Highway pavement construction method based on aerial survey of unmanned aerial vehicle

Abstract

The invention relates to an expressway pavement construction method based on aerial survey of an unmanned aerial vehicle, and the method comprises the following steps: coordinate transformation: calculating seven parameters through control points in an aerial survey area, and correcting the unmanned aerial vehicle; data acquisition: remotely controlling the unmanned aerial vehicle to fly along the aerial survey area to acquire road surface data; data processing: importing the acquired road surface data into data processing software to generate a picture model with elevation coordinates in the aerial survey area; and elevation model generation: generating a plurality of point locations with plane coordinates and elevation coordinates in the picture model, and identifying the point locations in different elevation intervals by adopting different colors. The unmanned aerial vehicle is adopted to carry out aerial photography on the aerial survey area, the road surface data in the aerial survey area are collected, the road surface data are processed through the data processing software, then the model of the aerial survey area is established, constructors can carry out adjustment in time, the model can achieve the precision of the plane and the elevation + / -5 mm, and the collection efficiency is high; and road surface data of 10-15 kilometers can be collected every day.

Description

Technical Field

[0001] The present application relates to the technical field of pavement construction, and in particular to a highway pavement construction method based on drone aerial survey. Background Art

[0002] The road surface of the highway is mostly asphalt pavement. During the construction process, it is generally divided into four layers for paving. Each layer needs to be compacted after paving. Road surface compaction is an important link in the asphalt pavement construction process. The compaction effect will directly affect the overall construction quality of the highway.

[0003] When paving and accepting each layer of a highway, its flatness and thickness must be measured. The current paving layer height and whether there is an over-height or under-height problem can be determined through measurement, and then the existing problems can be dealt with in time to avoid adverse effects on the quality of pavement paving. The existing methods for measuring paving flatness are mostly manual measurements using total stations, etc. Human factors have a great impact on the measurement results, which is time-consuming, labor-intensive and inefficient. In addition, only the flatness and thickness at the point can be measured, which cannot intuitively reflect the flatness of the entire road surface. Once the number of points is small, the quality of pavement paving is easily reduced. Summary of the invention

[0004] Based on this, it is necessary to provide a highway pavement construction method based on UAV aerial survey to overcome the defects of low efficiency of manual measurement of flatness and great influence of human factors on pavement paving quality during highway pavement construction.

[0005] A highway pavement construction method based on drone aerial survey includes the following steps:

[0006] Coordinate transformation, calculate seven parameters through the control points in the aerial survey area and calibrate the drone;

[0007] Data collection: remotely control the drone to fly along the aerial survey area to collect road surface data;

[0008] Data processing: import the collected road surface data into the data processing software, screen the road surface data, extract the corresponding road surface data for splicing, and generate a picture model with elevation coordinates of the aerial survey area;

[0009] Elevation model generation: Generate several points with plane coordinates and elevation coordinates in the picture model. Points in the same elevation range are marked with the same color, and points in different elevation ranges are marked with different colors.

[0010] As a preferred embodiment of the highway pavement construction method based on drone aerial survey in the present invention, the drone includes a body, an RTK positioning module is arranged in the body, and a five-axis head camera is also arranged in the body.

[0011] As a preferred embodiment of the highway pavement construction method based on drone aerial survey in the present invention, the pavement data collected by the drone includes pavement photos and elevation coordinates of the pavement photos;

[0012] As a preferred embodiment of the highway pavement construction method based on drone aerial survey in the present invention, road obstructions should be cleared before the data collection.

[0013] As a preferred method of highway pavement construction based on drone aerial survey in the present invention, the data collection includes flight and vehicle-mounted,

[0014] The flight comprises the following steps: planning a flight trajectory above the aerial survey area, and the drone automatically flies along the flight trajectory to collect road surface data;

[0015] The vehicle-mounted method includes the following steps: connecting the drone to the vehicle so that the drone is suspended above the vehicle, the vehicle travels along a planned route within the aerial survey area, and the drone collects road surface data.

[0016] As a preferred embodiment of the highway pavement construction method based on drone aerial survey in the present invention, the data collection also includes elevation fitting.

[0017] The elevation fitting comprises the following steps: calibrating a plurality of coordinate points in the aerial survey area, using an instrument to measure the plane coordinates and the elevation coordinates of the coordinate points, and importing the plane coordinates and the elevation coordinates of the coordinate points into data processing software.

[0018] As a preferred method of highway pavement construction based on drone aerial survey in the present invention, the data processing includes the following steps: fitting the collected pavement data according to the plane data and elevation coordinates of the coordinate points, screening out the pavement data that matches the data of the coordinate points, splicing the pavement photos in the screened pavement data through the splicing algorithm in the data processing software, and combining them with the corresponding elevation coordinates of the pavement photos to form a picture model;

[0019] As a preferred embodiment of the highway pavement construction method based on drone aerial survey in the present invention, the elevation model generation includes the following steps: generating a number of points in the picture model, each point does not overlap and has plane coordinates and elevation coordinates, and forming a point cloud three-dimensional model through color rendering of the elevation coordinates, marking the points in the point cloud three-dimensional model that are in the same elevation range with the same color, and marking the points in different elevation ranges with different colors to form an elevation model.

[0020] As a preferred embodiment of the highway pavement construction method based on drone aerial survey in the present invention, it also includes batch export. After the elevation model is generated, the plane coordinates of the whole pile number and offset in the aerial survey area are imported into the data processing software to fit it in the point cloud three-dimensional model, and the whole pile number elevation is exported in batches.

[0021] As a preferred embodiment of the highway pavement construction method based on drone aerial survey in the present invention, after the elevation model is generated for the first time, some points are re-surveyed by instruments in the aerial survey area to check the accuracy of the elevation model.

[0022] Beneficial effects of the present invention:

[0023] The present invention adopts a drone to take aerial photos of the aerial survey area, collects road surface data in the aerial survey area, processes the road surface data through data processing software, and then establishes a picture model, a point cloud three-dimensional model and an elevation model of the aerial survey area. The smoothness of the highway road surface can be clearly and intuitively displayed, which is convenient for construction personnel to make timely adjustments. The model can achieve an accuracy of ±5mm in plane and elevation, has high collection efficiency, and can collect 10 to 15 kilometers of road surface data every day. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 This is a schematic diagram of the construction method in the embodiment of the present application;

[0026] Figure 2 This is a schematic diagram of the structure of the picture model in the embodiment of the present application;

[0027] Figure 3 This is a schematic diagram of the structure when the image model generates points in the embodiment of the present application;

[0028] Figure 4 This is a schematic diagram of the structure of the point cloud three-dimensional model in the embodiment of the present application;

[0029] Figure 5 This is a schematic diagram of the structure of the elevation model in the embodiment of the present application;

[0030] Figure 6 This is a schematic diagram of the structure when the elevation model inputs the whole pile number and offset in the embodiment of the present application; DETAILED DESCRIPTION

[0031] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0032] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0033] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0034] In this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0035] In the present application, unless otherwise clearly specified and limited, a first feature being “above” or “below” a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being “above”, “above”, and “above” a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being “below”, “below”, and “below” a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0036] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "upper", "lower", "left", "right" and similar expressions used herein are for illustrative purposes only and are not intended to be the only implementation method.

[0037] Example

[0038] This embodiment provides a highway pavement construction method based on drone aerial survey, such as Figure 1 As shown, the following steps are included:

[0039] Coordinate transformation, calculate the seven parameters through the existing control points in the aerial survey area, and calibrate the drone used in this aerial survey.

[0040] Data collection: The remote-controlled UAV flies along the aerial survey area to collect road surface data. The collected road surface data includes road surface photos and the elevation coordinates corresponding to the road surface photos.

[0041] In this implementation, in order to improve the accuracy of aerial survey and restore the road conditions to the greatest extent, obstacles on the road should be cleared before the drone is released to avoid aerial survey blind spots.

[0042] In this embodiment, data collection is divided into two modes: flight and vehicle-mounted. When the aerial survey area is relatively open and there are no relatively high obstacles, high-voltage lines, signal towers, etc., the flight mode can be used to collect road surface data. When the flight mode is used, the flight trajectory of the drone should be planned in advance, and then the drone is released to automatically fly and collect road surface data according to the flight trajectory. When flight conditions are met, continuous operation is required, or higher aerial survey accuracy is required, the vehicle-mounted mode is used to collect road surface data. The drone is connected to the vehicle and suspended above the vehicle. The vehicle drives along the planned route in the aerial survey area, and the drone collects road surface data.

[0043] In this embodiment, in order to improve the efficiency of collecting road surface data, multiple drones can be used to perform aerial survey operations at the same time.

[0044] The data acquisition also includes elevation fitting to ensure the elevation accuracy of the aerial survey area. The elevation fitting includes the following steps: calibrating 3 to 4 coordinate points in the aerial survey area, and marking the coordinate points with conspicuous signs that are easy for drones to identify. After determining the coordinate points, use instruments to measure the plane coordinates and elevation coordinates of the coordinate points, and import the plane coordinates and elevation coordinates of the coordinate points into the data processing software as the elevation calibration of the aerial survey area.

[0045] Data processing: import the collected road surface data into the data processing software, screen the road surface data, extract the corresponding road surface data for splicing, and generate a picture model with elevation coordinates of the aerial survey area;

[0046] In this embodiment, the data processing includes the following steps: fitting the collected road surface data according to the plane data and elevation coordinates of the coordinate points, screening out the road surface data that matches the data of the coordinate points, and further screening the road surface data to obtain road surface photos that meet the accuracy requirements and their corresponding elevation coordinates, splicing the road surface photos in the screened road surface data through the splicing algorithm in the data processing software, and combining them with the corresponding elevation coordinates of the road surface photos to form a Figure 2 The picture model shown can be used to clearly and intuitively view the current road conditions.

[0047] Elevation model generation: Generate several points with plane coordinates and elevation coordinates in the picture model. Points in the same elevation range are marked with the same color, and points in different elevation ranges are marked with different colors.

[0048] In this embodiment, the elevation model generation includes the following steps: Figure 3 As shown in the figure, a large number of points are generated in the picture model. These points involve various areas of the road surface in the aerial survey area. Each point does not overlap and has plane coordinates and elevation coordinates. The elevation coordinates are rendered in color to form a Figure 4 The point cloud 3D model shown in the figure uses the same color to mark the points in the same elevation range, and different colors to mark the points in different elevation ranges, forming a point cloud 3D model as shown in the figure. Figure 5 The elevation model shown in the figure. Different elevation intervals are represented by different colors, which intuitively displays the elevation distribution of the aerial survey area.

[0049] In this embodiment, the drone surveying and mapping is carried out by using a set of integrated RTK positioning modules deployed in the collective, and a five-axis head camera with a built-in shock absorption system to shoot high-definition images. The road surface data is processed by data processing software to generate a picture model, and a digital elevation map is generated indoors based on the real-scene picture model. Since drones are flexible, economical and convenient, and can easily obtain high-resolution image maps, the use of drones to measure large-scale topographic maps is low-cost, short-term, and high-precision, which can greatly reduce the workload of field work, thereby improving production efficiency and shortening the construction period. It is easy to operate, low-cost, and highly maneuverable. It can restore the characteristics of land objects in an all-round and three-dimensional manner, and speed up data collection.

[0050] The elevation model can also be exported in batches. After the elevation model is generated, the plane coordinates of the whole pile number and offset in the aerial survey area are imported into the data processing software to fit it into the point cloud three-dimensional model. Figure 6 As shown, the corresponding whole pile number plane and elevation can be batch queried and exported for easy viewing by construction personnel.

[0051] After the elevation model is generated for the first time, some points in the aerial survey area are re-surveyed using instruments to check the accuracy of the elevation model.

[0052] Every time the highway pavement is paved, drones are used to detect its elevation, and any over-elevated or under-elevated areas found are repaired. The same method can also be used for pavement acceptance.

[0053] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0054] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A highway pavement construction method based on drone aerial survey, characterized in that: The steps include: Coordinate transformation, calculate seven parameters through the control points in the aerial survey area and calibrate the drone; Data collection: remotely control the drone to fly along the aerial survey area to collect road surface data; Data processing: import the collected road surface data into the data processing software, screen the road surface data, extract the corresponding road surface data for splicing, and generate a picture model with elevation coordinates of the aerial survey area; Elevation model generation: Generate several points with plane coordinates and elevation coordinates in the picture model. Points in the same elevation range are marked with the same color, and points in different elevation ranges are marked with different colors.

2. The highway pavement construction method based on drone aerial survey according to claim 1 is characterized in that: The drone comprises a body, in which an RTK positioning module is arranged, and a five-axis head camera is also arranged.

3. The highway pavement construction method based on drone aerial survey according to claim 2 is characterized in that: The road surface data collected by the drone includes road surface photos and elevation coordinates of the road surface photos.

4. The highway pavement construction method based on drone aerial survey according to claim 1 is characterized in that: Road obstructions should be cleared before the data collection is performed.

5. The highway pavement construction method based on drone aerial survey according to claim 4 is characterized in that: The data collection includes flight and vehicle-mounted, The flight comprises the following steps: planning a flight trajectory above the aerial survey area, and the drone automatically flies along the flight trajectory to collect road surface data; The vehicle-mounted method includes the following steps: connecting the drone to the vehicle so that the drone is suspended above the vehicle, the vehicle travels along a planned route within the aerial survey area, and the drone collects road surface data.

6. The highway pavement construction method based on drone aerial survey according to claim 5 is characterized in that: The data collection also includes elevation fitting, The elevation fitting comprises the following steps: calibrating a plurality of coordinate points in the aerial survey area, using an instrument to measure the plane coordinates and the elevation coordinates of the coordinate points, and importing the plane coordinates and the elevation coordinates of the coordinate points into data processing software.

7. The highway pavement construction method based on drone aerial survey according to claim 1 is characterized in that: The data processing includes the following steps: fitting the collected road surface data according to the plane data and elevation coordinates of the coordinate points, screening out the road surface data that matches the data of the coordinate points, splicing the road surface photos in the screened road surface data through the splicing algorithm in the data processing software, and combining them with the corresponding elevation coordinates of the road surface photos to form a picture model.

8. The highway pavement construction method based on drone aerial survey according to claim 1 is characterized in that: The elevation model generation includes the following steps: generating a plurality of points in the picture model, each point being non-overlapping and having plane coordinates and elevation coordinates, and forming a point cloud three-dimensional model by color rendering of the elevation coordinates, marking the points in the same elevation interval in the point cloud three-dimensional model with the same color, and marking the points in different elevation intervals with different colors to form an elevation model.

9. The highway pavement construction method based on drone aerial survey according to claim 1 is characterized in that: It also includes batch export. After the elevation model is generated, the plane coordinates of the whole pile number and offset in the aerial survey area are imported into the data processing software to fit it in the point cloud three-dimensional model, and the whole pile number elevation is exported in batches.

10. The highway pavement construction method based on drone aerial survey according to claim 1 is characterized in that: After the elevation model is generated for the first time, some points in the aerial survey area are re-surveyed using instruments to check the accuracy of the elevation model.

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