A UAV mapping and surveying service management system

Abstract

The present invention relates to the technical field of UAV surveying and mapping, and proposes a UAV surveying and mapping service management system, including a service center. A server is arranged in the service center, and a flight altitude prediction system, a flight decision-making system, and an image clarity evaluation system are arranged in the server. The flight altitude prediction system and the image clarity evaluation system are both connected to the flight decision-making system through data transmission technology. The flight altitude prediction system predicts the altitude that the UAV needs to adjust and automatically generates an instruction to change the flight design route, realizing the automatic change of the UAV flight design route. The image clarity evaluation system evaluates the images captured by the UAV and generates an instruction to change the UAV flight plan route, realizing the improvement of the accuracy of the captured images during the safe flight of the UAV.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV surveying and mapping, and particularly to a UAV surveying and mapping service management system. Background Art

[0002] At present, during geological surveying and mapping, through land ownership investigation and cadastral survey, the ownership, boundaries, area, use, location, etc. of each piece of land are found out, and survey data such as cadastral survey data and drawings are formed. Generally, UAVs are used to measure and map the geology. However, since the specific geological conditions to be measured and mapped are unknown, or the current specific geological conditions have changed and do not match the historical geological conditions, the flight state of the UAV is judged by the operator throughout the process, which may easily lead to the following two situations during the flight measurement and mapping of the UAV:

[0003] 1. To ensure the safety of the UAV flight, the operator raises the flight altitude of the UAV too high, resulting in the inability to guarantee the clarity of the captured images;

[0004] 2. To ensure the clarity of the captured images, the operator lowers the flight altitude of the UAV too low, resulting in the UAV being unable to continuously fly at a safe flight altitude, and the UAV is prone to crashing.

[0005] Therefore, we make improvements in this regard and propose a UAV surveying and mapping service management system. Summary of the Invention

[0006] (1) The technical problem to be solved by the present invention is to automatically control the safe flight altitude of the UAV while ensuring the clarity of the captured images, and avoid the situation that the images captured by the UAV are unclear due to manual control, or the UAV cannot continuously fly within the safe flight altitude, resulting in the crash of the UAV.

[0007] Technical Solution

[0008] To achieve the above-mentioned invention purpose, the present invention provides a UAV surveying and mapping service management system, including a service center, a server is arranged in the service center, a flight altitude prediction system, a flight decision-making system and an image clarity evaluation system are arranged in the server, and both the flight altitude prediction system and the image clarity evaluation system are connected to the flight decision-making system through data transmission technology;

[0009] The flight altitude prediction system includes an obstacle perception module, an obstacle scanning module, a distance detection module, a BIM model establishment module, a flight altitude calculation module, a flight trajectory acquisition module, a flight trajectory prediction module, a data comparison module, and an instruction generation module 1. The obstacle perception module is used to perceive ground obstacles during the flight of the unmanned aerial vehicle (UAV). The obstacle perception module is connected to the obstacle scanning module and the distance detection module through a controller, and is used to start the obstacle scanning module and the distance detection module to scan and measure the distance of the obstacle when the UAV perceives an obstacle within the safe flight range. The obstacle scanning module and the distance detection module are both connected to the BIM model establishment module through data transmission technology, and are used to transmit the scanned and distance-measured data to the BIM model establishment module for modeling. The BIM model establishment module is connected to the flight altitude calculation module through data transmission technology, and is used to calculate the safe flight altitude of the obstacle. The flight trajectory acquisition module is used to acquire the historical flight trajectory of the UAV. The flight trajectory acquisition module is connected to the flight trajectory prediction module through data transmission technology, and is used to predict the future flight altitude of the UAV. The flight altitude calculation module and the flight trajectory prediction module are both connected to the data comparison module through data transmission technology. The data comparison module is connected to the instruction generation module 1 through data transmission technology, and is used to compare the prediction results of the flight altitude calculation module and the flight trajectory prediction module, and generate a flight instruction for controlling the UAV.

[0010] Preferably, after the BIM model establishment module establishes the BIM model, the flight altitude calculation module calculates the minimum flight altitude passing through the obstacle according to the BIM model established by the BIM model establishment module. The minimum flight altitude h kz The calculation formula is as follows

[0011]

[0012] In the formula, h w is the current flight altitude of the UAV;

[0013] d wG is the horizontal distance between the current flight altitude of the UAV and the highest point G of the obstacle;

[0014] d wz is the horizontal distance between the current flight altitude of the UAV and the highest point G of the obstacle after 2s.

[0015] Preferably, the image clarity evaluation system includes an image acquisition module, a training image database, a category analysis module, an SVM classifier, an image processing module, an image analysis module, a weight ratio calculation module, an image evaluation module, and an instruction generation module II. The image acquisition module and the training image database are both connected to the SVM classifier through data transmission technology, and are used to send the images acquired by the UAV and the training images in the training image database into the SVM classifier for classification. The SVM classifier is connected to the image processing module through data transmission technology, and is used to send the classified images into the image processing module for preprocessing the images. The image processing module is connected to the image analysis module through data transmission technology, and is used to send the processed images into the image analysis module to analyze the brightness, contrast, and structure of the images. The image analysis module is connected to the weight ratio calculation module through data transmission technology, and is used to transmit the analyzed data into the weight ratio calculation module to calculate the weight ratio of the images. The weight ratio calculation module is connected to the image evaluation module through data transmission technology, and is used to send the analysis results and the weight ratio calculation results into the image evaluation module to comprehensively evaluate the images. The image evaluation module is connected to the instruction generation module II through data transmission technology, and is used to send the evaluation results into the instruction generation module II to generate instructions for the flight of the UAV according to the evaluation results.

[0016] Preferably, the training image database is also connected to the category analysis module through data transmission technology, and the category analysis module is connected to the SVM classifier through data transmission technology, and is used to perform category analysis on the training images in the training image database and send the analysis results into the SVM classifier to facilitate the SVM classifier to quickly classify the images.

[0017] Preferably, the specific analysis calculation formulas of the image analysis module for the image brightness l(x, y), contrast c(x, y), and structure s(x, y) are as follows

[0018]

[0019] where L is the dynamic change of pixel values;

[0020] K 1 , K 2 , K 3 << 1;

[0021] μ x , μ y is the estimated value of the brightness mean;

[0022] σ x , σ y is the estimated value of the standard variance of the contrast.

[0023] Preferably, the weight ratio calculation formula of the weight ratio calculation module is as follows

[0024]

[0025] In the formula, N is a natural number and N > 1.

[0026] Preferably, the formula for the image evaluation module to evaluate the image is

[0027] W(x, y) = [l(x, y)] α ·[c(x, y)] β ·[s(x, y)] γ

[0028] In the formula, α, β, γ > 1, and they are three parameters for weighting and adjusting brightness, contrast, and structural information.

[0029] Preferably, the flight decision system includes an instruction acquisition module, an instruction prediction module, an instruction comparison module, and an instruction execution module. The instruction acquisition module is used to acquire the flight instructions sent by the service center to the UAV and adjust the flight altitude of the UAV. The instruction acquisition module is connected to the instruction prediction module through data transmission technology and is used to further predict the received instructions. The instruction prediction module is connected to the instruction execution module through data transmission technology and is used to execute the instructions.

[0030] Preferably, the instruction acquisition module is also connected to the instruction comparison module through data transmission technology. The instruction comparison module is connected to the instruction prediction module through data transmission technology. The instruction prediction module is connected to the instruction execution module through data transmission technology and is used to compare the priorities of the instructions when receiving the instructions sent by instruction generation module one and instruction generation module two simultaneously.

[0031] (III) Beneficial effects

[0032] The beneficial effects of the UAV mapping and surveying service management system provided by the present invention are as follows:

[0033] 1. During the flight of the UAV, obstacles on the flight design route are scanned, and the scanning results are sent to the server in the service center. The flight altitude prediction system in the server predicts the altitude that the UAV needs to adjust and automatically generates instructions to change the flight design route, realizing the automatic change of the UAV flight design route, avoiding inaccurate calculation of the UAV flight route due to insufficient accuracy of human judgment, resulting in the UAV changing the flight route prematurely or lagging behind, and further causing unclear shooting pictures or the UAV crashing.

[0034] 2. During the UAV mapping and surveying process, the image clarity evaluation system in the server calculates the brightness, contrast, and structural information of the captured images, performs weighted calculations on the calculation results, and then generates a change instruction for the UAV flight plan route based on the brightness, contrast, structural information, and the weighted calculation results. When the captured image is not clear, the UAV is controlled to automatically change the flight plan route, achieving the improvement of the accuracy of the captured images while ensuring the safe flight of the UAV.

[0035] 3. When changing the flight plan route during the UAV flight, the flight route is predicted, and when two groups of route change instructions from the instruction generation module 1 and the instruction generation module 2 are received simultaneously, the priorities of the instructions are compared, ensuring the safe flight of the UAV when the UAV changes its flight plan and improving the quality of the geological survey and mapping results of the UAV. Brief Description of the Drawings

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0037] Figure 1 It is a schematic diagram of the overall system of a UAV mapping and surveying service management system provided by this application;

[0038] Figure 2 It is a schematic diagram of the flight altitude prediction system of a UAV mapping and surveying service management system provided by this application;

[0039] Figure 3 It is a schematic diagram of the image clarity evaluation system of a UAV mapping and surveying service management system provided by this application;

[0040] Figure 4 It is a schematic diagram of the flight decision-making system of a UAV mapping and surveying service management system provided by this application;

[0041] Figure 5 It is a schematic diagram of the UAV flight controllability analysis of a UAV mapping and surveying service management system provided by this application.

[0042] In the figure: 1. Service center; 2. Server; 3. Flight altitude prediction system; 4. Flight decision-making system; 5. Image clarity evaluation system; 6. Obstacle perception module; 7. Obstacle scanning module; 8. Distance detection module; 9. BIM model establishment module; 10. Flight altitude calculation module; 11. Flight trajectory acquisition module; 12. Flight trajectory prediction module; 13. Data comparison module; 14. Instruction generation module 1; 15. Image acquisition module; 16. Training image database; 17. Category analysis module; 18. SVM classifier; 19. Image processing module; 20. Image analysis module; 21. Weight ratio calculation module; 22. Image evaluation module; 23. Instruction generation module 2; 24. Instruction acquisition module; 25. Instruction prediction module; 26. Instruction comparison module; 27. Instruction execution module. Specific implementation manner

[0043] The following further describes in detail the specific implementation manner of the present invention in conjunction with the accompanying drawings of the specification and embodiments. The following embodiments are only used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0044] As Figures 1-5 shown, this implementation manner proposes a UAV mapping and surveying service management system, including a service center 1, characterized in that: a server 2 is provided in the service center 1, and a flight altitude prediction system 3, a flight decision-making system 4, and an image clarity evaluation system 5 are provided in the server 2. Both the flight altitude prediction system 3 and the image clarity evaluation system 5 are connected to the flight decision-making system 4 through data transmission technology;

[0045] The flight altitude prediction system 3 includes an obstacle perception module 6, an obstacle scanning module 7, a distance detection module 8, a BIM model establishment module 9, a flight altitude calculation module 10, a flight trajectory acquisition module 11, a flight trajectory prediction module 12, a data comparison module 13, and an instruction generation module 14. The obstacle perception module 6 is used to perceive ground obstacles during the flight of the UAV. The obstacle perception module 6 is connected to the obstacle scanning module 7 and the distance detection module 8 through a controller, and is used to start the obstacle scanning module 7 and the distance detection module 8 to scan and measure the distance of the obstacle when the UAV perceives an obstacle within the safe flight range. The obstacle scanning module 7 and the distance detection module 8 are both connected to the BIM model establishment module 9 through data transmission technology, and are used to transmit the scanned and distance-measured data to the BIM model establishment module 9 for modeling. The BIM model establishment module 9 is connected to the flight altitude calculation module 10 through data transmission technology, and is used to calculate the safe flight altitude of the obstacle. The flight trajectory acquisition module 11 is used to acquire the historical flight trajectory of the UAV. The flight trajectory acquisition module 11 is connected to the flight trajectory prediction module 12 through data transmission technology, and is used to predict the future flight altitude of the UAV. The flight altitude calculation module 10 and the flight trajectory prediction module 12 are both connected to the data comparison module 13 through data transmission technology. The data comparison module 13 is connected to the instruction generation module 14 through data transmission technology, and is used to compare the prediction results of the flight altitude calculation module 10 and the flight trajectory prediction module 12, and generate a flight instruction for controlling the UAV.

[0046] In this embodiment, after the BIM model establishment module 9 establishes the BIM model, the flight altitude calculation module 10 calculates the minimum flight altitude passing through the obstacle according to the BIM model established by the BIM model establishment module 9. The minimum flight altitude h kz The calculation formula is as follows

[0047]

[0048] In the formula, h w is the current flight altitude of the UAV;

[0049] d wG is the horizontal distance between the current flight altitude of the UAV and the highest point G of the obstacle;

[0050] d wz is the horizontal distance between the current flight altitude of the UAV and the highest point G of the obstacle after 2s.

[0051] During the flight of the drone, the present invention scans obstacles on the designed flight route and sends the scanning results to the server 2 in the service center 1. The flight altitude prediction system 3 in the server 2 predicts the altitude that the drone needs to adjust and automatically generates an instruction to change the designed flight route, realizing the automatic change of the drone's designed flight route and avoiding the inaccurate calculation of the drone's flight route due to insufficient accuracy of human judgment, which may cause the drone to change the flight route prematurely or lag, resulting in unclear captured images or the crash of the drone.

[0052] The image clarity evaluation system 5 includes an image acquisition module 15, a training image database 16, a category analysis module 17, an SVM classifier 18, an image processing module 19, an image analysis module 20, a weight ratio calculation module 21, an image evaluation module 22, and an instruction generation module two 23. The image acquisition module 15 and the training image database 16 are both connected to the SVM classifier 18 through data transmission technology, and are used to send the images acquired by the drone and the training images in the training image database 16 to the SVM classifier 18 for classification. The SVM classifier 18 is connected to the image processing module 19 through data transmission technology, and is used to send the classified images to the image processing module 19 for preprocessing the images. The image processing module 19 is connected to the image analysis module 20 through data transmission technology, and is used to send the processed images to the image analysis module 20 to analyze the brightness, contrast, and structure of the images. The image analysis module 20 is connected to the weight ratio calculation module 21 through data transmission technology, and is used to transmit the analyzed data to the weight ratio calculation module 21 to calculate the weight ratio of the images. The weight ratio calculation module 21 is connected to the image evaluation module 22 through data transmission technology, and is used to send the analysis results and the weight ratio calculation results to the image evaluation module 22 to comprehensively evaluate the images. The image evaluation module 22 is connected to the instruction generation module two 23 through data transmission technology, and is used to send the evaluation results to the instruction generation module two 23 to generate instructions for the drone to fly according to the evaluation results.

[0053] In this embodiment, the training image database 16 is also connected to the category analysis module 17 through data transmission technology, and the category analysis module 17 is connected to the SVM classifier 18 through data transmission technology, and is used to perform category analysis on the training images in the training image database 16 and send the analysis results to the SVM classifier 18 to facilitate the SVM classifier 18 to quickly classify the images.

[0054] In this embodiment, the specific analysis calculation formulas of the image analysis module 20 for the image brightness l(x,y), contrast c(x,y), and structure s(x,y) are as follows

[0055]

[0056]

[0057] Wherein, L is the dynamic change of pixel values;

[0058] K 1 , K 2 , K 3 << 1;

[0059] μ x , μ y is the estimated value of the average brightness;

[0060] σ x , σ y is the estimated value of the standard variance of the contrast.

[0061] In this embodiment, the weight ratio calculation formula of the weight ratio calculation module 21 is as follows

[0062]

[0063] Wherein, N is a natural number, and N > 1.

[0064] In this embodiment, the calculation formula for the evaluation value of the image by the image evaluation module 22 is

[0065] W(x, y) = [l(x, y)] α ·[c(x, y)] β ·[s(x, y)] γ

[0066] Wherein, α, β, γ > 1, and are three parameters for weighting and adjusting the brightness, contrast, and structural information.

[0067] In the present invention, during the process of unmanned aerial vehicle (UAV) mapping and surveying, the image clarity evaluation system 5 in the server 2 calculates the brightness, contrast, and structural information of the captured image, performs weighted calculation on the calculation results, and then generates a change instruction for the UAV flight plan route based on the brightness, contrast, structural information, and the weighted calculation results, controlling the UAV to automatically change the flight plan route when the captured image is not clear, thereby achieving the improvement of the accuracy of the captured image during the process of ensuring the safe flight of the UAV.

[0068] The flight decision-making system 4 includes an instruction acquisition module 24, an instruction prediction module 25, an instruction comparison module 26, and an instruction execution module 27. The instruction acquisition module 24 is used to acquire the flight instructions sent by the service center 1 to the UAV and adjust the flight altitude of the UAV. The instruction acquisition module 24 is connected to the instruction prediction module 25 through data transmission technology and is used to further predict the received instructions. The instruction prediction module 25 is connected to the instruction execution module 27 through data transmission technology and is used to execute the instructions.

[0069] In this embodiment, the instruction acquisition module 24 is also connected to the instruction comparison module 26 through data transmission technology. The instruction comparison module 26 is connected to the instruction prediction module 25 through data transmission technology. The instruction prediction module 25 is connected to the instruction execution module 27 through data transmission technology and is used to compare the priorities of the instructions when receiving the instructions sent by the instruction generation module 1 14 and the instruction generation module 2 23 at the same time.

[0070] In the present invention, when changing the flight plan route during the flight of the UAV, the flight route is predicted, and when receiving two groups of route change instructions from the instruction generation module 1 14 and the instruction generation module 2 23 at the same time, the priorities of the instructions are compared, so as to ensure the safe flight of the UAV when the UAV changes the flight plan and improve the quality of the geological survey and mapping results of the UAV.

[0071] The above embodiments are only used to illustrate the present invention, rather than to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, those of ordinary skill in the art should understand that various combinations, modifications or equivalent replacements of the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention and should all be covered by the scope of the claims of the present invention.

Claims

1. An unmanned aerial vehicle surveying and mapping service management system, comprising a service center (1), characterized in that: The service center (1) is provided with a server (2), the server (2) is provided with a flight altitude prediction system (3), a flight decision system (4) and an image clarity evaluation system (5), and the flight altitude prediction system (3) and the image clarity evaluation system (5) are both connected to the flight decision system (4) via data transmission technology; The flight altitude prediction system (3) comprises an obstacle perception module (6), an obstacle scanning module (7), a distance detection module (8), a BIM model establishment module (9), a flight altitude calculation module (10), a flight trajectory acquisition module (11), a flight trajectory prediction module (12), a data comparison module (13) and an instruction generation module (14). The obstacle perception module (6) is used for the unmanned aerial vehicle to perceive obstacles on the ground during flight. The obstacle perception module (6) is connected to the obstacle scanning module (7) and the distance detection module (8) through a controller. When the unmanned aerial vehicle perceives an obstacle within a safe flight range, the obstacle scanning module (7) and the distance detection module (8) are started to scan and measure the distance of the obstacle. The obstacle scanning module (7) and the distance detection module (8) are connected to the BIM model establishment module (9) through data transmission technology. The data of scanning and ranging are transmitted to a BIM model building module (9) for modeling. The BIM model building module (9) is connected to a flight altitude calculation module (10) through a data transmission technology and is used to calculate a safe flight altitude after passing through obstacles. The flight trajectory acquisition module (11) is used to acquire a historical flight trajectory of the UAV. The flight trajectory acquisition module (11) is connected to a flight trajectory prediction module (12) through a data transmission technology and is used to predict the future flight altitude of the UAV. The flight altitude calculation module (10) and the flight trajectory prediction module (12) are both connected to a data comparison module (13) through a data transmission technology. The data comparison module (13) is connected to an instruction generation module (14) through a data transmission technology and is used to compare the prediction results of the flight altitude calculation module (10) and the flight trajectory prediction module (12) and generate a flight instruction for controlling the UAV.

2. The unmanned aerial vehicle surveying and mapping service management system according to claim 1 is characterized by: After the BIM model building module (9) builds the BIM model, the flight altitude calculation module (10) calculates the minimum flight altitude for passing through obstacles based on the BIM model built by the BIM model building module (9). The minimum flight altitude h kz The calculation formula is as follows In the formula, h w The current flight altitude of the drone; d wG It is the horizontal distance between the current flight altitude of the drone and the highest point of the obstacle G; d wz It is the horizontal distance between the current flight altitude of the UAV and the highest point G of the obstacle after 2s.

3. The unmanned aerial vehicle surveying and mapping service management system according to claim 1 is characterized by: The image clarity evaluation system (5) comprises an image acquisition module (15), a training image database (16), a category analysis module (17), an SVM classifier (18), an image processing module (19), an image analysis module (20), a weight ratio calculation module (21), an image evaluation module (22) and a second instruction generation module (23). The image acquisition module (15) and the training image database (16) are both connected to the SVM classifier (18) via a data transmission technology, and are used to send images acquired by the drone and training images in the training image database (16) to the SVM classifier (18) for classification. The SVM classifier (18) is connected to the image processing module (19) via a data transmission technology, and is used to send the classified images to the image processing module (19) for image preprocessing. 19) is connected to the image analysis module (20) through data transmission technology, and is used to send the processed image to the image analysis module (20) to analyze the brightness, contrast and structure of the image. The image analysis module (20) is connected to the weight ratio calculation module (21) through data transmission technology, and is used to transmit the analyzed data to the weight ratio calculation module (21) to calculate the weight ratio of the image. The weight ratio calculation module (21) is connected to the image evaluation module (22) through data transmission technology, and is used to send the analysis result and the weight ratio calculation result to the image evaluation module (22) to perform a comprehensive evaluation on the image. The image evaluation module (22) is connected to the instruction generation module 2 (23) through data transmission technology, and is used to send the evaluation result to the instruction generation module 2 (23), and generate the UAV flight instruction according to the evaluation result.

4. The unmanned aerial vehicle surveying and mapping service management system according to claim 3 is characterized by: The training image database (16) is also connected to the category analysis module (17) through data transmission technology, and the category analysis module (17) is connected to the SVM classifier (18) through data transmission technology, and is used to perform category analysis on the training images in the training image database (16) and send the analysis results to the SVM classifier (18), so that the SVM classifier (18) can quickly classify the images.

5. The unmanned aerial vehicle surveying and mapping service management system according to claim 3 is characterized by: The image analysis module (20) specifically analyzes and calculates the image brightness l(x, y), contrast c(x, y) and structure s(x, y) as follows: Where L is the dynamic change of pixel value; K1, K2, K3<<1; μ x , μ y is the estimated value of the mean brightness; σ x , σ y is an estimate of the standard deviation of the contrast.

6. The unmanned aerial vehicle surveying and mapping service management system according to claim 3 is characterized by: The weight ratio calculation formula of the weight ratio calculation module (21) is as follows: Wherein, N is a natural number and N>1.

7. The unmanned aerial vehicle surveying and mapping service management system according to claim 3 is characterized by: The image evaluation module (22) calculates the evaluation value of the image as W(x,y)=[l(x,y)] α [c(x,y)] β ·[s(x,y)] γ In the formula, α, β, γ>1, which are three parameters for adjusting the weights of brightness, contrast, and structure information.

8. The unmanned aerial vehicle surveying and mapping service management system according to claim 1 is characterized by: The flight decision system (4) comprises an instruction acquisition module (24), an instruction prediction module (25), an instruction comparison module (26) and an instruction execution module (27). The instruction acquisition module (24) is used to acquire the flight instruction sent by the service center (1) to the UAV and adjust the flight altitude of the UAV. The instruction acquisition module (24) is connected to the instruction prediction module (25) through data transmission technology to further predict the received instruction. The instruction prediction module (25) is connected to the instruction execution module (27) through data transmission technology to execute the instruction.

9. The unmanned aerial vehicle surveying and mapping service management system according to claim 8, characterized in that: The instruction acquisition module (24) is also connected to the instruction comparison module (26) through data transmission technology, the instruction comparison module (26) is connected to the instruction prediction module (25) through data transmission technology, and the instruction prediction module (25) is connected to the instruction execution module (27) through data transmission technology, and is used to compare the priorities of the instructions when the instructions sent by the instruction generation module 1 (14) and the instruction generation module 2 (23) are received at the same time.

Images