Low-altitude remote sensing surveying and mapping method based on intelligent sensing monitoring of unmanned aerial vehicle

Abstract

The invention discloses a low-altitude remote sensing surveying and mapping method based on unmanned aerial vehicle intelligent sensing monitoring, and the method comprises the steps: S1, obtaining the number of unmanned aerial vehicles, dividing an unmanned aerial vehicle cluster into a plurality of unmanned aerial vehicle small groups, and numbering the unmanned aerial vehicle small groups; s2, according to the size of the remote sensing surveying and mapping area, the large area is divided into a plurality of small areas, and the number corresponds to the number of unmanned aerial vehicle small groups; s3, performing remote sensing surveying and mapping on the small areas, including the following steps: 1) enabling one unmanned aerial vehicle small group to correspond to one small area, and performing surveying and mapping at a low altitude; 2) performing remote sensing surveying and mapping on the region by the unmanned aerial vehicle small group to obtain a plurality of sub-pictures; 3) displaying a plurality of sub-pictures on a large screen to form an integral picture; s4, a complete remote sensing surveying and mapping picture is obtained, the number of the unmanned aerial vehicle small groups is the same as that of the small areas, surveying and mapping are facilitated, and the surveying and mapping picture obtained by adjusting the height of the unmanned aerial vehicle does not need to be adjusted.

Description

Technical Field

[0001] The present invention relates to the technical field of low-altitude remote sensing mapping, and particularly relates to a low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles (UAVs). Background Art

[0002] Remote sensing mapping: Remote sensing is a non-contact long-distance detection technology. By using UAV technology, remote sensing sensor technology, telemetry and remote control technology, communication technology, GPS differential positioning technology, and remote sensing application technology, it can automatically, intelligently, and specifically and rapidly obtain spatial remote sensing mapping images of land resources, natural environment, earthquake-stricken areas, etc. Currently, the development of computer technology and remote sensing technology is very rapid, and remote sensing technology has gradually emerged in the fields of environmental resource monitoring, geological exploration, geographical mapping, and disaster monitoring.

[0003] In the existing low-altitude remote sensing mapping method based on intelligent perception monitoring of UAVs, low-altitude remote sensing mapping is completed by using UAVs to take pictures. However, in this way, during use, a UAV swarm is required. When the UAV swarm is working, there will be differences in altitude, which will lead to the need for adjustment when splicing the pictures, and it is rather inconvenient. Summary of the Invention

[0004] The present invention mainly solves the technical problems existing in the above-mentioned prior art, and provides a low-altitude remote sensing mapping method based on intelligent perception monitoring of UAVs.

[0005] The above technical problems of the present invention are mainly solved by the following technical solutions: A low-altitude remote sensing mapping method based on intelligent perception monitoring of UAVs divides the UAV swarm into multiple small UAV groups, and then divides the remote sensing mapping area into multiple small areas. The number of small UAV groups is the same as the number of small areas, which is convenient for mapping. By adjusting the altitude of the UAVs, the obtained mapping pictures do not need to be adjusted.

[0006] The present invention also provides the above-mentioned low-altitude remote sensing mapping method based on intelligent perception monitoring of UAVs, including the following steps:

[0007] S1. Obtain the number of UAVs, divide the UAV swarm into multiple small UAV groups, and number them;

[0008] S2. According to the size of the remote sensing mapping area, divide the large area into multiple small areas, and the number corresponds to the number of small UAV groups;

[0009] S3. Conduct remote sensing mapping on the small areas, including the following steps:

[0010] 1). One small UAV group corresponds to one small area. The small UAV group is evenly distributed in each corner of the small area according to the size of the small area and the number of UAVs, and conducts mapping at low altitude;

[0011] 2) The small groups of unmanned aerial vehicles conduct remote sensing mapping on the area to obtain multiple images. The images mapped by the unmanned aerial vehicles are stitched with the images mapped by other unmanned aerial vehicles to form sub-images, and multiple sub-images are obtained.

[0012] 3) The multiple sub-images are displayed on the large screen, and the image positions correspond to the small area positions, and then an overall image is formed.

[0013] S4. Detect the altitude of each small group of unmanned aerial vehicles to make the altitudes of each small group of unmanned aerial vehicles consistent, and then a complete remote sensing mapping diagram is obtained.

[0014] According to a low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles provided by the present invention, in S1, dividing the unmanned aerial vehicle cluster into multiple small groups of unmanned aerial vehicles specifically means evenly dividing them into multiple small groups of unmanned aerial vehicles according to the total number of unmanned aerial vehicles.

[0015] According to a low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles provided by the present invention, in S1, numbering them specifically means numbering the small groups of unmanned aerial vehicles.

[0016] According to a low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles provided by the present invention, in S2, dividing the large area into multiple small areas according to the size of the remote sensing mapping area specifically means dividing according to the area size and the number of unmanned aerial vehicles to ensure that there are at least ten unmanned aerial vehicles in each small area.

[0017] According to a low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles provided by the present invention, in S3, in 1), the small groups of unmanned aerial vehicles are evenly distributed in the corners of the small area according to the size of the small area and the number of unmanned aerial vehicles specifically means setting the X-axis and Y-axis in the small area, dividing the small area into multiple small grids, and the number of small grids is equal to the number of unmanned aerial vehicles.

[0018] According to a low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles provided by the present invention, in S3, in 2), the images mapped by the unmanned aerial vehicles are stitched with the images mapped by other unmanned aerial vehicles to form sub-images specifically means stitching the remotely sensed images of the unmanned aerial vehicles in the same area, and after stitching, it is the sub-image of this small area.

[0019] According to a low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles provided by the present invention, in S3, in 3), the image position corresponding to the small area position specifically means arranging the small area images on the large screen according to the position relationship.

[0020] A low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles according to the present invention. In step S4, the detection of the altitude of each small group of unmanned aerial vehicles specifically refers to the detection of the altitude of the unmanned aerial vehicles, adjusting the altitudes of the unmanned aerial vehicles to be the same, and the flight altitude of the unmanned aerial vehicles is 5-10 m.

[0021] Compared with the prior art, in this low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles, by dividing the unmanned aerial vehicle cluster into multiple small groups of unmanned aerial vehicles, and then dividing the remote sensing mapping area into multiple small areas, the number of small groups of unmanned aerial vehicles is the same as that of the small areas, thus facilitating mapping. By adjusting the altitude of the unmanned aerial vehicles, the obtained mapping images do not need to be adjusted. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention will be further described below in conjunction with the drawings and embodiments;

[0023] Figure 1 It is a flowchart of the low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] This part will describe in detail the specific embodiments of the present invention. The preferred embodiments of the present invention are shown in the drawings. The function of the drawings is to supplement the description of the text part of the specification, enabling people to intuitively and vividly understand each technical feature and the overall technical solution of the present invention, but it cannot be construed as a limitation on the protection scope of the present invention.

[0025] Refer to Figure 1 , an embodiment of the low-altitude remote sensing mapping method based on intelligent perception monitoring of unmanned aerial vehicles of the present invention includes the following steps:

[0026] S1. Obtain the number of unmanned aerial vehicles, divide the unmanned aerial vehicle cluster into multiple small groups of unmanned aerial vehicles, and number them. The specific numbering is to number the small groups of unmanned aerial vehicles. Dividing the unmanned aerial vehicle cluster into multiple small groups of unmanned aerial vehicles specifically means dividing them into multiple small groups of unmanned aerial vehicles on average according to the total number of unmanned aerial vehicles;

[0027] S2. According to the size of the remote sensing mapping area, divide the large area into multiple small areas, and the number corresponds to the number of small groups of unmanned aerial vehicles. Dividing the large area into multiple small areas according to the size of the remote sensing mapping area specifically means ensuring that there are at least ten unmanned aerial vehicles in each small area according to the area size and the number of unmanned aerial vehicles;

[0028] S3. Conduct remote sensing mapping on the small areas, including the following steps:

[0029] 1). One small group of drones corresponds to one small area. The small group of drones is evenly distributed in each corner of the small area according to the size of the small area and the number of drones, and conducts mapping at low altitude. The small group of drones being evenly distributed in each corner of the small area according to the size of the small area and the number of drones specifically means setting the X-axis and Y-axis within the small area, dividing the small area into multiple small grids, and the number of small grids being equal to the number of drones.

[0030] 2). The small group of drones conducts remote sensing mapping on the area and obtains multiple images. The images mapped by the drones are stitched with the images mapped by other drones to form sub-images, and multiple sub-images are obtained. The images mapped by the drones being stitched with the images mapped by other drones to form sub-images specifically means stitching the remotely sensed images of the drones within the same area. After stitching is completed, it is the sub-image of this small area.

[0031] 3). Multiple sub-images are displayed on the large screen, and the positions of the images correspond to the positions of the small areas, thereby forming an overall image. The positions of the images corresponding to the positions of the small areas specifically means that the small area images are arranged on the large screen according to the positional relationship.

[0032] S4. Detect the height of each small group of drones to make the height of each small group of drones consistent, thereby obtaining a complete remote sensing mapping diagram. Detecting the height of each small group of drones specifically means detecting the height of the drones and adjusting the heights of the drones to be consistent. The flight height of the drones is 5 - 10m.

[0033] The above has described the embodiments of the present invention in detail with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those of ordinary skill in the art in the said technical field, various changes can also be made without departing from the gist of the present invention.

Claims

1. A low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring, characterized in that: The following steps are involved: S1. Obtain the number of drones, divide the drone cluster into multiple drone groups, and number them; S2. According to the size of the remote sensing mapping area, the large area is divided into multiple small areas, the number of which corresponds to the number of small groups of drones; S3. Remote sensing mapping of a small area, including the following steps: 1) A small group of drones corresponds to a small area. The small group of drones is evenly distributed in every corner of the small area according to the size of the small area and the number of drones, and performs mapping at low altitude; 2) A small group of drones conducts remote sensing mapping of the area to obtain multiple images. The images mapped by the drones are spliced ​​with the images mapped by other drones to form sub-images to obtain multiple sub-images; 3) Multiple sub-pictures are displayed on the large screen, and the positions of the pictures correspond to the positions of the small areas, thus forming the overall picture; S4. Detect the height of each small group of drones to make the height of each small group of drones consistent, so as to obtain a complete remote sensing mapping.

2. The low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring according to claim 1 is characterized in that: In S1, the drone cluster is divided into a plurality of drone sub-groups, specifically, the total number of drones is evenly divided into a plurality of drone sub-groups.

3. The low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring according to claim 1 is characterized in that: The numbering in S1 specifically includes numbering the small groups of drones.

4. The low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring according to claim 1 is characterized in that: In S2, the large area is divided into a plurality of small areas according to the size of the remote sensing mapping area, specifically according to the size of the area and the number of drones, to ensure that there are at least ten drones in each small area.

5. The low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring according to claim 1 is characterized in that: The small group of drones in 1) in S3 is evenly distributed in each corner of the small area according to the size of the small area and the number of drones. Specifically, an X-axis and a Y-axis are set in the small area, and the small area is divided into multiple small grids, and the number of small grids is equal to the number of drones.

6. The low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring according to claim 1 is characterized in that: The picture mapped by the drone in 2) in S3 is spliced ​​with the pictures mapped by other drones to form a sub-picture, specifically, the images mapped by drone remote sensing in the same area are spliced. After the splicing is completed, it becomes a sub-picture of the small area.

7. The low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring according to claim 1 is characterized in that: The image position in 3) of S3 corresponds to the position of the small area, and specifically the small area images are arranged on the large screen according to the position relationship.

8. The low-altitude remote sensing mapping method based on unmanned aerial vehicle intelligent perception monitoring according to claim 1 is characterized in that: The detection of the height of each small group of drones in S4 specifically includes detecting the height of the drones and adjusting the heights of the drones to be consistent. The flying height of the drones is 5-10m.

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