CN114812512A - Automatic imaging system of unmanned aerial photography based on AI exempts from image control point - Google Patents
Automatic imaging system of unmanned aerial photography based on AI exempts from image control point Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
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- B64—AIRCRAFT; AVIATION; COSMONAUTICS
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Abstract
The invention provides an AI-free image control point-based unmanned aerial automatic imaging system, which comprises unmanned aerial vehicle equipment, wherein the unmanned aerial vehicle equipment is a fixed-wing unmanned aerial vehicle, and is loaded with a power module, a communication module, a laser scanner, a GNSS high-precision positioning module, an MEMS inertial navigation module, an IMU attitude measurement module, a high-speed data acquisition and storage module and a full-frame aerial camera; the method comprises the following specific steps: the method comprises the steps of accurately measuring camera parameters, drawing a three-dimensional route, erecting a base station, obtaining data information stored by a mobile station and a reference station, calculating three-dimensional geographic coordinate information, automatically flying and shooting, importing a current unmanned aerial vehicle low-altitude photography aerial photograph, reading EXIF information and calibrating the precision of rare image control points. According to the invention, aerial photos can be imported in batches for multiple times, the imported photos are subjected to image quality detection, the coordinate error range in a flight line is analyzed, the writing of PPK data and the drawing of a track map are rapidly carried out, high-precision mapping is realized in dangerous areas, and safety risks are effectively avoided.
Description
Technical Field
The invention relates to the technical field of aerial photography, in particular to an automatic unmanned aerial photography imaging system based on an AI image-free control point.
Background
The traditional large-airplane aerial photogrammetry has the defects of long flight time, poor maneuverability, low real-time property, higher cost, limited precision, unsuitability for dangerous areas and the like, the unmanned aerial vehicle low-altitude digital aerial photogrammetry technology rapidly developed in recent years makes up the defects of the traditional manned aerial survey, gradually becomes an effective supplementary means of satellite remote sensing, manned remote sensing and ground remote sensing, and is particularly suitable for rapidly obtaining a high-precision large-scale digital map in a small-area and difficult-to-fly area. However, the aerial survey image of the unmanned aerial vehicle has smaller image size and more image pairs, the image quality is easily influenced by weather and flight quality, the number of image control points of the low-altitude photogrammetry of the unmanned aerial vehicle is more, the distribution requirement is higher, and the field work load of the image control measurement is larger.
The GPS single-point positioning accuracy of unmanned aerial vehicle flight control is too poor, three-dimensional modeling needs to use a large number of image control points to correct the distortion of images, but some special terrain field personnel hardly do not cut the image control points, in order to lighten the workload, most of the image control points are reduced, or even the image control points are not needed, the longitude of the POS point of the airplane is required to be improved, and the PPK technology can reach centimeter-level accuracy. And after positioning observation, performing measured combined processing on data acquired by the two GPS receivers, thereby calculating the coordinate position of the rover station on response time. The photo that unmanned aerial vehicle oblique photography shot through adopting the produced coordinate position of PPK technique, writes it into the photo, has very important meaning to three-dimensional modeling, and the later stage need not carry out image distortion's correction work yet. Therefore, it is necessary to design an intelligent oblique photography image writing method based on image control free PPK data.
Disclosure of Invention
The invention provides an automatic unmanned aerial photography imaging system based on an AI (artificial intelligence) image-free control point, which can solve the problems in the background technology.
The technical scheme of the invention is realized as follows: an automatic unmanned aerial photographing imaging system based on an AI image-free control point comprises unmanned aerial vehicle equipment, wherein the unmanned aerial vehicle equipment is a fixed-wing unmanned aerial vehicle, and is loaded with a power supply module, a communication module, a laser scanner, a GNSS high-precision positioning module, an MEMS inertial navigation module, an IMU attitude measurement module, a high-speed data acquisition and storage module and a full-frame aerial camera;
the method comprises the following specific steps:
a. accurate measurement of camera parameters: accurately calibrating the internal orientation elements of the aerial camera based on an outdoor three-dimensional calibration field, and acquiring accurate camera parameters, lens distortion parameters and camera GNSS antenna installation eccentricity;
b. drawing and erecting a base station by a three-dimensional route: calculating the course interval, the shooting baseline, the relative altitude, the lowest point resolution, the highest point course overlapping degree and the highest point lateral overlapping degree; before the fixed wing unmanned aerial vehicle three-dimensional modeling and mapping device takes off without image control points, a base station consisting of a reference station GNSS receiver and a static base station radio station assembly is erected;
c. acquiring data information stored in a mobile station and a reference station, resolving three-dimensional geographic coordinate information, linearly combining the acquired position data through specific computer software to form virtual carrier phase observation quantity, determining the relative position between receivers, introducing known coordinates of the reference station, and acquiring three-dimensional coordinates of aerial photography of the unmanned aerial vehicle;
d. automatically flying and shooting, wherein the fixed wing unmanned aerial vehicle is controlled by an erected base station to automatically fly by an image-control-point-free three-dimensional modeling and mapping device through a self-driving instrument according to a flying route designed in the step two;
e. importing the aerial photo of the current unmanned aerial vehicle in low altitude photography, and reading EXIF information: shooting photos by the unmanned aerial vehicle at equal intervals or at equal time according to a specified track route, recording attribute information and shooting data of the digital photos, reading EXIF information through software, and acquiring position information of the corresponding photos;
f. importing coordinate information acquired by the unmanned aerial vehicle during the current flight process after PPK processing, storing the processed data as a CSV format file, importing the CSV format file and reading the PPK processing data through the system, and importing the PPK data into aerial photos by one key
g. Adding image control point-free space-three calculation of an integrated system error parameter;
h. and (4) rare image control point precision calibration, adding four image control points at four corners of the measurement area to calibrate the object space free of the image control points in the step seven, and eliminating system differences of scale, direction and system offset.
Preferably, the full-frame aerial camera is rigidly and fixedly connected below the IMU attitude measurement module and is connected with an electric signal of the IMU attitude measurement module; the self-driving instrument module is respectively in electric signal connection with the GNSS high-precision positioning module, the communication module and the IMU attitude measurement module, and the MEMS inertial navigation module is connected with the full-picture aerial camera through camera exposure lines; the ground is provided with a control module which is in electric signal connection with the communication module; the GNSS high-precision positioning module, the MEMS inertial navigation module and the communication module are all electrically connected with the power supply module.
Preferably, the GNSS high-precision positioning module at least comprises an onboard multimode high-frequency GNSS receiver, a GNSS receiving antenna, an epoch data memory, an RTK communication link radio and an electronic coupling connection accessory.
Preferably, when measuring the terrain of the mountainous area, if the fluctuation of the mountainous area is small, namely the height difference inside the mountainous area is small, the relative flight heights are basically the same under the requirement of the same ground resolution, so that all the flight lines are at the same absolute flight height; if the mountainous area has large fluctuation, namely the height difference inside the mountainous area is large, the flight lines are at different absolute flight heights under the requirement of the same ground resolution.
Preferably, in the step a, the camera parameters are accurately determined, and the camera parameters include: a camera principal point position (x0, y0) and a camera principal distance (f); the lens distortion parameters include: a radial distortion coefficient k1, a radial distortion coefficient k2, a radial distortion coefficient k3, a tangential distortion coefficient p1, a tangential distortion coefficient p2, an area array deformation coefficient alpha and an area array deformation coefficient beta; the camera GNSS antenna is mounted with eccentricity (Δ X, Δ Y, Δ Z).
Preferably, in the step b, the three-dimensional course drawing parameter calculation is performed by using the measured camera parameters, the loaded public global DEM data and the shooting region KML format range line according to the altitude calculation principle, and the course interval, the shooting baseline, the relative altitude, the lowest point resolution, the highest point course overlapping degree and the highest point lateral overlapping degree are obtained and calculated.
Preferably, in the step d, a downward-looking single-lens camera or an inclined multi-lens camera is carried during flying to perform automatic aerial photography to acquire real-time dynamic differential RTK data or rear differential PPK data, IMU attitude data and aerial images.
Preferably, the step f of importing PPK data into the aerial photo by one key includes the following steps: judging whether the POS point coordinates exist in the guided aerial photo; according to when unmanned aerial vehicle aerial photograph and PPK aftertreatment data carry out quantity matching, match in proper order and import.
Compared with the prior art, the invention has the advantages that: aerial photos can be led in batch for multiple times, image quality detection is carried out on the led-in photos, the coordinate error range in the air route is analyzed, and PPK data writing and drawing of a track graph are carried out rapidly. The non-measurement aerial camera is carried on the fixed-wing unmanned aerial vehicle, aerial triangulation can be completed without any ground image control point measurement after aerial photography is completed, aerial surveying interior product processing can be directly performed, and surveying and mapping precision superior to 1:500 scale is realized under the condition of extremely small amount of image control point calibration. The field ground image control point measurement process is eliminated in the operation process, the direct connection of the operation mode from aerial photography to field calculation is realized, the time and cost expenditure for field image control point measurement are reduced, and meanwhile, high-precision mapping is realized in dangerous and difficult areas and the safety risk is effectively avoided.
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FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b): referring to fig. 1, an AI-image-control-point-free unmanned aerial automatic imaging system comprises unmanned aerial vehicle equipment, wherein the unmanned aerial vehicle equipment is a fixed-wing unmanned aerial vehicle and is provided with a power module, a communication module, a laser scanner, a GNSS high-precision positioning module, an MEMS inertial navigation module, an IMU attitude measurement module, a high-speed data acquisition and storage module and a full-frame aerial camera;
the method comprises the following specific steps:
a. accurate measurement of camera parameters: accurately calibrating the internal orientation elements of the aerial camera based on an outdoor three-dimensional calibration field, and acquiring accurate camera parameters, lens distortion parameters and camera GNSS antenna installation eccentricity;
b. drawing and erecting a base station by a three-dimensional route: calculating the course interval, the shooting baseline, the relative altitude, the lowest point resolution, the highest point course overlapping degree and the highest point lateral overlapping degree; before the fixed wing unmanned aerial vehicle three-dimensional modeling and mapping device takes off without image control points, a base station consisting of a reference station GNSS receiver and a static base station radio station assembly is erected;
c. acquiring data information stored in a mobile station and a reference station, resolving three-dimensional geographic coordinate information, linearly combining the acquired position data through specific computer software to form virtual carrier phase observation amount, determining the relative position between receivers, introducing the known coordinates of the reference station, and acquiring the three-dimensional coordinates of the aerial photography of the unmanned aerial vehicle;
d. automatically flying and shooting, wherein the fixed wing unmanned aerial vehicle is controlled by an erected base station to automatically fly by an image-control-point-free three-dimensional modeling and mapping device through a self-driving instrument according to a flying route designed in the step two;
e. importing the aerial photo of the current unmanned aerial vehicle in low altitude photography, and reading EXIF information: shooting photos by the unmanned aerial vehicle at equal intervals or at equal time according to a specified track route, recording attribute information and shooting data of the digital photos, reading EXIF information through software, and acquiring position information of the corresponding photos;
f. importing coordinate information acquired by the unmanned aerial vehicle during the current flight process after PPK processing, storing the processed data as a CSV format file, importing the CSV format file and reading the PPK processing data through the system, and importing the PPK data into aerial photos by one key
g. Adding image control point-free space-three calculation of an integrated system error parameter;
h. and (4) rare image control point precision calibration, adding four image control points at four corners of the measurement area to calibrate the object space free of the image control points in the step seven, and eliminating system differences of scale, direction and system offset.
Preferably, the full-frame aerial camera is rigidly and fixedly connected below the IMU attitude measurement module and is connected with an electric signal of the IMU attitude measurement module; the self-driving instrument module is respectively in electric signal connection with the GNSS high-precision positioning module, the communication module and the IMU attitude measurement module, and the MEMS inertial navigation module is connected with the full-picture aerial camera through camera exposure lines; the ground is provided with a control module which is in electric signal connection with the communication module; the GNSS high-precision positioning module, the MEMS inertial navigation module and the communication module are all electrically connected with the power supply module.
Preferably, the GNSS high-precision positioning module at least comprises an onboard multimode high-frequency GNSS receiver, a GNSS receiving antenna, an epoch data memory, an RTK communication link radio and an electronic coupling connection accessory.
Preferably, when measuring the terrain of the mountainous area, if the fluctuation of the mountainous area is small, namely the height difference inside the mountainous area is small, the relative flight heights are basically the same under the requirement of the same ground resolution, so that all the flight lines are at the same absolute flight height; if the mountainous area has large fluctuation, namely the height difference inside the mountainous area is large, the flight lines are at different absolute flight heights under the requirement of the same ground resolution.
Preferably, in the step a, the camera parameters are accurately determined, and the camera parameters include: a camera principal point position (x0, y0) and a camera principal distance (f); the lens distortion parameters include: a radial distortion coefficient k1, a radial distortion coefficient k2, a radial distortion coefficient k3, a tangential distortion coefficient p1, a tangential distortion coefficient p2, an area array deformation coefficient alpha and an area array deformation coefficient beta; the camera GNSS antenna is mounted with eccentricity (Δ X, Δ Y, Δ Z).
Preferably, in the step b, the three-dimensional course drawing parameter calculation is performed by using the measured camera parameters, the loaded public global DEM data and the shooting region KML format range line according to the altitude calculation principle, and the course interval, the shooting baseline, the relative altitude, the lowest point resolution, the highest point course overlapping degree and the highest point lateral overlapping degree are obtained and calculated.
Preferably, in the step d, a downward-looking single-lens camera or an inclined multi-lens camera is carried during flying to perform automatic aerial photography to acquire real-time dynamic differential RTK data or rear differential PPK data, IMU attitude data and aerial images.
Preferably, the step f of importing PPK data into the aerial photo by one key includes the following steps: judging whether POS point coordinates exist in the guided aerial photo; according to when unmanned aerial vehicle aerial photograph and PPK aftertreatment data carry out quantity matching, match in proper order and import.
The oblique photography image intelligent writing method based on the image control-free PPK data can lead aerial photographs in batches for multiple times, detect the image quality of the lead photographs, analyze the coordinate error range in a flight line, and quickly write the PPK data and draw a track map. The non-measurement aerial camera is carried on the fixed-wing unmanned aerial vehicle, aerial triangulation can be completed without any ground image control point measurement after aerial photography is completed, aerial surveying of interior products can be directly performed, and surveying and mapping precision superior to 1:500 scale is achieved under the condition of extremely small amount of image control point calibration. The field ground image control point measuring process is eliminated in the operation flow, the direct connection of the operation mode from aerial photography to field calculation is realized, the time and cost for field image control point measurement are reduced, and meanwhile, high-precision mapping is realized in dangerous and difficult areas and the safety risk is effectively avoided.
In actual use, the communication module is used for receiving instructions of the ground control module, and the power supply module is responsible for supplying power to the fixed-wing flight platform and various electronic modules on the fixed-wing flight platform. And a reference station GNSS receiver of the ground control module receives the coordinate information, and the static base station radio station assembly radio sends the coordinates to the airborne communication module and the self-driving instrument module. The autopilot module is responsible for controlling the flight of the whole fixed-wing flight platform 1 according to the coordinate information and a pre-drawn three-dimensional route and simultaneously triggering pulses to the IMU attitude measurement module, the full-frame and the airborne GNSS high-precision positioning module. And the IMU attitude measurement module marks time according to the pulse and records angle information. The full frame is time stamped according to the pulse and a picture is taken. And the airborne GNSS high-precision positioning module marks time according to the pulse and records coordinate information. A signal transmission process is completed.
The acquisition frequency of the airborne multimode high-frequency GNSS receiver epoch is not lower than 20HZ, the reading and writing speed of the epoch data memory is not lower than 100MB/s, the communication radius of the RTK communication link radio station is not lower than 5km when the RTK communication link radio station is not shielded, and the marking time difference recorded by the airborne multimode high-frequency GNSS receiver and the IMU attitude measurement module from the pulse signal of the autopilot is not more than 1ms by the electronic coupling connection accessory. When the GNSS high-precision positioning module is actually used, when the flying speed of the fixed-wing unmanned aerial vehicle flying platform is not more than 20 m/s, the GNSS high-precision positioning module can accurately acquire the space coordinates of the exposure point by utilizing two modes, namely a static PPK mode and a dynamic RTK mode.
Analyzing the coordinate track of the air route of the unmanned aerial vehicle by using software, carrying out linear combination on data synchronously received by the reference station and the unmanned aerial vehicle rover station to form virtual carrier phase observed quantity, determining the relative position between receivers, introducing the known coordinate of the reference station, and obtaining the three-dimensional coordinate of aerial photography of the unmanned aerial vehicle. Intelligently writing the obtained three-dimensional coordinates into EXIF information of the photo by means of comparison, searching for leakage repair and the like, and realizing accurate three-dimensional modeling effect; the image control-free photograph importing coordinate information is achieved through the PPK technology, high-precision aerial photography and charting are completed, and in the large-area real-scene three-dimensional reconstruction process, the problems of dislocation, layering and the like during model block combination are avoided, so that model empty and three failures are easily caused, and further the model cannot be reconstructed.
The image control-free scheme has the advantages that the field industry does not need to arrange phase control: the field time is shortened, and the mountain stream valley zone can be reduced by 10 times; personnel and equipment are safer, and frequent rushing and trembling are not needed. The efficiency of the air conditioner is improved in the field: the air triangle does not need to be punctured, so that the air triangulation becomes intelligent; the time of the three air chambers is shortened, and professional steps are simplified. Ensuring the uniform precision of the whole image: performing stereo mapping, wherein the plane is 10cm, and the elevation is 5 cm; and (3) three-dimensional mapping, wherein the plane is 3cm, and the height is 5 cm. The open cloud comedy fly image-control-free solution greatly shortens the field and interior time of a user, improves aerial survey precision, fundamentally solves the problem of aerial survey precision control, solves the core problem of aerial triangulation by two core technologies, namely POS refinement and high-precision camera calibration, provides accurate interior and exterior orientation elements for the air navigation three software according to the three-dimensional position (exterior orientation elements) at the aerial film exposure time and the aerial camera distortion parameters (interior orientation elements), and ensures the success of the air navigation three software by 100%. POS refinement the POS position is a POS refinement to estimate the pole-arm effect for the RTK antenna.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. The utility model provides an automatic imaging system of unmanned aerial vehicle based on AI exempts from to take photo by plane accuse point, includes unmanned aerial vehicle equipment, its characterized in that: the unmanned aerial vehicle equipment is a fixed-wing unmanned aerial vehicle, and a power supply module, a communication module, a laser scanner, a GNSS high-precision positioning module, an MEMS inertial navigation module, an IMU attitude measurement module, a high-speed data acquisition and storage module and a full-frame aerial camera are loaded on the unmanned aerial vehicle equipment;
the method comprises the following specific steps:
a. accurate measurement of camera parameters: accurately calibrating the internal orientation elements of the aerial camera based on an outdoor three-dimensional calibration field, and acquiring accurate camera parameters, lens distortion parameters and camera GNSS antenna installation eccentricity;
b. drawing and erecting a base station by a three-dimensional route: calculating the course interval, the shooting baseline, the relative altitude, the lowest point resolution, the highest point course overlapping degree and the highest point lateral overlapping degree; before the fixed wing unmanned aerial vehicle three-dimensional modeling and mapping device takes off without image control points, a base station consisting of a reference station GNSS receiver and a static base station radio station assembly is erected;
c. acquiring data information stored in a mobile station and a reference station, resolving three-dimensional geographic coordinate information, linearly combining the acquired position data through specific computer software to form virtual carrier phase observed quantity, determining the relative position between receivers, introducing known coordinates of the reference station, and acquiring three-dimensional coordinates of aerial photography of the unmanned aerial vehicle;
d. automatically flying and shooting, wherein the fixed wing unmanned aerial vehicle is controlled by an erected base station to automatically fly by an image-control-point-free three-dimensional modeling and mapping device through a self-driving instrument according to a flying route designed in the step two;
e. importing the aerial photo of the unmanned aerial vehicle at the low altitude at the current time, and reading EXIF information: shooting photos by the unmanned aerial vehicle at equal intervals or at equal time according to a specified track route, recording attribute information and shooting data of the digital photos, reading EXIF information through software, and acquiring position information of the corresponding photos;
f. importing coordinate information acquired by the unmanned aerial vehicle during the current flight process after PPK processing, storing the processed data as a CSV format file, importing the CSV format file and reading PPK processing data through the system, and importing the PPK data into aerial photos by one key
g. Adding image control point-free space-three calculation of an integrated system error parameter;
h. and (4) rare image control point precision calibration, adding four image control points at four corners of the measurement area to calibrate the object space free of the image control points in the step seven, and eliminating system differences of scale, direction and system offset.
2. The AI-based point-free automatic aerial photography imaging system of claim 1, wherein: the full-frame aerial camera is rigidly and fixedly connected below the IMU attitude measurement module and is connected with an electric signal of the IMU attitude measurement module; the autopilot module is respectively in electric signal connection with the GNSS high-precision positioning module, the communication module and the IMU attitude measurement module, and the MEMS inertial navigation module is connected with the full-frame aerial camera through camera exposure lines; the ground is provided with a control module which is in electric signal connection with the communication module; the GNSS high-precision positioning module, the MEMS inertial navigation module and the communication module are all electrically connected with the power supply module.
3. The AI-based point-free automatic aerial photography imaging system of claim 2, wherein: the GNSS high-precision positioning module at least comprises an airborne multimode high-frequency GNSS receiver, a GNSS receiving antenna, an epoch data memory, an RTK communication link radio station and an electronic coupling connection accessory.
4. The AI-based point-by-image-free unmanned aerial automatic imaging system of claim 1, wherein: when the terrain of the mountainous area is measured, if the fluctuation of the mountainous area is small, namely the height difference inside the mountainous area is small, the relative flight heights are basically the same under the requirement of the same ground resolution, so that all flight paths are at the same absolute flight height; if the mountainous area has large fluctuation, namely the height difference inside the mountainous area is large, the flight lines are at different absolute flight heights under the requirement of the same ground resolution.
5. The AI-based point-free automatic aerial photography imaging system of claim 1, wherein: in the step a, the camera parameters are accurately determined, and the camera parameters include: a camera principal point position (x0, y0) and a camera principal distance (f); the lens distortion parameters include: a radial distortion coefficient k1, a radial distortion coefficient k2, a radial distortion coefficient k3, a tangential distortion coefficient p1, a tangential distortion coefficient p2, an area array deformation coefficient alpha and an area array deformation coefficient beta; the camera GNSS antenna is mounted with eccentricity (Δ X, Δ Y, Δ Z).
6. The AI-based point-by-image-free unmanned aerial automatic imaging system of claim 5, wherein: and in the step b, calculating three-dimensional course drawing parameters by using the measured camera parameters, loading the public global DEM data and the shooting region KML format range line according to the altitude calculation principle, and acquiring and calculating course intervals, a shooting baseline, relative altitude, lowest point resolution, highest point course overlapping degree and highest point lateral overlapping degree.
7. The AI-based point-by-image-free unmanned aerial automatic imaging system of claim 6, wherein: and d, carrying a downward-looking single-lens camera or an inclined multi-lens camera during flying to automatically carry out aerial photography to obtain real-time dynamic differential RTK data or rear differential PPK data, IMU posture data and aerial photography images.
8. The AI-based point-of-image-free unmanned aerial vehicle imaging system of claim 7, wherein: the step f of importing PPK data into the aerial photo by one key comprises the following steps: judging whether the imported aerial photo has POS point coordinates or not; according to when unmanned aerial vehicle aerial photograph and PPK aftertreatment data carry out quantity matching, match in proper order and import.
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| CN116931601A (en) * | 2023-07-25 | 2023-10-24 | 苏州瀚易特信息技术股份有限公司 | Aerial photography and video shooting control system based on unmanned aerial vehicle |
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| CN116929306B (en) * | 2023-07-20 | 2024-04-19 | 深圳赛尔智控科技有限公司 | Data acquisition method, device, equipment and computer readable storage medium |
| CN116931601A (en) * | 2023-07-25 | 2023-10-24 | 苏州瀚易特信息技术股份有限公司 | Aerial photography and video shooting control system based on unmanned aerial vehicle |
| CN116931601B (en) * | 2023-07-25 | 2024-02-20 | 苏州瀚易特信息技术股份有限公司 | Aerial photography and video shooting control system based on unmanned aerial vehicle |
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