Unmanned aerial vehicle three-dimensional modeling scanning method

Abstract

The invention discloses an unmanned aerial vehicle three-dimensional modeling scanning method. The method comprises the steps of unmanned aerial vehicle flight track setting, multi-azimuth video shooting, infrared laser point position scanning, shot picture data transmission, infrared point position scanning data transmission, video picture decomposition, three-dimensional frame construction, picture three-dimensional segmentation, frame real scene configuration and overlapping part splicing modeling. The method has the beneficial effects that an object needing to be scanned and modeled can be integrally and comprehensively scanned by combining a bottom end annular flight path, a middle spiral flight path and a top end annular flight path only through a three-section type flight path, and the unmanned aerial vehicle does not need to carry out repeated flight paths; the distance data between the surface of the object and the unmanned aerial vehicle is acquired, the three-dimensional frame of the object is formed by combining the point positions, the shape skeleton is matched by combining the real scene picture data of the surface of the object, and the precision of the constructed three-dimensional modeling model can be ensured to be higher by adopting the mode.

Description

Technical Field

[0001] The invention relates to a three-dimensional modeling method, in particular to a three-dimensional modeling scanning method for unmanned aerial vehicles, and belongs to the technical field of three-dimensional modeling for unmanned aerial vehicles. Background Art

[0002] Drone 3D modeling is a method of 3D modeling using drone technology. This method uses a variety of sensors carried by drones, such as cameras and laser scanners, to obtain multi-angle image data of buildings, and then uses computer vision technology and 3D reconstruction algorithms to convert these image data into high-precision 3D models.

[0003] In the prior art, there is a UAV for three-dimensional modeling of human body disclosed in announcement number CN205168937U, which includes a UAV and a signal transmitting device connected to a signal receiving device and a circular motion trajectory, and the circular motion trajectory includes a number of camera points evenly distributed along the circumference. The system in the utility model can be used to model a static human body from multiple angles and in all directions. Another example is a UAV three-dimensional modeling system disclosed in announcement number CN110910502A, which includes a UAV, which is equipped with a data acquisition unit, a flight control execution unit and a wireless communication unit. The data acquisition unit includes a camera unit, a posture acquisition unit and a positioning unit. The camera unit, the posture adjustment unit, the positioning unit and the flight control execution unit are respectively connected to the wireless communication unit. The UAV sends the image information and posture position information collected by the data acquisition unit to the host and modeling terminal of the ground workstation through the wireless communication unit. The modeling terminal generates three-dimensional scene information through reconstruction algorithm processing. The host generates three-dimensional scene information based on the image information and posture position information collected by the data acquisition unit. The attitude position information and three-dimensional scene information send instructions to the flight control execution unit to control the attitude of the drone. However, when the drone is scanning, it is necessary to fly along a certain trajectory to ensure that the full picture of the required modeling object is captured. However, the existing modeling method often adopts a vertical lifting flight trajectory, or a circular motion trajectory, and then repeats the vertical flight trajectory or circular motion trajectory in sequence. This method often requires the drone to perform multiple and repeated flights, which leads to unreasonable overall flight route planning. Secondly, it is often based on the camera to capture the image of the object, but the collected image information often lacks spatial sense, which makes the constructed three-dimensional modeling model not accurate enough. Summary of the invention

[0004] The purpose of the present invention is to provide a UAV 3D modeling scanning method in order to solve the problems that the UAV flight trajectory set by the existing method is not reasonable and the constructed 3D modeling model is not accurate enough.

[0005] The present invention achieves the above-mentioned purpose through the following technical scheme: A three-dimensional modeling scanning method of an unmanned aerial vehicle comprises the following steps: S1. Setting the flight trajectory of the drone. First, the drone is flown in a circle around the object to be modeled to obtain the circumference of the object. Then, the drone is lifted and lowered vertically to obtain the height of the object. Then, based on the obtained circumference data and height data, a cylindrical model of the object is established. The modeling scanning flight trajectory of the drone is set around the cylindrical model. S2, multi-directional video shooting, based on the set UAV flight trajectory, using the camera carried by the UAV to shoot the surface of the object to obtain real scene image data of the object surface; S3, infrared laser point scanning, based on the set UAV flight trajectory, uses the infrared laser ranging sensor carried by the UAV to perform laser ranging on the surface of the object to obtain the distance data between the object surface and the UAV; S4, transmitting the captured image data to the terminal computer; S5, infrared point scanning data transmission, transmitting the acquired infrared scanning data to the terminal computer; S6, video screen decomposition, decomposing the captured real scene screen by video editing software, and dividing the continuous video screen into multiple images; S7, constructing a three-dimensional framework, obtaining the distance between each point of the object and the cylindrical model through the acquired infrared scanning data, and then marking each point of the object in the cylindrical model, and forming a three-dimensional framework of the object through multiple points; S8, three-dimensional image segmentation, combining the real scene image taken at the same time with the acquired infrared point scanning data, segmenting and three-dimensionalizing the corresponding points in the plane image according to the distance from the cylindrical model; S9, frame real scene configuration, combining the three-dimensional real scene picture with the object frame at the same position to render the frame at that position so that the frame has a real scene picture; S10, overlapping parts splicing modeling, splicing the configured multiple frame real scenes, when splicing, the overlapping parts are butt-joined together, so as to obtain the real scene three-dimensional modeling of the object.

[0006] As a further solution of the present invention: the flight trajectory of the drone is set to three parts, including: S11, setting a circular flight trajectory based on the bottom end of the cylindrical model; S12, setting a spiral flight trajectory based on the middle area of ​​the cylindrical model; S13. Setting a circular flight trajectory based on the top of the cylindrical model.

[0007] As a further solution of the present invention: when the UAV moves along the set flight trajectory, the upper and lower ends of the real-life picture taken by the UAV's camera have overlapping areas, and the upper and lower ends of the UAV's laser point scanning part have overlapping areas, so that when the overall structure is modeled later, the overlapping areas can be stacked together, and the constructed three-dimensional modeling model can form a complete structure.

[0008] As a further solution of the present invention: when transmitting the real scene image data and the infrared scanning data, 5G wireless transmission technology is adopted, and the frequency band of the spectrum adopted in the transmission process is 50GHz~150GHz, and the corresponding wavelength is 5mm~10mm.

[0009] As a further solution of the present invention: video picture decomposition specifically includes: S61, horizontally segmenting the graphics through horizontal projection to obtain an image of each row; S62, vertically segmenting each row of the segmented image by vertical projection, finally determining the coordinate position of each character, and segmenting each character; S63, counting a certain type of pixel of the binary preprocessed image in the horizontal and vertical directions respectively. The binary image is either black or white. By counting the white dots or black dots therein, the upper and lower boundaries of each row and the left and right boundaries of each column can be determined according to the statistical results, thereby achieving the purpose of segmentation.

[0010] As a further solution of the present invention: the three-dimensional image segmentation specifically includes: S81, plane segmenting the image using the same pixel point area as a unit, and dividing a complete image into a plurality of the same unit areas; S82, selecting one of the unit areas as a reference point, and taking the point distance of the unit area as the reference distance; S83. Make corresponding adjustments based on the difference between the point distance of other unit areas and the benchmark distance. If the difference is positive, it means that the distance between the unit area and the cylindrical model is longer, so the unit area needs to be moved inward. If the difference is negative, it means that the distance between the unit area and the cylindrical model is shorter, so the unit area needs to be moved outward.

[0011] The beneficial effects of the present invention are as follows: the present invention first establishes a cylindrical model of an object, and sets the modeling scanning flight trajectory of the drone around the cylindrical model. When setting the scanning flight trajectory, only a three-segment flight trajectory is required, which is combined with a bottom circular flight trajectory, a middle spiral flight trajectory, and a top circular flight trajectory, so as to realize an overall and comprehensive scanning of the object to be scanned and modeled, and the drone does not need to perform multiple repeated flight paths; The present invention obtains the distance data of the object surface from the drone, and combines it with the initially set cylindrical model, marks each point of the object in the cylindrical model, and forms a three-dimensional framework of the object through multiple points, which is equivalent to first constructing the shape skeleton of the object, and then obtains the real-life picture data of the object surface, and divides and stereoscopicizes the corresponding points in the plane image according to the distance from the cylindrical model, so that the captured real-life picture can match the constructed shape skeleton, and then the two are combined to obtain a complete real-life three-dimensional modeling of the object. By adopting this method, the constructed three-dimensional modeling model can be ensured to be more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 It is a schematic diagram of the flight trajectory design of the present invention. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1

[0014] like Figure 1 to Figure 2 As shown, a UAV 3D modeling and scanning method comprises the following steps: S1. Setting the flight trajectory of the drone. First, the drone is flown in a circle around the object to be modeled to obtain the circumference of the object. Then, the drone is lifted and lowered vertically to obtain the height of the object. Then, based on the obtained circumference data and height data, a cylindrical model of the object is established. The modeling scanning flight trajectory of the drone is set around the cylindrical model. S2, multi-directional video shooting, based on the set UAV flight trajectory, using the camera carried by the UAV to shoot the surface of the object to obtain real scene image data of the object surface; S3, infrared laser point scanning, based on the set UAV flight trajectory, uses the infrared laser ranging sensor carried by the UAV to perform laser ranging on the surface of the object to obtain the distance data between the object surface and the UAV; S4, transmitting the captured image data to the terminal computer; S5, infrared point scanning data transmission, transmitting the acquired infrared scanning data to the terminal computer; S6, video screen decomposition, decomposing the captured real scene screen by video editing software, and dividing the continuous video screen into multiple images; S7, constructing a three-dimensional framework, obtaining the distance between each point of the object and the cylindrical model through the acquired infrared scanning data, and then marking each point of the object in the cylindrical model, and forming a three-dimensional framework of the object through multiple points; S8, three-dimensional image segmentation, combining the real scene image taken at the same time with the acquired infrared point scanning data, segmenting and three-dimensionalizing the corresponding points in the plane image according to the distance from the cylindrical model; S9, frame real scene configuration, combining the three-dimensional real scene picture with the object frame at the same position to render the frame at that position so that the frame has a real scene picture; S10, overlapping parts splicing modeling, splicing the configured multiple frame real scenes, when splicing, the overlapping parts are butt-joined together, so as to obtain the real scene three-dimensional modeling of the object. Embodiment 2

[0015] In addition to all the technical features of the first embodiment, this embodiment also includes: In S1, the flight trajectory of the drone is set to three parts, including: S11, setting a circular flight trajectory based on the bottom end of the cylindrical model; S12, setting a spiral flight trajectory based on the middle area of ​​the cylindrical model; S13. Setting a circular flight trajectory based on the top of the cylindrical model.

[0016] Furthermore, when the UAV moves along the set flight trajectory, the upper and lower ends of the real-life scene pictures taken by the UAV's camera have overlapping areas, and the upper and lower ends of the UAV's laser point scanning parts have overlapping areas, so that when the overall structure modeling is carried out later, the overlapping areas can be stacked together, and the constructed three-dimensional modeling model can form a complete structure. Embodiment 3

[0017] In addition to all the technical features of the first embodiment, this embodiment also includes: When transmitting real-scene image data and infrared scanning data, 5G wireless transmission technology is used, and the frequency band of the spectrum used in the transmission process is 50GHz~150GHz, and the corresponding wavelength is 5mm~10mm.

[0018] Furthermore, the video picture decomposition specifically includes: S61, horizontally segmenting the graphics through horizontal projection to obtain an image of each row; S62, vertically segmenting each row of the segmented image by vertical projection, finally determining the coordinate position of each character, and segmenting each character; S63, counting a certain type of pixel of the binary preprocessed image in the horizontal and vertical directions respectively. The binary image is either black or white. By counting the white dots or black dots therein, the upper and lower boundaries of each row and the left and right boundaries of each column can be determined according to the statistical results, thereby achieving the purpose of segmentation.

[0019] Furthermore, the three-dimensional image segmentation specifically includes: S81, plane segmenting the image using the same pixel point area as a unit, and dividing a complete image into a plurality of the same unit areas; S82, selecting one of the unit areas as a reference point, and taking the point distance of the unit area as the reference distance; S83. Make corresponding adjustments based on the difference between the point distance of other unit areas and the benchmark distance. If the difference is positive, it means that the distance between the unit area and the cylindrical model is longer, so the unit area needs to be moved inward. If the difference is negative, it means that the distance between the unit area and the cylindrical model is shorter, so the unit area needs to be moved outward.

[0020] Working principle: By setting a three-stage flight trajectory, combining the bottom circular flight trajectory, the middle spiral flight trajectory and the top circular flight trajectory, an overall and comprehensive scan of the object to be scanned and modeled can be achieved, without the need for the drone to perform multiple repeated flight paths. The real-life image data of the object surface and the distance data from the object surface to the drone can be combined to obtain a real-life three-dimensional modeling of the object.

[0021] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0022] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A three-dimensional modeling and scanning method for unmanned aerial vehicles, characterized in that: The following steps are involved: S1. Setting the flight trajectory of the drone. First, the drone is flown in a circle around the object to be modeled to obtain the circumference of the object. Then, the drone is lifted and lowered vertically to obtain the height of the object. Then, based on the obtained circumference data and height data, a cylindrical model of the object is established. The modeling scanning flight trajectory of the drone is set around the cylindrical model. S2, multi-directional video shooting, based on the set UAV flight trajectory, using the camera carried by the UAV to shoot the surface of the object to obtain real scene image data of the object surface; S3, infrared laser point scanning, based on the set UAV flight trajectory, uses the infrared laser ranging sensor carried by the UAV to perform laser ranging on the surface of the object to obtain the distance data between the object surface and the UAV; S4, transmitting the captured image data to the terminal computer; S5, infrared point scanning data transmission, transmitting the acquired infrared scanning data to the terminal computer; S6, video screen decomposition, decomposing the captured real scene screen by video editing software, and dividing the continuous video screen into multiple images; S7, constructing a three-dimensional framework, obtaining the distance between each point of the object and the cylindrical model through the acquired infrared scanning data, and then marking each point of the object in the cylindrical model, and forming a three-dimensional framework of the object through multiple points; S8, three-dimensional image segmentation, combining the real scene image taken at the same time with the acquired infrared point scanning data, segmenting and three-dimensionalizing the corresponding points in the plane image according to the distance from the cylindrical model; S9, frame real scene configuration, combining the three-dimensional real scene picture with the object frame at the same position to render the frame at that position so that the frame has a real scene picture; S10, overlapping parts splicing modeling, splicing the configured multiple frame real scenes, when splicing, the overlapping parts are butt-joined together, so as to obtain the real scene three-dimensional modeling of the object.

2. The method for three-dimensional modeling and scanning of unmanned aerial vehicle according to claim 1, characterized in that: In S1, the flight trajectory of the drone is set to three parts, including: S11, setting a circular flight trajectory based on the bottom end of the cylindrical model; S12, setting a spiral flight trajectory based on the middle area of ​​the cylindrical model; S13. Setting a circular flight trajectory based on the top of the cylindrical model.

3. The method for three-dimensional modeling and scanning of unmanned aerial vehicle according to claim 2, characterized in that: When the drone moves along the set flight trajectory, the upper and lower ends of the real-life scene picture taken by the drone's camera have overlapping areas, and the upper and lower ends of the drone's laser point scanning part have overlapping areas, so that when the overall structure modeling is carried out later, the overlapping areas can be stacked together, thereby realizing that the constructed three-dimensional modeling model forms a complete structure.

4. The method for three-dimensional modeling and scanning of unmanned aerial vehicle according to claim 1, characterized in that: In S4 and S5, 5G wireless transmission technology is used to transmit the real scene data and the infrared scanning data, and the frequency band of the spectrum used in the transmission process is 50GHz to 150GHz, and the corresponding wavelength is 5mm to 10mm.

5. The method for three-dimensional modeling and scanning of unmanned aerial vehicle according to claim 1, characterized in that: In S6, the video picture decomposition specifically includes: S61, horizontally segmenting the graphics through horizontal projection to obtain an image of each row; S62, vertically segmenting each row of the segmented image by vertical projection, finally determining the coordinate position of each character, and segmenting each character; S63, counting a certain type of pixel of the binary preprocessed image in the horizontal and vertical directions respectively. The binary image is either black or white. By counting the white dots or black dots therein, the upper and lower boundaries of each row and the left and right boundaries of each column can be determined according to the statistical results, thereby achieving the purpose of segmentation.

6. The unmanned aerial vehicle three-dimensional modeling and scanning method according to claim 1, characterized in that: In S8, the three-dimensional image segmentation specifically includes: S81, plane segmenting the image using the same pixel point area as a unit, and dividing a complete image into a plurality of the same unit areas; S82, selecting one of the unit areas as a reference point, and taking the point distance of the unit area as the reference distance; S83. Make corresponding adjustments based on the difference between the point distance of other unit areas and the benchmark distance. If the difference is positive, it means that the distance between the unit area and the cylindrical model is longer, so the unit area needs to be moved inward. If the difference is negative, it means that the distance between the unit area and the cylindrical model is shorter, so the unit area needs to be moved outward.

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