CN117029790A - Actual measurement real-quantity robot work method - Google Patents
Actual measurement real-quantity robot work method Download PDFInfo
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- CN117029790A CN117029790A CN202310850368.6A CN202310850368A CN117029790A CN 117029790 A CN117029790 A CN 117029790A CN 202310850368 A CN202310850368 A CN 202310850368A CN 117029790 A CN117029790 A CN 117029790A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C15/00—Surveying instruments or accessories not provided for in groups G01C1/00 - G01C13/00
- G01C15/002—Active optical surveying means
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/26—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/28—Measuring arrangements characterised by the use of optical techniques for measuring areas
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
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Abstract
The invention discloses a real-measurement robot manual work method, which comprises the steps that a robot constructs a three-dimensional coordinate space to realize global positioning; the robot moves to a target position; the laser emits phase coded laser light; receiving laser reflected signals and collecting information; and realizing actual measurement real quantity of the field environment according to the acquired information. According to the technical scheme, the sensor and the laser measuring instrument with high precision are carried to sense the surrounding environment, parameters such as the size, the angle and the shape of a building are accurately measured, an accurate three-dimensional model is generated, tasks such as flatness, perpendicularity, yin and yang angles, extremely poor top surface and bottom surface, squareness, opening, depth, space size measurement, area measurement and special-shaped component size measurement are implemented on a building site, so that the efficiency and the accuracy of building construction are improved, and the measurement of building parameters on a building construction site and the auxiliary monitoring of working progress are realized.
Description
Technical Field
The invention relates to the technical field of intelligent measurement, in particular to a real-quantity actual-measurement robot working method.
Background
In the building industry, the wall body mainly comprises a bearing wall and a non-bearing wall, and mainly plays a role in enclosing and separating a space. The wall body of the wall bearing structure building integrates bearing and enclosing, and the function of the wall body of the framework structure building is enclosing and separating space. The wall body has enough strength and stability and has the capabilities of heat preservation, heat insulation, sound insulation, fire prevention and water prevention.
There is the data to show, in the building trade, carries out the in-process of wall building, has a lot of problems in the punching location in-process of wall horizontal position, and current some wall level punching, marking off positioner operation is comparatively complicated, and two locating holes of inconvenient accurate calibration are on same horizon, and then reduce the precision of location, influence the efficiency of location mark, inconvenient use, in addition after the wall construction is accomplished, need carry out a preliminary detection to the roughness of wall. Meanwhile, after the ground building is completed, flatness detection is needed, and the deviation value and the design deviation range are compared to determine whether the building quality meets the standard or not, so that the normal operation of the next construction process of the building engineering is facilitated.
Chinese patent document CN110954051B discloses a "wall surface level measuring device". Including two guide rails, fixed platform and main control unit who sets up on the guide rail, one side of fixed platform is equipped with anti-tilting mechanism, both sides are equipped with supporting mechanism respectively on the fixed platform, be equipped with elevating system on the supporting mechanism, elevating system establishes guide piece on the stay tube including the cover, the base, pulley mechanism, the base is connected with the driver in vertical direction, be equipped with the spirit level on the guide piece respectively, pulley mechanism includes first pulley, the second pulley assembly, the third pulley, the suspension piece, two guide pieces are close to wall one side and are provided with first wallboard, be provided with two risers on the first wallboard, be equipped with flexible probe and second wallboard on the riser, driver, flexible probe and main control unit electric connection. The technical scheme has single wall surface measurement data, and is difficult to meet the requirements of building construction.
Disclosure of Invention
The invention mainly solves the technical problems that the prior technical scheme is single for wall surface measurement data and is difficult to meet the requirements of building construction, provides a practical measurement robot working performance improvement method, and provides a robot for improving the working performance of the building through measurement and data acquisition.
The technical problems of the invention are mainly solved by the following technical proposal: the invention comprises the following steps:
s1, constructing a three-dimensional coordinate space by a robot to realize global positioning;
s2, the robot sets an initial node, a target node and an obstacle grid in a constructed three-dimensional coordinate space by using a grid method, acquires obstacle avoidance information by using an ant colony algorithm, sequentially moves from the initial node to a target position, records the result of each path detection, counts the change of a back and forth path and the reason that the obstacle frequently displaces in the path process, and realizes the metering judgment of the workload of a construction site;
s3, the laser emits phase coding laser;
s4, receiving laser reflection signals and collecting information;
s5, realizing actual measurement real quantity of the field environment according to the acquired information.
Preferably, the step S1 specifically includes:
s1.1 different illumination images P are acquired through two cameras Xn And image P Yn ；
S1.2 respectively aiming at different illumination images P Xn And image P Yn Carrying out illumination normalization processing and constructing an illumination reference image P' Xn And image P' Yn ；
S1.3 pair of images P' Xn And image P' Yn Preprocessing and cognition determination are carried out;
s1.4, parallax calculation is carried out according to a binocular stereoscopic imaging principle, and a point cloud image is obtained;
s1.5, constructing a three-dimensional coordinate space according to the targeted cognitive characteristics of the acquisition object and the point cloud image.
The illumination normalization process specifically comprises: input image P Xn (x Xn ，y Xn ) And image P Yn (x Yn ，y Yn ) Taking the logarithm; calculating a shadow layer image; calculating a reflection layer image and performing index transformation; selecting an image P Xn (x Xn ，y Xn ) Is a sample image g of (2) X (x Xn ，y Xn ) And calculate its histogramTaking an image P Yn (x Yn ，y Yn ) Is a sample image g of (2) Y (x Yn ，y Yn ) And calculate its histogramNormalizing the reflection layer image by adopting a histogram matching method to obtain an image r corrected by an illumination normalization method X (x X ，y X ) And r Y (x Y ，y Y )。
Preferably, the step S1.3 cognitive determination specifically includes determining the image P X0 And image P Y0 Cognitive characteristics, build image P X0 And image P Y0 The matching relation between the acquisition objects identifies the cognitive attribute of the acquisition object, wherein the cognitive characteristic comprises texture,Profile and color. The preprocessing comprises filtering, noise reduction, white balance, distortion processing and affine transformation, wherein the filtering is used for filtering specific band frequencies in signals, the noise reduction is used for suppressing and preventing interference, the noise reduction is used for eliminating interference factors, the white balance is used for correcting color temperature, the color of a collecting main body is restored, the colors of pictures shot under different light source conditions are similar to the colors of pictures watched by human eyes, the color condition of a shot object can be accurately reflected by a camera image, and the affine transformation is transformed from one two-dimensional coordinate system to another two-dimensional coordinate system and belongs to linear transformation.
Preferably, the step S2 is to collect obstacle avoidance information by using an ant colony algorithm and move the obstacle avoidance information to a target position, and specifically includes:
s2.1, setting an initial node, a target node and an obstacle grid in a three-dimensional coordinate space by using a grid method;
s2.2, initializing the basic parameters of an ant colony algorithm, and initializing an ant colony at a starting node;
s2.3, each ant selects the next node according to the transition probability until the digital ant reaches the target node and the digital ant can travel without a path;
s2.4 recording the travel path A traversed by all the digital ants n And selecting an optimal path by applying the principle of fewer inflection points;
s2.5, adjusting and iterating until the maximum iteration number to obtain a global optimal path A 0 。
And the travel paths of the non-path walkable digital ants are removed, so that the calculated amount is reduced, and the efficiency is improved. After each iteration is completed, calculating the number of inflection points in the optimal path generated by the current iteration, comparing the optimal path length generated by the current iteration with the existing optimal path length, and if the optimal path length is the same, selecting a path with fewer inflection points; if different, a path with a shorter path length is selected. The obtained optimal path A of initial iteration 0 Considered as a standard path.
After reaching the target position, measuring, returning to the initial node after the measurement is completed, starting to the next target position again, and simultaneously performing path detection between the initial node and the target position to obtain an optimal path B 0 、C 0 、D 0 … …. And recording the result of each path detection, counting the change of the back and forth path and the reason that the obstacle frequently generates displacement in the path process, realizing the metering judgment of the workload of the construction site and realizing the auxiliary monitoring of the working process.
Preferably, the step S3 specifically includes that the laser emits phase-coded laser, irradiates the wall surface to be measured after focusing through the lens, and records a time stamp of the laser emission.
Preferably, the step S4 specifically includes that the photoelectric receiver receives the reflected laser and converts the reflected laser into an electrical signal, and records a time stamp and light intensity information of the reflected laser; the camera receives the reflected laser light to form a laser line image. The photoelectric receiver is used for receiving the reflected laser and converting the reflected laser into an electric signal, and recording the time stamp and the light intensity information of the reflected laser, so that the collection of the surface point distance of the reflected laser object is realized, the complete surface information of the reflected laser object is finally obtained, and according to the obtained complete surface information of the reflected laser object, the actual measurement real robot can perform tasks such as flatness, perpendicularity, yin-yang angle, extremely poor top (bottom) surface, squareness, spacing, depth, space dimension measurement, area measurement, special-shaped component dimension measurement and the like in a building site.
Preferably, the step S5 includes measuring the yin-yang angle according to the collected information, specifically includes calculating the time difference from the emission to the reception of the laser by using a time stamp, thereby calculating the phase variation of the laser during the propagation process, calculating the angle information of the reflecting surface according to the variation of the phase difference and the wavelength of the light, comparing the phase information of adjacent pixels, and obtaining the position and size information of the yin-yang angle of the wall surface. And sequentially calculating the distance between the adjacent pixel points and the laser, comparing and calculating the distance between the adjacent pixel points to acquire the surface point distance of the reflected laser object, finally acquiring the complete surface information of the reflected laser object, and judging the yin and yang angles according to the acquired complete surface information of the reflected laser object.
Preferably, the step S5 includes measuring verticality according to the acquired information, specifically includes processing the laser line image, extracting a position and a direction of the line, and calculating a direction vector of the line in the three-dimensional space according to the position and the direction of the line; calibrating the camera and the laser transmitter to obtain the internal and external parameters of the camera and the laser transmitter; calculating the distance between the camera and the laser transmitter and each point on the wall surface by using the triangle cosine theorem and the internal and external parameters; according to the distance of each point, calculating the height of each point on the wall surface; for two points on the same horizontal line, calculating coordinates of the two points on a camera imaging plane, and calculating the distance of the two points in a three-dimensional space to obtain the height difference of the two points; and calculating the inclination angle of the wall surface through the height difference and the horizontal distance between the two points, thereby obtaining the perpendicularity of the wall surface.
Preferably, the step S5 includes measuring the flatness according to the collected information, specifically includes measuring the phase difference of the laser beam reflected from the surface of the measured object, so as to obtain the difference information of the surface of the measured object, and converting the phase difference into the difference of the surface of the measured object through a data processing algorithm, so as to realize the measurement of the flatness of the surface.
Preferably, the step S5 includes measuring the difference between the top surface and the ground of the house according to the collected information, specifically includes measuring the phase difference of the laser beam reflected from the surface of the measured object, so as to obtain the difference information of the surface of the measured object, and calculating the difference between the highest point and the lowest point according to the measured result of the phase difference.
The beneficial effects of the invention are as follows: the method has the advantages that the surrounding environment is sensed by carrying high-precision sensors and laser measuring instruments, parameters such as the size, the angle and the shape of a building are accurately measured, an accurate three-dimensional model is generated, tasks such as flatness, perpendicularity, yin and yang angles, top surface and bottom surface extremely poor, squareness, opening, depth, space dimension measurement, area measurement and special-shaped component dimension measurement are implemented on a building site, the efficiency and the accuracy of building construction are improved, and the measurement of building parameters and auxiliary monitoring of working progress on a building construction site are realized.
Drawings
Fig. 1 is a flow chart of the present invention.
Detailed Description
The technical scheme of the invention is further specifically described below through examples and with reference to the accompanying drawings.
Examples: an actual measurement real-world robot working method of the present embodiment, as shown in fig. 1, includes the following steps:
s1, constructing a three-dimensional coordinate space by a robot to realize global positioning, which specifically comprises the following steps:
s1.1 different illumination images P are acquired through two cameras Xn And image P Yn ；
S1.2 respectively aiming at different illumination images P Xn And image P Yn Carrying out illumination normalization processing and constructing an illumination reference image P' Xn And image P' Yn The method comprises the steps of carrying out a first treatment on the surface of the The illumination normalization process specifically comprises:
input image P Xn (x Xn ，y Xn ) And image P Yn (x Yn ，y Yn ) Taking the logarithm;
calculating a shadow layer image;
calculating a reflection layer image and performing index transformation;
selecting an image P Xn (x Xn ，y Xn ) Is a sample image g of (2) X (x Xn ，y Xn ) And calculate its histogramTaking an image P Yn (x Yn ，y Yn ) Is a sample image g of (2) Y (x Yn ，y Yn ) And calculate its histogram +.>
Normalizing the reflection layer image by adopting a histogram matching method to obtain an image r corrected by an illumination normalization method X (x X ，y X ) And r Y (x Y ，y Y )。
S1.3 pair of images P' Xn And image P' Yn Pretreatment and cognitive determinations are performed. The cognitive determination specifically includes determining an image P X0 And image P Y0 Cognitive characteristics, build image P X0 And image P Y0 And (3) identifying the cognitive attributes of the acquisition object by matching the acquired objects, wherein the cognitive features comprise textures, outlines and colors.
Preprocessing includes filtering, noise reduction, white balancing, warping, and affine transformation. The operation of filtering out the frequency of a specific wave band in the signal is used for inhibiting and preventing interference, noise reduction is used for eliminating interference factors, white balance is used for correcting color temperature, the color of a collecting main body is restored, the picture shot under different light source conditions is similar to the picture watched by human eyes, the color condition of a shot object can be accurately reflected by a camera image, and affine transformation is to transform from one two-dimensional coordinate system to another two-dimensional coordinate system, and the affine transformation belongs to linear transformation.
S1.4, parallax calculation is carried out according to a binocular stereoscopic imaging principle, and a point cloud image is obtained;
s1.5, constructing a three-dimensional coordinate space according to the targeted cognitive characteristics of the acquisition object and the point cloud image.
S2, the robot collects obstacle avoidance information and moves to a target position; the ant colony algorithm is utilized to collect obstacle avoidance information and move the obstacle avoidance information to a target position, and the method specifically comprises the following steps:
s2.1, setting an initial node, a target node and an obstacle grid in a three-dimensional coordinate space by using a grid method;
s2.2, initializing the basic parameters of an ant colony algorithm, and initializing an ant colony at a starting node;
s2.3, each ant selects the next node according to the transition probability until the digital ant reaches the target node and the digital ant can travel without a path; and the travel paths of the non-path walkable digital ants are removed, so that the calculated amount is reduced, and the efficiency is improved.
S2.4 recording the travel path A traversed by all the digital ants n And selecting an optimal path by applying the principle of fewer inflection points; after each iteration is completed, the inflection point in the optimal path generated by the current iteration is calculatedComparing the number of the paths with the optimal path length generated by the current iteration and the current optimal path length, and if the optimal path length is the same, selecting a path with fewer inflection points; if different, a path with a shorter path length is selected.
S2.5, adjusting and iterating until the maximum iteration number to obtain a global optimal path A 0 . The obtained optimal path A of initial iteration 0 Considered as a standard path.
After reaching the target position, measuring, and executing tasks such as flatness, perpendicularity, yin and yang angles, top surface and bottom surface extremely poor, squareness, opening, depth, space dimension measurement, area measurement, special-shaped member dimension measurement and the like in the house on a building site, returning to the initial node after measuring, starting to the next target position again, and simultaneously performing path detection between the initial node and the target position, thereby obtaining an optimal path B 0 、C 0 、D 0 … …. And recording the result of each path detection, counting the change of the back and forth path and the reason that the obstacle frequently generates displacement in the path process, realizing the metering judgment of the workload of the construction site and realizing the auxiliary monitoring of the working process.
Specifically, after the task is completed, repeating the step S1 and the step S2 to detect a return path, and returning to the starting node so as to obtain an optimal path A 00 . If the optimal path A 0 And A is a 00 And if the overlap ratio is less than 90%, judging that the optimal path is changed, recording and analyzing the result of each path detection, counting the position objects and reasons for generating displacement, such as consumption and transfer of building materials, realizing the metering judgment of the workload of a building site, and realizing the auxiliary monitoring of the working process in combination with time.
S3, the laser emits phase coding laser; the laser emits phase coded laser, irradiates the wall surface to be measured after focusing through the lens, and records the time stamp of laser emission.
S4, receiving laser reflection signals and collecting information; the photoelectric receiver receives the reflected laser and converts the reflected laser into an electric signal, and records the time stamp and the light intensity information of the reflected laser; the camera receives the reflected laser light to form a laser line image. The photoelectric receiver is used for receiving the reflected laser and converting the reflected laser into an electric signal, and recording the time stamp and the light intensity information of the reflected laser, so that the collection of the surface point distance of the reflected laser object is realized, the complete surface information of the reflected laser object is finally obtained, and according to the obtained complete surface information of the reflected laser object, the actual measurement real robot can perform tasks such as flatness, perpendicularity, yin-yang angle, extremely poor top (bottom) surface, squareness, spacing, depth, space dimension measurement, area measurement, special-shaped component dimension measurement and the like in a building site.
S5, realizing actual measurement real quantity of the field environment according to the acquired information.
Measuring yin and yang angles according to the acquired information, specifically comprising the steps of calculating a time difference from emission to receiving of laser by utilizing a time stamp, calculating a phase change amount of the laser in a propagation process, calculating angle information of a reflecting surface according to the change amount of the phase difference and the wavelength of the light, and comparing phase information of adjacent pixel points to obtain position and size information of the yin and yang angles of the wall surface. And sequentially calculating the distance between the adjacent pixel points and the laser, comparing and calculating the distance between the adjacent pixel points to acquire the surface point distance of the reflected laser object, finally acquiring the complete surface information of the reflected laser object, and judging the yin and yang angles according to the acquired complete surface information of the reflected laser object.
Measuring verticality according to the acquired information, specifically comprising the steps of processing a laser line image, extracting the position and the direction of a line, and calculating the direction vector of the line in a three-dimensional space according to the position and the direction of the line; calibrating the camera and the laser transmitter to obtain the internal and external parameters of the camera and the laser transmitter; calculating the distance between the camera and the laser transmitter and each point on the wall surface by using the triangle cosine theorem and the internal and external parameters; according to the distance of each point, calculating the height of each point on the wall surface; for two points on the same horizontal line, calculating coordinates of the two points on a camera imaging plane, and calculating the distance of the two points in a three-dimensional space to obtain the height difference of the two points; and calculating the inclination angle of the wall surface through the height difference and the horizontal distance between the two points, thereby obtaining the perpendicularity of the wall surface.
Measuring the flatness according to the acquired information, specifically comprising measuring the phase difference of laser reflected by the surface of the measured object irradiated by the laser beam, so as to obtain the difference information of the surface of the measured object, and converting the phase difference into the difference of the surface of the measured object through a data processing algorithm, so as to realize the measurement of the surface flatness.
Measuring the extreme difference between the top surface and the ground of the house according to the acquired information, specifically comprising measuring the phase difference of the laser reflected by the laser beam irradiated to the surface of the measured object, thereby obtaining the difference information of the surface of the measured object, and calculating the extreme difference of the surface of the measured object, namely the difference between the highest point and the lowest point according to the measuring result of the phase difference.
Claims (10)
1. A method of actually measuring a real-world robot, comprising the steps of:
s1, constructing a three-dimensional coordinate space by a robot to realize global positioning;
s2, the robot sets an initial node, a target node and an obstacle grid in a constructed three-dimensional coordinate space by using a grid method, acquires obstacle avoidance information by using an ant colony algorithm, sequentially moves from the initial node to a target position, records the result of each path detection, counts the change of a back and forth path and the reason that the obstacle frequently displaces in the path process, and realizes the metering judgment of the workload of a construction site;
s3, the laser emits phase coding laser;
s4, receiving laser reflection signals and collecting information;
s5, realizing actual measurement real quantity of the field environment according to the acquired information.
2. The method of actual measurement robot as set forth in claim 1, wherein the step S1 specifically includes:
s1.1 different illumination images P are acquired through two cameras Xn And image P Yn ；
S1.2 respectively aiming at different illumination images P Xn And image P Yn Carrying out illumination normalization treatment, andand construct illumination reference image P' Xn And image P' Yn ；
S1.3 pair of images P' Xn And image P' Yn Preprocessing and cognition determination are carried out;
s1.4, parallax calculation is carried out according to a binocular stereoscopic imaging principle, and a point cloud image is obtained;
s1.5, constructing a three-dimensional coordinate space according to the targeted cognitive characteristics of the acquisition object and the point cloud image.
3. The method according to claim 1, wherein said step S1.3 of cognitively determining comprises determining the image P X0 And image P Y0 Cognitive characteristics, build image P X0 And image P Y0 And (3) identifying the cognitive attributes of the acquisition object by matching the acquired objects, wherein the cognitive features comprise textures, outlines and colors.
4. The method of claim 1, wherein the step S2 is performed by using an ant colony algorithm to collect obstacle avoidance information and move the obstacle avoidance information to a target location, and specifically comprises:
s2.1, setting an initial node, a target node and an obstacle grid in a three-dimensional coordinate space by using a grid method;
s2.2, initializing the basic parameters of an ant colony algorithm, and initializing an ant colony at a starting node;
s2.3, each ant selects the next node according to the transition probability until the digital ant reaches the target node and the digital ant can travel without a path;
s2.4 recording the travel path A traversed by all the digital ants n And selecting an optimal path by applying the principle of fewer inflection points;
s2.5, adjusting and iterating until the maximum iteration number to obtain a global optimal path A 0 。
5. The method according to claim 1, wherein the step S3 specifically includes emitting the phase-coded laser beam by the laser, focusing the laser beam by the lens, irradiating the laser beam onto the wall surface to be measured, and recording the time stamp of the laser emission.
6. The method according to claim 1, wherein the step S4 specifically includes that the photoelectric receiver receives the reflected laser light and converts the reflected laser light into an electrical signal, and records a time stamp and light intensity information of the reflected laser light; the camera receives the reflected laser light to form a laser line image.
7. The method of claim 6, wherein the step S5 includes measuring the internal and external angles according to the collected information, specifically includes calculating a time difference from emission to reception of the laser using a time stamp, thereby calculating a phase change amount of the laser during propagation, calculating angle information of the reflecting surface according to the change amount of the phase difference and the wavelength of the light, and comparing the phase information of adjacent pixels to obtain the position and size information of the internal and external angles of the wall surface.
8. The method according to claim 6, wherein the step S5 includes measuring verticality according to the acquired information, specifically includes processing the laser line image, extracting a position and a direction of the line, and calculating a direction vector of the line in the three-dimensional space according to the position and the direction of the line; calibrating the camera and the laser transmitter to obtain the internal and external parameters of the camera and the laser transmitter; calculating the distance between the camera and the laser transmitter and each point on the wall surface by using the triangle cosine theorem and the internal and external parameters; according to the distance of each point, calculating the height of each point on the wall surface; for two points on the same horizontal line, calculating coordinates of the two points on a camera imaging plane, and calculating the distance of the two points in a three-dimensional space to obtain the height difference of the two points; and calculating the inclination angle of the wall surface through the height difference and the horizontal distance between the two points, thereby obtaining the perpendicularity of the wall surface.
9. The method according to claim 6, wherein the step S5 includes measuring flatness according to the collected information, specifically includes measuring a phase difference of the laser beam reflected from the surface of the measured object, thereby obtaining the measured object surface height difference information, and converting the phase difference into the measured object surface height difference by a data processing algorithm, thereby realizing the measurement of the surface flatness.
10. The method according to claim 6, wherein the step S5 includes measuring the difference between the roof and floor according to the collected information, specifically includes measuring the difference between the height of the measured object by measuring the phase difference of the laser beam reflected from the surface of the measured object, and calculating the difference between the highest point and the lowest point according to the measured result of the difference.
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