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

Abstract

The present application relates to the technical field of inspection planning, and particularly relates to a UAV low-altitude inspection planning system and method based on danger analysis, which performs detailed evaluation on the route of the UAV, combines environmental abnormal influence and dangerous area influence, and considers building collision danger, performs multi-dimensional calculation on flight complexity evaluation, flight height danger and building density danger, comprehensively calculates dynamic and static risks, finally, comprehensively obtains global route danger evaluation result by combining building collision danger of each area and risk evaluation result, and selects the route with the minimum danger according to the global route danger evaluation result, so that the whole scheme realizes multi-dimensional and comprehensive risk evaluation, considers various factors such as environment and building, meets relevant standard requirements, and can effectively reduce UAV flight risk.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of inspection planning, and in particular to a UAV low-altitude inspection planning system and method based on hazard analysis. BACKGROUND

[0002] In recent years, UAVs have been widely used in many fields due to their flexibility and efficiency, such as power inspection, geographic mapping, logistics distribution, disaster rescue, etc. For example, in power inspection, UAVs can quickly fly to the designated line area and use the high-definition camera and other equipment to conduct a comprehensive and detailed inspection of power facilities, thereby discovering potential safety hazards in a timely manner and greatly improving the efficiency and accuracy of the inspection. However, UAVs face many risks during flight, one of which is collision with surrounding buildings. On the one hand, with the acceleration of urbanization, high-rise buildings are springing up in cities, and the building density is increasing, making the UAV flight environment increasingly complex. On the other hand, UAVs are easily affected by dangerous area environmental factors (such as temperature, smoke, humidity, etc. in fire hazard areas) and dangerous areas (such as disaster rescue, etc.) during flight, causing the flight trajectory to deviate. Once the flight trajectory deviates, the UAV may collide with surrounding buildings, not only causing damage to the UAV itself, but also potentially causing secondary damage, such as broken building glass and personal injury, resulting in serious safety hazards and economic losses.

[0003] Currently, the evaluation of UAV flight risks mainly focuses on the impact of environmental factors and dangerous areas. For example, meteorological data is used to monitor the impact of strong winds, heavy rain, and other adverse weather conditions on the stability of UAV flight, and geographic information system technology is used to mark dangerous areas to restrict UAV entry. However, these evaluation methods often ignore the risk of UAV trajectory collision with surrounding buildings and do not include building factors in the overall risk assessment system. SUMMARY

[0004] In order to overcome the defects and deficiencies of the prior art, the present application provides a UAV low-altitude inspection planning system and method based on hazard analysis.

[0005] In order to achieve the above purpose, the present application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a UAV low-altitude inspection planning method based on hazard analysis, comprising the following steps:

[0007] Step S1, obtaining UAV inspection route conditions, corresponding hazard occurrence position condition data, and safety range condition data;

[0008] Step S2, performing UAV route risk assessment based on the hazard occurrence position condition data and the safety range condition data;

[0009] Step S3, building collision danger of the UAV trajectory based on the building situation near the UAV trajectory;

[0010] Step S4, UAV route danger assessment based on the UAV route risk assessment result and the building collision danger of the UAV trajectory;

[0011] Step S5, UAV route selection based on the UAV route danger assessment result.

[0012] In an implementation manner of the present application, the UAV inspection route situation includes a pre-prepared inspection route trajectory situation, and the nearest distance of the building near the trajectory to the trajectory route, the height situation and the trajectory building density data are acquired, wherein the building data can be acquired from the municipal system by networking with the municipal system, the corresponding danger occurrence position situation data includes the environment situation data of the danger occurrence position, and the safety range situation data is the safety range situation and the danger level situation drawn by the emergency management department, and the depth of the UAV into the danger area and the danger situation of the UAV into the danger area can be acquired by acquiring the safety range situation drawn by the emergency management department.

[0013] In an implementation manner of the present application, the UAV route risk assessment in step S2 includes the following specific steps:

[0014] S21, acquiring the UAV alternative route situation, the environment situation of each area of the route and the depth of the UAV into the danger area;

[0015] S22, analyzing the abnormal influence of the environment of each area of the route on the UAV flight through the corresponding environment situation of each area of the route;

[0016] S23, acquiring the depth of the UAV into the danger area in each area, i.e. the distance from the danger area to the accident center point, the smaller the distance, the higher the danger degree, the influence of the danger area on the UAV is obtained by dividing the safety area distance by the depth of the UAV into the danger area in each area, the ratio of the safety area distance and the current position of the UAV is used to dynamically reflect the spatial proximity risk according to the distance attenuation effect;

[0017] S24, the UAV risk assessment result of the corresponding area is obtained by weighted summation of the abnormal influence of the environment of each area of the route on the UAV flight and the influence of the danger area on the UAV, the environmental abnormality and the danger depth are weighted and fused to realize multi-dimensional risk coupling analysis, which covers the sudden environmental threat and identifies the spatial hidden risk, when the danger occurs, the UAV is affected by the environment and the danger area, and the deviation is easy to cause collision with the surrounding buildings to cause secondary damage.

[0018] In an implementation form of the present application, the building collision risk of the UAV trajectory in step S3 comprises the following specific contents:

[0019] S31, obtain the UAV flight trajectory situation of each region, the nearest distance from the building near the trajectory to the trajectory route, the height situation and the building density data of the trajectory, obtain the UAV flight trajectory, building distance, height, density and other data, and establish an environment perception baseline, which provides basic spatial information for risk assessment;

[0020] S32, obtain the flight height variation and flight trajectory angle variation of the UAV in the region corresponding to the trajectory, input the flight height variation and flight trajectory angle variation into the UAV flight complexity evaluation formula to obtain the height complexity evaluation value and the trajectory angle complexity evaluation value, average the height complexity evaluation value and the trajectory angle complexity evaluation value of the trajectory in the corresponding region to obtain the height complexity evaluation value and the trajectory angle complexity evaluation value of the corresponding region, and weightedly sum the height complexity evaluation value and the trajectory angle complexity evaluation value of the corresponding region to obtain the flight complexity evaluation value of the corresponding region. Frequent height or angle changes will increase the risk of loss of control. The differential method is used to quantify the instantaneous change and standardize the processing, which can separate the height and angle risk sources and avoid the influence of unit difference. The regional mean value and weighted sum can comprehensively reflect the flight operation difficulty and provide a quantitative basis for subsequent risk assessment;

[0021] S33, obtain the building height situation of the flight region and the UAV flight height situation, and evaluate the flight height risk value of the region based on the building height situation of the flight region and the UAV flight height situation, that is, divide the average value of the building height of the flight region by the UAV flight height situation to obtain the flight height risk value of the corresponding region;

[0022] S34, obtain the trajectory building density data, and divide the regional trajectory building density data by the density safety value to obtain the building density risk value of the corresponding region;

[0023] S35, weightedly sum the flight complexity evaluation value, the flight height risk value and the building density risk value of the corresponding region to obtain the flight risk value of the corresponding region;

[0024] S36, obtain the nearest distance from the building near the trajectory to the trajectory route, divide the safety distance by the nearest distance from the building near the trajectory to the trajectory route to obtain the distance risk value, and weightedly sum the distance risk value and the flight risk value to obtain the building collision risk. The distance risk value is obtained by dividing the safety distance by the nearest building distance, and then combined with the weighted calculation of the flight risk value, which can comprehensively reflect the dynamic and static risks.

[0025] In an implementation form of the present application, the step S4 of evaluating the risk of the UAV route comprises the following specific contents:

[0026] S41, obtain the building collision risk result of each region on the path and the UAV risk evaluation result, sum them to obtain the UAV route risk of the corresponding region, divide the flight path into continuous regions, and through superimposing the building collision risk value and the dynamic risk evaluation result of each region, the comprehensive threat level of a single region can be quantified;

[0027] S42, sum the UAV route risk of each region on the path to obtain the UAV route risk evaluation result, and add up the risk values of all regions on the path to generate the global route risk evaluation result. This step reflects the overall risk exposure degree through linear aggregation, and supports horizontal comparison of different path schemes.

[0028] In an implementation form of the present application, the step S5 of selecting the UAV route comprises the following specific contents:

[0029] Obtain the risk evaluation results of all routes, arrange them in descending order, and select the planning route corresponding to the smallest risk evaluation result as the UAV route.

[0030] In a second aspect, the present application further provides a UAV low-altitude inspection planning system based on risk analysis, comprising:

[0031] A data acquisition module acquires data of a UAV inspection route, corresponding risk occurrence position, and safety range.

[0032] A route risk evaluation module evaluates the risk of the UAV route based on the data of the risk occurrence position and the safety range.

[0033] A building collision risk module evaluates the building collision risk of the UAV trajectory based on the building near the UAV trajectory.

[0034] A route risk evaluation module evaluates the risk of the UAV route based on the risk evaluation result of the UAV route and the building collision risk of the UAV trajectory.

[0035] A route selection module selects the UAV route based on the route risk evaluation result.

[0036] In a third aspect, the present application 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 risk analysis by calling the computer program stored in the memory.

[0037] In a fourth aspect, the present application provides a computer readable storage medium storing instructions, which, when executed on a computer, cause the computer to perform the unmanned aerial vehicle low-altitude inspection planning method based on risk analysis.

[0038] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0039] Firstly, in data acquisition, various data such as unmanned aerial vehicle inspection route, risk occurrence position, safety range and the like are comprehensively collected, laying a foundation for subsequent evaluation, in risk evaluation, the unmanned aerial vehicle route is evaluated in detail, the influence of environmental abnormalities and dangerous areas is combined, and the building collision danger is considered, the flight complexity evaluation, flight height danger and building density danger are calculated in multiple dimensions, the dynamic and static risks are comprehensively calculated, finally, the building collision danger and risk evaluation results of each area are combined to obtain the global route danger evaluation result, and the route with the minimum danger is selected, the whole scheme realizes multi-dimensional and comprehensive risk evaluation, considers various factors such as environment and building, meets the requirements of relevant standards, and can effectively reduce the flight risk of the unmanned aerial vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0040] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments with reference to the attached drawings:

[0041] Figure 1 It is a whole flow schematic diagram of the method embodiment 1 of the present application;

[0042] Figure 2 It is a flow schematic diagram of the S2 step of the method embodiment 1 of the present application;

[0043] Figure 3 It is a flow schematic diagram of the S3 step of the method embodiment 1 of the present application;

[0044] Figure 4 It is a structure schematic diagram of the system embodiment 2 of the present application. DETAILED DESCRIPTION

[0045] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0046] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from the description, and those skilled in the art can make similar generalizations without departing from the connotation of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0047] 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 in this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0048] Example 1

[0049] like Figures 1 to 3 As 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.

[0050] This embodiment provides a method for planning low-altitude UAV inspections based on hazard analysis, specifically including the following steps:

[0051] Step S1: Obtain data on the drone inspection route, the location of the corresponding hazard, and the safe zone.

[0052] 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.

[0053] 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;

[0054] In this embodiment, the drone route risk assessment in step S2 includes the following specific steps:

[0055] 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;

[0056] S22, analyze the abnormal influence of the environment of each area of the route on the flight of the unmanned aerial vehicle by the environment of the corresponding area of the route;

[0057] The specific content is: obtaining the environment of each area, obtaining the standard deviation of the environment of each area and the safe corresponding environment condition range of the corresponding unmanned aerial vehicle, obtaining the abnormality of each environment, obtaining the abnormal influence of the environment of each area on the flight of the unmanned aerial vehicle by weighted summation, quantifying the environmental mutation risk by calculating the standard deviation of the environmental parameters (wind speed, visibility, etc.) and the safety threshold and weighted summation, which is based on the probabilistic risk assessment model. Historical data shows that environmental abnormalities account for the main cause of accidents. The weighting strategy can adjust the sensitivity for different models. The value of the weight is obtained according to the historical data test;

[0058] S23, obtaining the depth of the unmanned aerial vehicle entering the dangerous area in each area, that is, the distance from the dangerous area to the accident center point. The smaller the distance, the higher the risk. The influence of the dangerous area on the unmanned aerial vehicle is obtained by dividing the safe area distance by the depth of the unmanned aerial vehicle entering the dangerous area in each area. The ratio of the safe area distance to the current position of the unmanned aerial vehicle dynamically reflects the spatial proximity risk according to the distance attenuation effect;

[0059] S24, weighted summation of the abnormal influence of the environment of each area on the flight of the unmanned aerial vehicle and the influence of the dangerous area on the unmanned aerial vehicle to obtain the risk assessment result of the unmanned aerial vehicle in the corresponding area. The environmental abnormality and the dangerous depth are weighted and fused to realize multi-dimensional risk coupling analysis, which covers both sudden environmental threats and hidden spatial risks. When the danger occurs, the unmanned aerial vehicle is affected by the environment and the dangerous area, and the deviation is easy to cause collision with surrounding buildings, resulting in secondary damage. Therefore, the building collision danger of the unmanned aerial vehicle trajectory is analyzed in step S3, and then the environmental and dangerous area influence is fused to evaluate the risk of the unmanned aerial vehicle being affected by the environment and the dangerous area, deviating to cause collision with surrounding buildings, resulting in secondary damage. Specifically, a large amount of unmanned aerial vehicle flight accident data is collected first, and the proportion of environmental abnormalities and the depth of entering the dangerous area in accidents is analyzed. For example, after analyzing 1000 unmanned aerial vehicle flight accident data, it is found that the proportion of accidents caused by environmental abnormalities is 60%, and the proportion of accidents caused by the depth of entering the dangerous area is 40%. Therefore, the weight of the abnormal influence of the environment of each area on the flight of the unmanned aerial vehicle can be set to 0.6, and the weight of the influence of the dangerous area on the unmanned aerial vehicle can be set to 0.4;

[0060] Step S3, building collision danger of unmanned aerial vehicle trajectory based on building conditions near the unmanned aerial vehicle trajectory;

[0061] In this embodiment, the building collision danger of the unmanned aerial vehicle trajectory in step S3 includes the following specific contents:

[0062] S31, obtain the unmanned aerial vehicle flight trajectory situation of each region, the nearest distance from the trajectory route to the building near the trajectory, the height situation and the building density of the trajectory, obtain the unmanned aerial vehicle flight trajectory, building distance, height, density and other data, and establish an environment perception baseline. This step provides basic spatial information for risk assessment, such as identifying high-risk areas such as urban canyons through building density, and predicting potential collision risks by combining building height and unmanned aerial vehicle flight height to ensure the accuracy of subsequent assessment;

[0063] S32, obtain the flight height variation of the unmanned aerial vehicle in the region corresponding to the trajectory and the flight trajectory angle variation of the unmanned aerial vehicle, and input the flight height variation and the flight trajectory angle variation into the unmanned aerial vehicle flight complexity evaluation formula to obtain the height complexity evaluation value and the trajectory angle complexity evaluation value. The unmanned aerial vehicle flight complexity evaluation formula for the i-th position is: Wherein, si is the flight height situation and flight trajectory angle situation of the i-th position, s(i-1) is the flight height situation and flight trajectory angle situation of the previous position, and sc is the set variation safety value. The variation safety value is the flight height variation situation and flight trajectory angle variation situation that will not affect the flight safety. The height data and the trajectory angle data are substituted respectively, not together. The output of the substituted height data is the height complexity evaluation value, and the output of the substituted trajectory angle data is the trajectory angle complexity evaluation value. The height complexity evaluation value and the trajectory angle complexity evaluation value of the corresponding region are averaged respectively to obtain the height complexity evaluation value and the trajectory angle complexity evaluation value of the corresponding region. The height complexity evaluation value and the trajectory angle complexity evaluation value of the corresponding region are weighted and summed to obtain the flight complexity evaluation value of the corresponding region. Frequent height or angle changes will increase the risk of loss of control (such as sharp turns or wind speed interference). The differential method is used to quantify the instantaneous change and standardize the processing, which can separate the height 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;

[0064] S33, obtain the building height situation of the flight region and the unmanned aerial vehicle flight height situation, and evaluate the regional flight height danger value based on the building height situation of the flight region and the unmanned aerial vehicle flight height situation, that is, by dividing the average value of the building height of the flight region by the unmanned aerial vehicle flight height situation to obtain the flight height danger value of the corresponding region. When the height of the unmanned aerial vehicle is lower than the average height of the building, the collision probability is significantly increased. The ratio (average building height / unmanned aerial vehicle height) directly quantifies the space compression risk;

[0065] S34, obtain the track building density data, divide the regional track building density data by the density safety value to obtain the building density risk 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, the suburban area can reduce the safety threshold to 5 buildings / km2, thereby flexibly adapting to the obstacle avoidance needs of different scenes;

[0066] S35, the flight risk value of the corresponding region is obtained by weighted sum of the flight complexity evaluation value, the flight height risk value and the building density risk value of the corresponding region;

[0067] S36, obtain the nearest distance from the buildings near the regional track to the track route, divide the safety distance by the nearest distance from the buildings near the regional track to the track route to obtain the distance risk value, and obtain the building collision risk by weighted sum of the distance risk value and the flight risk value, obtain the distance risk value by safety distance / nearest building distance, and combine the flight risk value for weighted calculation, which can comprehensively reflect the dynamic and static risks. As for the flight speed, the flight speed of the same kind of unmanned aerial vehicle is roughly the same in urban areas, so the influence of flight speed does not need to be considered. The weighted weight is also determined according to historical data and actual flight scene test. For the weighting of the flight complexity evaluation value, the flight height risk value and the building density risk value of the corresponding region, collect unmanned aerial vehicle and building collision accident data in different scenes, analyze the role of each factor in the accident, and assume that in the urban high-rise dense area, after analyzing 500 collision accidents, the flight complexity evaluation value accounts for 30% of the accidents, the flight height risk value accounts for 40%, and the building density risk value accounts for 30%. Therefore, the flight complexity evaluation value weight is 0.3, the flight height risk value weight is 0.4, and the building density risk value weight is 0.3. For the weighting of the distance risk value and the flight risk value, if it is found through analysis that the distance factor accounts for 60% of the collision accidents, and the flight risk value factor accounts for 40%, then the distance risk value weight is 0.6, and the flight risk value weight is 0.4;

[0068] Step S4, based on the unmanned aerial vehicle route risk evaluation result and the building collision risk of the unmanned aerial vehicle track, evaluate the risk of the unmanned aerial vehicle route;

[0069] In this embodiment, the unmanned aerial vehicle route risk evaluation in step S4 includes the following specific contents:

[0070] S41, obtain the building collision danger result of each region on the path and the UAV risk assessment result, sum them to obtain the UAV route danger of the corresponding region, divide the flight path into continuous regions, and superimpose the building collision danger value and the dynamic risk assessment result (such as wind speed, visibility, etc.) of each region to quantize the comprehensive threat level of a single region. The weighting weight can be obtained based on the comprehensive analysis of the environment, dangerous region, and building collision factors in different regional flight accidents. For example, in an industrial park, after analyzing 300 UAV accidents, it is found that the building collision factor accounts for 55% of the accidents, and the environment and dangerous region factor accounts for 45% of the accidents. Therefore, the building collision danger result weight can be set to 0.55, and the UAV risk assessment result weight can be set to 0.45.

[0071] S42, sum the UAV route danger of each region on the path to obtain the UAV route danger assessment result, and add up the danger values of all regions on the path to generate the global route danger assessment result. This step reflects the overall risk exposure degree (such as higher total score for routes in urban dense areas) through linear aggregation, supporting horizontal comparison of different path schemes.

[0072] Step S5, selecting a UAV route based on the UAV route danger assessment result.

[0073] In this embodiment, the selection of the UAV route in step S5 includes the following specific contents:

[0074] Obtain the danger assessment result of all routes, arrange them in descending order, and select the planning route corresponding to the smallest danger assessment result as the UAV route.

[0075] It should be noted in this embodiment that the embodiment has the following benefits and advantages: In data acquisition, comprehensive collection of UAV inspection routes, hazard occurrence positions, safety ranges, and other data lays a foundation for subsequent evaluation. In risk assessment, the UAV route is evaluated in detail, combined with environmental abnormal influence and dangerous region influence, and considering building collision danger, from multi-dimensional calculation of flight complexity evaluation, flight height danger, and building density danger, comprehensive dynamic and static risk, finally, the building collision danger of each region and the risk assessment result are combined to obtain the global route danger assessment result, and the route with the smallest danger is selected accordingly. The whole scheme realizes multi-dimensional and comprehensive risk assessment, taking into account multiple factors such as environment and buildings, meets the requirements of relevant standards, and can effectively reduce the UAV flight risk.

[0076] Embodiment 2

[0077] As Figure 3As shown, the embodiment provides a UAV low-altitude inspection planning system based on risk analysis, which is realized based on the UAV low-altitude inspection planning method based on risk analysis in embodiment 1, and includes: a data acquisition module that acquires data about a UAV inspection route, corresponding risk occurrence positions, and safety ranges;

[0078] a route risk assessment module that performs UAV route risk assessment based on the data about risk occurrence positions and safety ranges;

[0079] a building collision danger module that performs building collision danger of a UAV trajectory based on building conditions near the UAV trajectory;

[0080] a route danger assessment module that performs UAV route danger assessment based on the UAV route risk assessment result and the building collision danger of the UAV trajectory;

[0081] a route selection module that performs UAV route selection based on the UAV route danger assessment result, and the specific steps of each module of the embodiment of the system are the same as the specific steps of the method embodiment of embodiment 1, and will not be repeated here.

[0082] Embodiment 3

[0083] An electronic device according to an embodiment of the present application 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 risk analysis by calling the computer program stored in the memory. It should be noted that all computer programs of the UAV low-altitude inspection planning method based on risk analysis are realized using C language.

[0084] Embodiment 4

[0085] The embodiment provides a computer-readable storage medium having an erasable computer program stored thereon.

[0086] When the computer program runs on the computer device, the computer device executes the UAV low-altitude inspection planning method based on risk analysis described above.

[0087] The above-described embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented by software, the above-described embodiments can be implemented in whole or in part in the form of a computer program product. The 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, the processes or functions according to the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center, etc. containing one or more available medium collections. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0088] Those skilled in the art can understand that the units and algorithm steps of the examples described in combination with the embodiments disclosed in the present application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the 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 implementation should not be considered beyond the scope of the present application.

[0089] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device, and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0090] In several embodiments provided by the present application, it should be understood that the disclosed system, device, and method can be implemented in other ways. For example, the above-described device embodiments are merely schematic, for example, the division of units is only one, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices, or units, which can be electrical, mechanical, or other forms.

[0091] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may be distributed to multiple network units. Part or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.

[0092] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit.

[0093] In the description of the present specification, the description referring to the terms "one embodiment", "an example", "a specific example" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0094] The basic principles and main features of the present application and the advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only illustrative of the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for planning a low-altitude inspection of a UAV based on risk analysis, characterized in that, Comprise the following steps: Step S1, obtaining the unmanned aerial vehicle inspection route situation, corresponding dangerous situation data and safety range data; Step S2, based on the dangerous situation data and safety range data, the unmanned aerial vehicle route risk assessment; Step S3, based on the building near the unmanned aerial vehicle trajectory, the building collision danger analysis of the unmanned aerial vehicle trajectory; The building collision danger analysis of the unmanned aerial vehicle trajectory comprises the following specific contents: S31, obtaining the unmanned aerial vehicle flight trajectory situation of each region, the nearest distance from the building near the trajectory to the trajectory route, the height situation and the trajectory building density data; S32, obtain the flight height change situation and the flight trajectory angle change situation of the unmanned aerial vehicle corresponding to the region, and import the flight height change situation and the flight trajectory angle change situation into the unmanned aerial vehicle flight complexity evaluation formula to obtain a height complexity evaluation value and a trajectory angle complexity evaluation value, wherein the unmanned aerial vehicle flight complexity evaluation formula of the i-th position is: Wherein, si is the flight height situation and the flight trajectory angle situation of the i-th position, s(i-1) is the flight height situation and the flight trajectory angle situation of the previous position, sc is a set change safety value, the height complexity evaluation value and the trajectory angle complexity evaluation value corresponding to the region are averaged respectively to obtain a height complexity evaluation value and a trajectory angle complexity evaluation value of the corresponding region, and the height complexity evaluation value and the trajectory angle complexity evaluation value of the corresponding region are weighted and summed to obtain a flight complexity evaluation value of the corresponding region. S33, obtaining the building height situation of the flight region and the unmanned aerial vehicle flight height situation, based on the building height situation of the flight region and the unmanned aerial vehicle flight height situation, the region flight height danger value is evaluated; S34, obtaining the trajectory building density data, and obtaining the building density danger value of the corresponding region by dividing the region trajectory building density data by the density safety value; S35, the flight complex evaluation value, the flight height danger value, the building density danger value of the corresponding region are weighted and summed to obtain the flight danger value of the corresponding region; S36, obtaining the nearest distance from the building near the trajectory to the trajectory route, dividing the safety distance by the nearest distance from the building near the trajectory to the trajectory route to obtain the distance danger value, and obtaining the building collision danger by weighted sum of the distance danger value and the flight danger value; Step S4, based on the unmanned aerial vehicle route risk assessment result and the building collision danger of the unmanned aerial vehicle trajectory, the unmanned aerial vehicle route danger assessment is carried out; Step S5, based on the unmanned aerial vehicle route danger assessment result, the unmanned aerial vehicle route selection is carried out. 2.The method of claim 1, wherein, The unmanned aerial vehicle route risk assessment comprises the following specific steps: S21, obtaining the unmanned aerial vehicle candidate route situation, and the environment situation of each region of the route and the depth of the unmanned aerial vehicle entering the danger region; S22, analyzing the abnormal influence of the environment of each region of the route on the unmanned aerial vehicle flight through the environment situation of each region of the corresponding route; S23, obtaining the depth of the unmanned aerial vehicle entering the danger region in each region, and obtaining the influence of the danger region on the unmanned aerial vehicle by dividing the safety zone distance by the depth of the unmanned aerial vehicle entering the danger region in each region; S24, the influence of the region environment on the unmanned aerial vehicle flight and the influence of the danger region on the unmanned aerial vehicle are weighted and summed to obtain the unmanned aerial vehicle risk assessment result of the corresponding region. 3.The method of claim 2, wherein, The unmanned aerial vehicle route danger assessment comprises the following specific contents: S41, obtaining the building collision danger result of each region on the path and the unmanned aerial vehicle risk assessment result, summing to obtain the unmanned aerial vehicle route danger of the corresponding region; S42, the unmanned aerial vehicle route danger of each region on the path is summed to obtain the unmanned aerial vehicle route danger assessment result. 4.The risk analysis based UAV low-altitude patrol planning method of claim 3, wherein, The unmanned aerial vehicle route selection comprises the following specific contents: Obtaining the danger assessment result of all routes, arranging in descending order, selecting the planning route corresponding to the smallest danger assessment result as the unmanned aerial vehicle route. 5.The risk analysis based UAV low-altitude patrol planning method of claim 2, wherein, The specific content of the analysis of the abnormal influence of the environment of each area of the route on the flight of the unmanned aerial vehicle by the environment of each area of the corresponding route is: obtaining the environment of each area, obtaining the standard deviation of the environment of each area and the safe corresponding environment condition range of the corresponding unmanned aerial vehicle, obtaining the abnormality of each environment, and obtaining the abnormal influence of the environment of each area on the flight of the unmanned aerial vehicle by weighted summation of the abnormality of each environment. 6.The risk analysis based UAV low-altitude patrol planning method of claim 1, wherein, The unmanned aerial vehicle inspection route condition includes a prepared inspection route trajectory condition, and the nearest distance from the trajectory to the building, the height condition and the trajectory building density data are obtained. The corresponding dangerous situation position condition data includes the environment condition data of the dangerous situation position, and the safety range condition data is the safety range condition and the danger level condition drawn by the emergency management department.

7. The unmanned aerial vehicle low-altitude patrol planning system based on risk analysis, used to realize the unmanned aerial vehicle low-altitude patrol planning method based on risk analysis in any one of claims 1-6, characterized in that, The system comprises: a data acquisition module for acquiring the unmanned aerial vehicle inspection route condition, the corresponding dangerous situation position condition data and the safety range condition data; a route risk assessment module for assessing the route risk of the unmanned aerial vehicle based on the dangerous situation position condition data and the safety range condition data; a building collision danger module for analyzing the building collision danger of the unmanned aerial vehicle trajectory based on the building condition near the trajectory; a route danger assessment module for assessing the danger of the route of the unmanned aerial vehicle based on the route risk assessment result and the building collision danger of the unmanned aerial vehicle trajectory; a route selection module for selecting the route of the unmanned aerial vehicle based on the route danger assessment result.

8. 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 unmanned aerial vehicle low-altitude inspection planning method based on the dangerous situation analysis according to any one of claims 1-6 by calling the computer program stored in the memory.

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