CN-122015787-A - Mapping method and device based on unmanned aerial vehicle apparatus, medium, and program product

CN122015787ACN 122015787 ACN122015787 ACN 122015787ACN-122015787-A

Abstract

The invention discloses a mapping method, a mapping device, mapping equipment, mapping media and mapping program products based on an unmanned aerial vehicle, wherein laser point cloud data and aerial image data of a region to be detected are collected through a laser radar aerial survey module carried by the unmanned aerial vehicle, and a three-dimensional model of the region to be detected is constructed according to the laser point cloud data and the aerial image data; and adjusting the base inclination until the base inclination is in a tolerance range, and controlling the image total station to map the target point to obtain the absolute three-dimensional coordinate of the target point. According to the invention, the laser radar aerial survey module and the image total station are mounted on the unmanned aerial vehicle, after the target point is identified, the base is perceived and actively adjusted to be in a horizontal state in real time and then the sighting and surveying are carried out, so that the small target can be identified, sighting and measuring under a complex environment, and the precision of the surveying and surveying operation of a complex dangerous area is improved.

Inventors

JIN YAN
WU HANG

Assignees

齐之明光电智能科技(苏州)有限公司

Dates

Publication Date: 20260512
Application Date: 20260210

Claims (10)

1. The mapping method based on the unmanned aerial vehicle is characterized in that the unmanned aerial vehicle is provided with a laser radar aerial survey module and an image total station, and the method comprises the following steps: Collecting laser point cloud data and aerial image data of a region to be detected through the laser radar aerial detection module carried by the unmanned aerial vehicle, and fusing the laser point cloud data and the aerial image data to obtain a three-dimensional model of the region to be detected; Identifying and determining a target point in the three-dimensional model, controlling the unmanned aerial vehicle to fly to the target point, and identifying the inclination of the base of the unmanned aerial vehicle falling to the target point; and adjusting the inclination of the base until the inclination of the base is in a tolerance range, and controlling the image total station to map the target point to obtain the absolute three-dimensional coordinate of the target point.
2. The method according to claim 1, wherein the method further comprises: acquiring historical three-dimensional coordinates of the target point, wherein the historical three-dimensional coordinates are three-dimensional coordinates mapped for the target point in a plurality of historical periods; Calculating a coordinate difference between the absolute three-dimensional coordinate and the historical three-dimensional coordinate, and determining a time displacement sequence of the target point based on the coordinate difference; Calculating deformation index data of the target point according to the time displacement sequence, and comparing the deformation index data with a preset safety early warning threshold value to obtain a comparison result; and generating a monitoring report of the target point according to the three-dimensional coordinates, the time displacement sequence and the comparison result.
3. The method of claim 1, wherein the drone is communicatively linked to a ground station via a data link; the laser radar aerial survey module that carries through unmanned aerial vehicle carries on gathers laser point cloud data and the image data of taking photo by plane in the region of awaiting measuring, include: presetting an autonomous flight route of the unmanned aerial vehicle in the region to be tested, and controlling the unmanned aerial vehicle to carry out automatic flight according to the autonomous flight route; in the flight process, performing time synchronization on the laser radar and the aerial camera in the laser radar aerial survey module; After time synchronization, acquiring laser point cloud data of the region to be detected through the laser radar, and simultaneously acquiring aerial image data of the region to be detected through the aerial camera; and transmitting the laser point cloud data and the aerial image data to the ground station or storing the laser point cloud data and the aerial image data in an onboard memory of the unmanned aerial vehicle through the data link.
4. A method according to claim 1 or 3, wherein the fusing the laser point cloud data and the aerial image data to obtain a three-dimensional model of the region to be measured comprises: Extracting a time stamp and first pose information corresponding to the time stamp from the laser point cloud data, and determining second pose information corresponding to the time stamp from the aerial image data; Based on the first pose information and the second pose information, performing spatial registration on the laser point cloud data and the aerial image data; Establishing a geometric surface model according to the registered laser point cloud data; mapping the aerial image data to the geometric surface model to generate a three-dimensional model of the region to be detected.
5. The method of claim 4, wherein the spatially registering the laser point cloud data with the aerial image data based on the first pose information and the second pose information comprises: Based on the first pose information and the second pose information, initially aligning an imaging center and an imaging direction of the aerial image data with the laser point cloud data; Extracting a plurality of two-dimensional feature points from the aligned aerial image data, and matching the two-dimensional feature points to generate a sparse three-dimensional feature point cloud; And carrying out spatial registration on the sparse three-dimensional characteristic point cloud and the laser point cloud data.
6. The method of claim 5, wherein the geometric surface model comprises a plurality of geometric patches, and wherein the mapping the aerial image data to the geometric surface model generates a three-dimensional model of the region under test comprises: determining at least one texture source image from the aerial image data according to the spatial position and orientation of each geometric patch; And projecting the pixel area corresponding to the texture source image to the geometric surface patch, and performing fusion processing to generate a three-dimensional model of the area to be detected.
7. The method of claim 1, wherein the drone further comprises an automatic leveling module, wherein the adjusting the base tilt until the base tilt is within a tolerance range, controlling the image total station to map the target point, obtaining absolute three-dimensional coordinates of the target point, comprises: Acquiring the inclination of the base of the unmanned aerial vehicle through an inclination sensor in the automatic leveling module, leveling the base of the unmanned aerial vehicle based on the inclination of the base, and judging whether the residual inclination of the base after leveling is within a tolerance range; If yes, establishing a horizontal reference aiming at the target point, and controlling the image total station to map the target point at the horizontal reference to obtain an absolute three-dimensional coordinate of the target point; If not, triggering an alarm, controlling the unmanned aerial vehicle to execute the landing and leveling process again at the other position of the target point until the inclination of the base is in a tolerance range, establishing a horizontal reference for the target point, and controlling the image total station to map the target point at the horizontal reference to obtain the absolute three-dimensional coordinate of the target point.
8. The method of claim 7, wherein the controlling the image total station to map the target point at the horizontal reference comprises: acquiring a rough three-dimensional coordinate of the target point in the three-dimensional model, and controlling the image total station to initially position the target point based on the rough three-dimensional coordinate; After preliminary positioning, acquiring an image of a target point by using an industrial camera configured by the image total station, and repositioning the target point in the image; Controlling the servo driving system of the image total station to aim the relocated target point, and measuring the horizontal angle, the vertical angle and the inclined distance of the target point relative to the image total station; And acquiring an absolute coordinate system of the image total station, and determining three-dimensional coordinates of the target point under the absolute coordinate system based on the horizontal angle, the vertical angle and the inclined distance.
9. Survey and drawing device based on unmanned aerial vehicle, its characterized in that carries on laser radar aerial survey module and image total powerstation on the unmanned aerial vehicle, the device includes: The data acquisition module is used for acquiring laser point cloud data and aerial image data of a region to be detected through the laser radar aerial survey module carried by the unmanned aerial vehicle, and fusing the laser point cloud data and the aerial image data to obtain a three-dimensional model of the region to be detected; The inclination calculation module is used for identifying and determining a target point in the three-dimensional model, controlling the unmanned aerial vehicle to fly to the target point and identifying the inclination of the base of the unmanned aerial vehicle falling to the target point; and the target mapping module is used for adjusting the inclination of the base until the inclination of the base is in a tolerance range, and controlling the image total station to map the target point to obtain the absolute three-dimensional coordinate of the target point.
10. A computer program product comprising computer instructions for causing a computer to perform the unmanned aerial vehicle-based mapping method of any of claims 1 to 8.

Description

Mapping method and device based on unmanned aerial vehicle apparatus, medium, and program product Technical Field The invention relates to the technical field of mapping, in particular to a mapping method, a mapping device, mapping equipment, mapping media and mapping program products based on unmanned aerial vehicles. Background The traditional surveying and mapping means such as manual total station measurement, GNSS static measurement and the like have the limitations of low operation efficiency, high labor intensity, difficult coverage of complex dangerous areas and the like although the precision is high. In recent years, unmanned aerial vehicle mapping technology has been widely used due to its high efficiency and high flexibility. However, the existing unmanned aerial vehicle mapping technology still has obvious bottlenecks, such as insufficient absolute precision, dependence on ground control points in photogrammetry, difficulty in achieving millimeter-level precision in an uncontrolled area, remarkably reduced precision in a GNSS signal shielded area, poor environmental adaptability, lack of high-precision absolute references, difficulty in realizing autonomous accurate measurement in a complex environment, low automation and intelligent degree, and incapability of realizing full-flow automatic operation due to the fact that a large amount of manual intervention is required for specific monitoring targets. Disclosure of Invention The invention provides a mapping method, device, equipment, medium and program product based on an unmanned aerial vehicle, which are used for solving the problem of how to autonomously identify, aim and measure a small target in a complex environment. In a first aspect, the present invention provides a mapping method based on an unmanned aerial vehicle, on which a lidar aerial survey module and an image total station are mounted, the method comprising: Collecting laser point cloud data and aerial image data of a region to be detected through the laser radar aerial detection module carried by the unmanned aerial vehicle, and fusing the laser point cloud data and the aerial image data to obtain a three-dimensional model of the region to be detected; Identifying and determining a target point in the three-dimensional model, controlling the unmanned aerial vehicle to fly to the target point, and identifying the inclination of the base of the image total station falling to the target point; and adjusting the inclination of the base until the inclination of the base is in a tolerance range, and controlling the unmanned aerial vehicle to map the target point to obtain the absolute three-dimensional coordinate of the target point. According to the invention, the laser radar aerial survey module and the image total station are mounted on the unmanned aerial vehicle, after the target point is identified, the base is perceived and actively adjusted to be in a horizontal state in real time and then the sighting and surveying are carried out, so that the small target can be identified, sighting and measuring under a complex environment, and the precision of the surveying and surveying operation of a complex dangerous area is improved. In an alternative embodiment, the method further comprises: acquiring historical three-dimensional coordinates of the target point, wherein the historical three-dimensional coordinates are three-dimensional coordinates mapped for the target point in a plurality of historical periods; Calculating a coordinate difference between the absolute three-dimensional coordinate and the historical three-dimensional coordinate, and determining a time displacement sequence of the target point based on the coordinate difference; Calculating deformation index data of the target point according to the time displacement sequence, and comparing the deformation index data with a preset safety early warning threshold value to obtain a comparison result; and generating a monitoring report of the target point according to the three-dimensional coordinates, the time displacement sequence and the comparison result. The invention constructs the time displacement sequence of the target point by comparing the current and the history coordinates, thereby quantifying the deformation process. Based on the time displacement sequence, key deformation indexes such as accumulated displacement, deformation rate and the like are further calculated, and are compared with a preset safety threshold value, so that automatic grading early warning of the deformation state is realized. And finally, integrating the coordinate data, the displacement sequence, the analysis index and the early warning result to generate a structured monitoring report, directly converting the original measurement data into safety information for decision making, and improving the timeliness, the accuracy and the automation level of deformation monitoring. In an alternative embodiment, the drone is communicatively link