As shown, this embodiment provides a UAV low-altitude inspection planning system based on hazard analysis, which is implemented based on the UAV low-altitude inspection planning method based on hazard analysis in Embodiment 1. It includes: a data acquisition module, which acquires data on UAV inspection route, corresponding hazard location, and safety range. The route risk assessment module assesses the risk of drone routes based on data about the location of potential hazards and data about the safe range. The building collision hazard module assesses the building collision hazard of the drone's trajectory based on the building conditions near the drone's path. The route hazard assessment module assesses the hazard of the UAV route based on the results of the UAV route risk assessment and the building collision risk of the UAV trajectory. The route selection module selects the drone route based on the drone route hazard assessment results. The specific steps of each module in this embodiment are the same as those in the method embodiment of embodiment 1, and will not be repeated here.

[0024] Example 3

[0025] An electronic device according to an embodiment of the present invention includes a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a UAV low-altitude inspection planning method based on hazard analysis by calling the computer program stored in the memory. It should be noted that all computer programs for the UAV low-altitude inspection planning method based on hazard analysis are implemented using the C language.

[0026] Example 4

[0027] This embodiment proposes a computer-readable storage medium on which an erasable and rewritable computer program is stored. When the computer program runs on the computer device, it causes the computer device to execute the above-mentioned UAV low-altitude inspection planning method based on hazard analysis.

[0028] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network and / or wireless network. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives (SSDs).

[0029] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0030] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0031] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only one method, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0032] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0033] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0034] In the description of this specification, references to terms such as "an embodiment," "example," and "specific example" indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0035] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for planning low-altitude UAV inspections based on hazard analysis, characterized in that, Includes the following steps: Step S1: Obtain data on the drone inspection route, the location of the corresponding hazard, and the safe zone. Step S2: Conduct a drone route risk assessment based on the situation data of the location of the hazard and the situation data of the safe range; Step S3: Determine the building collision risk of the drone based on the building conditions near the drone's trajectory; Step S4: Conduct a drone route hazard assessment based on the drone route risk assessment results and the building collision hazard of the drone trajectory; Step S5: Select the drone route based on the drone route hazard assessment results.

2. The UAV low-altitude inspection planning method based on hazard analysis according to claim 1, characterized in that, The drone route risk assessment includes the following specific steps: S21. Obtain information on alternative routes for drones, as well as the environmental conditions of each area along the route and the depth at which the drone enters dangerous areas; S22. Analyze the abnormal impact of the environmental conditions in each area of ​​the corresponding route on the flight of the UAV. S23. Obtain the depth at which the drone enters the danger zone in each area, and obtain the impact of the danger zone on the drone by dividing the safe zone distance by the drone's depth at which it enters the danger zone in each area. S24. The risk assessment result of the corresponding region's drones is obtained by weighted summing the abnormal impact of the regional environment on drone flight and the impact of dangerous areas on drones.

3. The UAV low-altitude inspection planning method based on hazard analysis according to claim 2, characterized in that, The building collision hazard of the drone trajectory includes the following specific aspects: S31. Obtain data on the flight trajectory of drones in each region, the shortest distance and altitude of buildings near the trajectory to the trajectory route, and the density of buildings along the trajectory. S32. Obtain the changes in the UAV's flight altitude and flight trajectory angle in the corresponding area of ​​the trajectory. Import the changes in flight altitude and flight trajectory angle into the UAV flight complexity evaluation formula to obtain the altitude complexity evaluation value and the trajectory angle complexity evaluation value. The UAV flight complexity evaluation formula for the i-th position is: Where si represents the flight altitude and flight trajectory angle at the i-th position, s(i-1) represents the flight altitude and flight trajectory angle at the previous position, and sc represents the set safety value for changes. The height complexity assessment value and trajectory angle complexity assessment value of the corresponding region are averaged to obtain the height complexity assessment value and trajectory angle complexity assessment value of the corresponding region. The height complexity assessment value and trajectory angle complexity assessment value of the corresponding region are weighted and summed to obtain the flight complexity assessment value of the corresponding region. S33. Obtain the building height information and UAV flight altitude information in the flight area, and assess the regional flight altitude hazard value based on the building height information and UAV flight altitude information in the flight area. S34. Obtain the building density data of the trajectory, and obtain the building density hazard value of the corresponding area by dividing the regional trajectory building density data by the density safety value. S35. The flight hazard value of the corresponding area is obtained by weighted summing of the flight complexity assessment value, flight altitude hazard value, and building density hazard value. S36. Obtain the shortest distance from the building near the area trajectory to the trajectory route. Divide the safe distance by the shortest distance from the building near the area trajectory to the trajectory route to obtain the distance hazard value. Obtain the building collision hazard by weighted summing of the distance hazard value and the flight hazard value.

4. The UAV low-altitude inspection planning method based on hazard analysis according to claim 3, characterized in that, The drone route hazard assessment includes the following specific contents: S41. Obtain the building collision hazard results and UAV risk assessment results for each area along the path, and sum them to obtain the corresponding UAV route hazard for the area. S42. Sum the drone route hazards in each area along the path to obtain the drone route hazard assessment result.

5. The UAV low-altitude inspection planning method based on hazard analysis according to claim 4, characterized in that, The selection of drone routes includes the following specific aspects: Obtain the hazard assessment results for all routes, sort them in descending order, and select the planned route corresponding to the lowest hazard assessment result as the drone route.

6. The UAV low-altitude inspection planning method based on hazard analysis according to claim 2, characterized in that, The specific content of analyzing the abnormal impact of the environmental conditions in each area of ​​the corresponding route on the flight of the UAV is as follows: obtain the environmental conditions of each corresponding area, obtain the standard deviation of each environmental condition in the area and the corresponding safe environmental conditions of the UAV, obtain the abnormality of each environmental condition, and obtain the abnormal impact of the regional environment on the flight of the UAV by weighted summation of the abnormalities of each environmental condition.

7. The UAV low-altitude inspection planning method based on hazard analysis according to claim 1, characterized in that, The drone inspection route information includes the pre-prepared inspection route trajectory information, and also acquires the closest distance, height and density of buildings near the trajectory to the trajectory route data, as well as the data on the density of buildings along the trajectory. The information on the location of the corresponding hazard includes the environmental information of the location of the hazard. The information on the safe range information includes the safe range delineated by the emergency management department and the hazard level information.

8. A UAV low-altitude inspection planning system based on hazard analysis, used to implement the UAV low-altitude inspection planning method based on hazard analysis as described in any one of claims 1-7, characterized in that, The system includes: The data acquisition module acquires data on the drone inspection route, the location of the corresponding hazard, and the safe range. The route risk assessment module assesses the risk of drone routes based on data on the location of potential hazards and the safety range. The building collision hazard module assesses the building collision hazard of the drone's trajectory based on the building conditions near the drone's path. The route hazard assessment module assesses the hazard of the UAV route based on the results of the UAV route risk assessment and the building collision risk of the UAV trajectory. The route selection module selects drone routes based on the drone route hazard assessment results.

9. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the UAV low-altitude inspection planning method based on hazard analysis as described in any one of claims 1-7 by calling the computer program stored in the memory.

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