An adaptive method for calibrating the lifting height of a mechanical structure.

Abstract

This invention discloses an adaptive method for calibrating the lifting height of a mechanical structure, belonging to the field of construction robot technology. Applicable robots include lifting motors, main lifting mechanisms, slave lifting mechanisms, and equipment pan-tilt units. A camera is located on the top of the equipment pan-tilt unit, and a locking mechanism is used for locking the main lifting mechanism. The calibration method includes measuring the distance H between the ceiling and the ground using the camera. total The device performs surface detection on the ceiling using a camera, obtaining the observed values ​​of the distance H from the ceiling to the camera and the angle α; the actual height the device rises is H1 = H. total -H; The predetermined lifting height H2 of the device's pan-tilt unit can be obtained based on the number of rotations of the lifting motor. The difference Δ between H1 and H2 is the false position. After performing multiple false position tests at different positions, the average value of Δ is taken as the setting value for this correction. By adjusting the correction setting value, the actual lifting height H1 of the device equals the predetermined lifting height H2 of the device, thus achieving adaptive height correction.

Description

Technical Field

[0001] This invention relates to the field of construction robot technology, and in particular to an adaptive method for calibrating the lifting height of a mechanical structure. Background Technology

[0002] In the market, the automation technology of construction robots for spraying and scraping building walls is gradually maturing. However, during the construction process, the lifting structure and other components inevitably experience misalignment errors, resulting in a discrepancy between the actual lifting height and the preset lifting height. Therefore, external calibration is necessary to correct these misalignment errors. The cause of this misalignment error is that, over long-term use, the main lifting structure inevitably develops some misalignment, which gradually accumulates and affects the normal operation of the equipment. Calibration is required to correct this misalignment.

[0003] To address the false positioning error, a camera-based surface detection algorithm can be used to detect the distance between the camera and the ceiling. Then, by manually measuring the distance between the ceiling and the ground, and considering the fixed difference between the camera and the top of the lifting structure, the measured height of the top of the lifting structure from the ground can be obtained. Assuming the error between the measured height and the actual lifting height is within the tolerance range, the false positioning error can be eliminated using the difference between the measured height and the preset lifting height.

[0004] Using cameras to calibrate the height of a wall-mounted robot's lifting mechanism requires strong coupling between visual algorithms, hardware, and device movements; there is currently no corresponding solution on the market. Summary of the Invention

[0005] The purpose of this invention is to provide an adaptive method for calibrating the lifting height of a mechanical structure, so as to solve the technical problem that building wall robots are prone to accumulating false position errors in the prior art.

[0006] This invention provides an adaptive mechanical structure lifting height calibration method for a wall-building robot. The wall-building robot includes a lifting motor, a main lifting mechanism, a secondary lifting mechanism, and a gimbal. The gimbal is used for wall construction operations. The main lifting mechanism controls the overall lifting of the wall-building robot, and the secondary lifting mechanism controls the lifting of the gimbal. The lifting motor provides the power output for both the main and secondary lifting mechanisms. The wall-building robot also includes a camera located on top of the gimbal. A locking mechanism is provided at the connection between the main lifting mechanism and the chassis of the wall-building robot. The calibration method includes:

[0007] Sp1: The distance between the ceiling and the ground is measured by a camera. The wall construction robot is manually moved to select a flat, unobstructed ceiling, and the distance Htotal from the ground to the ceiling is measured. The parameters are then manually entered.

[0008] Sp2: Perform surface detection on the ceiling using a camera, and based on the surface detection results, obtain the observed values ​​of the distance H from the ceiling to the camera and the angle α.

[0009] Sp3: The distance from the device's pan-tilt unit to the ground, i.e., the actual height of the device, is H1 = Htotal - H. Here, H1 is based on the actual measured value and is used as a reference for calibration.

[0010] Sp4: The predetermined lifting height H2 of the device gimbal can be obtained based on the number of rotations of the lifting motor. The difference Δ between H1 and H2 is the false position. After the robot performs multiple false position detections at different positions, the average value of Δ is taken as the set value for this correction.

[0011] Sp5: By adjusting the correction setpoint, the actual lifting height H1 of the equipment is equal to the predetermined lifting height H2 of the equipment, thus achieving adaptive height correction.

[0012] Furthermore, when the camera performs surface detection on the ceiling, it measures the α angle multiple times, calculates the average value, and uses this as an adjustment parameter. Then, by adjusting the locking mechanism, it fixes the main lifting mechanism and the robot chassis, eliminating the deviation angle of the equipment gimbal. When α is not zero, when the main lifting mechanism is stationary, adjusting the locking structure makes α zero, thus adjusting the deviation angle of the equipment gimbal. During the lifting process, the equipment gimbal may tilt at a certain angle, which can pose safety hazards and potentially reduce construction quality. By measuring the α angle multiple times and calculating the average value as an adjustment parameter, the locking mechanism of the main lifting mechanism can be effectively adjusted to eliminate the deviation angle of the equipment gimbal.

[0013] Furthermore, when correcting the set value, when the desired height increases by H1, the motor is sent an increase of H1+Δ based on the existing Δ value to estimate the false position. At this time, the actual increase is H=H1+Δ-Δ, which is close to the desired value.

[0014] Furthermore, when the camera performs surface detection on the ceiling, the detection method is as follows: for n points in space, i.e., n3, according to the SVD transformation of the covariance matrix, the singular vector corresponding to the minimum singular value is the direction of the plane.

[0015] Furthermore, when the camera performs surface detection on the ceiling, the detection method can also be as follows: using the normal method, for n points in space, i.e., n3, outliers are removed, and the centroid P of the point cloud is calculated; if the normal is already obtained in the point cloud, after removing discrete points from the normal, the mean of the minimum variance can be obtained to directly obtain the normal direction N(alpha, beta, theta); the point normal form is used to describe the three-dimensional plane; or the general form of the plane equation is calculated based on the centroid P and the normal direction, and the normal is used for multiple clustering to complete the scene plane extraction.

[0016] Furthermore, when the camera performs surface detection on the ceiling, another detection method that can be used is: RANSAC random sampling fitting.

[0017] Sp2-1: Consider a model with a minimum sampling set of cardinality n, where n is the minimum number of samples required to initialize the model parameters; and a sample set P, where the number of samples in set P is #(P)>n. Randomly select a subset S of P containing n samples from P to initialize the model M.

[0018] Sp2-2: The set of samples in the remainder set SC = P\S whose error with model M is less than a certain set threshold t, together with S, constitute S*. S* is considered to be the set of interior points, and they constitute the consistent set of S.

[0019] Sp2-3: If #(S*)≥N, it is considered that the correct model parameters have been obtained, and the new model M* is recalculated using the set S* (inliers) and other methods such as least squares; a new S is randomly selected again, and the above process is repeated.

[0020] Sp2-4: If no consistent set is found after a certain number of samplings, the algorithm fails; otherwise, the largest consistent set obtained after sampling is selected to determine the internal and external points, and the algorithm ends.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0022] 1. In existing technologies, during long-term use of wall-cleaning robots, the main lifting structure inevitably experiences some play, which gradually accumulates and affects the normal operation of the equipment. It is necessary to correct the play through calibration. Therefore, this invention designs a height calibration method. The distance from the camera to the ceiling is detected by the camera on the top of the device's gimbal. The distance from the camera to the ground is calculated based on the height difference between the ceiling and the ground. Based on the fixed distance between the camera's reference plane and the top of the main lifting mechanism, the measured height of the main lifting mechanism to the ground can be obtained. The measured height is used as the basis for play adjustment. The entire calibration process of the building wall-cleaning robot can be controlled through a software APP. This lifting height calibration scheme is strongly coupled with the robot's movements, and the play error is accurately eliminated.

[0023] 2. During the ascent of the equipment pan-tilt head, there may be a certain angle of tilt, which may pose certain safety hazards and reduce the quality of construction. By repeatedly measuring the α angle and calculating the average value, the locking mechanism of the main lifting mechanism can be effectively adjusted to eliminate the deviation angle of the equipment pan-tilt head. Attached Figure Description

[0024] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the overall structure of the construction robot in this invention;

[0026] Figure 2 This is a flowchart of the calibration method of the present invention. Attached image description:

[0028] 1. Main lifting mechanism; 2. Slave lifting mechanism; 3. Camera; 4. Locking mechanism; 5. Lifting motor; 6. Equipment pan-tilt unit. Detailed Implementation

[0029] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0030] The components of the embodiments of the invention described and shown in the accompanying drawings can typically be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention.

[0031] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Specific implementation examples:

[0033] The following is combined Figures 1 to 2 As shown, this embodiment of the invention provides an adaptive mechanical structure lifting height calibration method for a wall-building robot. The wall-building robot includes a lifting motor 5, a main lifting mechanism 1, a secondary lifting mechanism 2, and a gimbal 6. The gimbal 6 is used for wall construction work. The main lifting mechanism 1 controls the overall lifting of the wall-building robot, and the secondary lifting mechanism 2 controls the lifting of the gimbal 6. The lifting motor 5 provides the power output for both the main lifting mechanism 1 and the secondary lifting mechanism 2. The wall-building robot also includes a camera 3 located on top of the gimbal 6. A locking mechanism 4 is provided at the connection between the main lifting mechanism 1 and the chassis of the wall-building robot. The calibration method includes:

[0034] Sp1: Measure the distance between the ceiling and the ground using camera 3. Manually move the wall construction robot to select a flat, unobstructed ceiling, measure the distance Htotal from the ground to the ceiling, and manually input the parameters.

[0035] Sp2: Perform surface detection on the ceiling using camera 3, and based on the surface detection results, obtain the observed values ​​of the distance H from the ceiling to camera 3 and the angle α.

[0036] The method includes:

[0037] Method 1: For n points in space, i.e., n³, according to the SVD transformation of the covariance matrix, the singular vector corresponding to the minimum singular value is the direction of the plane.

[0038] Method 2: Using the normal method, for n points in space, i.e., n³, outliers are removed, and the centroid P of the point cloud is calculated. If the normals are already obtained in the point cloud, after removing discrete points from the normals, the mean of the minimum variance can be calculated to directly obtain the normal direction N(alpha, beta, theta). The point normal form is used to describe the 3D plane; or, based on the centroid P and the normal direction, the general form of the plane equation is calculated, and the normals are used for multiple clustering to complete the scene plane extraction.

[0039] Method 3: Fitting using RANSAC random sampling:

[0040] Sp2-1: Consider a model with a minimum sampling set of cardinality n, where n is the minimum number of samples required to initialize the model parameters; and a sample set P, where the number of samples in set P is #(P)>n. Randomly select a subset S of P containing n samples from P to initialize the model M.

[0041] Sp2-2: The set of samples in the remainder set SC = P\S whose error with model M is less than a certain set threshold t, together with S, constitute S*. S* is considered to be the set of interior points, and they constitute the consistent set of S.

[0042] Sp2-3: If #(S*)≥N, it is considered that the correct model parameters have been obtained, and the new model M* is recalculated using the set S* (inliers) and other methods such as least squares; a new S is randomly selected again, and the above process is repeated.

[0043] Sp2-4: If no consistent set is found after a certain number of samplings, the algorithm fails; otherwise, the largest consistent set obtained after sampling is selected to determine the internal and external points, and the algorithm ends.

[0044] Sp3: The distance from the device's pan-tilt unit 6 to the ground, i.e., the actual height of the device, is H1 = Htotal - H. Here, H1 is based on the actual measured value and is used as a reference for calibration.

[0045] Sp4: The predetermined lifting height H2 of the device gimbal 6 can be obtained based on the number of rotations of the lifting motor 5. The difference Δ between H1 and H2 is the false position. After the robot performs multiple false position detections at different positions, the average value of Δ is taken as the set value for this correction.

[0046] Sp5: By adjusting the correction setpoint, the actual lifting height H1 of the equipment is equal to the predetermined lifting height H2 of the equipment, thus achieving adaptive height correction.

[0047] In existing technologies, during long-term use of wall-cleaning robots, the main lifting mechanism inevitably experiences some play, which gradually accumulates and affects the normal operation of the equipment. This play needs to be corrected through calibration. Therefore, this invention designs a height calibration method. The distance from the camera 3 on the top of the device's gimbal 6 to the ceiling is detected. Based on the height difference between the ceiling and the ground, the distance from the camera 3 to the ground is calculated. Based on the fixed distance between the reference plane of the camera 3 and the top of the main lifting mechanism, the measured height of the main lifting mechanism from the ground can be obtained. This measured height is used as the basis for play adjustment. The entire calibration process of the building wall-cleaning robot can be controlled through a software APP. This lifting height calibration scheme is strongly coupled with the robot's movements, and the play error is accurately eliminated.

[0048] In another embodiment, when camera 3 performs surface detection on the ceiling, it measures the α angle multiple times, calculates the average value, and uses it as an adjustment parameter. Then, it adjusts the locking mechanism 4 to fix the main lift 1 and the robot chassis, eliminating the deviation angle of the equipment gimbal 6. When α is not 0, when the main lift 1 is stationary, the locking structure is adjusted to make α 0, thus adjusting the deviation angle of the equipment gimbal 6. When correcting the set value, when the desired height increases by H1, the motor is sent to increase by H1+Δ based on the existing Δ value, estimating the false position. At this time, the actual increase is H=H1+Δ-Δ, which is close to the desired value. During the lifting process, the equipment gimbal 6 may tilt at a certain angle, which may bring certain safety hazards and reduce the construction quality. By measuring the α angle multiple times and calculating the average value as an adjustment parameter, the locking mechanism 4 of the main lift 1 can be effectively adjusted to eliminate the deviation angle of the equipment gimbal 6.

[0049] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive mechanical structure lifting height calibration method for a wall construction robot, the wall construction robot comprising a lifting motor (5), a main lifting mechanism (1), a secondary lifting mechanism (2), and a gimbal (6), wherein the wall construction is performed by the gimbal (6), the main lifting mechanism (1) controls the overall lifting of the wall construction robot, the secondary lifting mechanism (2) controls the lifting of the gimbal (6), and the lifting motor (5) serves as the power output for the main lifting mechanism (1) and the secondary lifting mechanism (2), characterized in that: The wall-building robot also includes a camera (3) located on top of the device gimbal (6), and a locking mechanism (4) is provided at the connection between the main lifting (1) and the chassis of the wall-building robot. The calibration method includes: Sp1: Measure the distance between the ceiling and the ground using camera (3), manually move the wall construction robot, select a flat, unobstructed ceiling, and measure the distance H from the ground to the ceiling. total And manually input the parameters; Sp2: Perform surface detection on the ceiling using the camera (3), and based on the results of the surface detection, obtain the observed values ​​of the distance H from the ceiling to the camera (3) and the angle α. Sp3: The distance from the device's pan-tilt unit (6) to the ground, i.e., the actual height of the device, is H1 = H total -H, where H1 is the actual measured value, used as a calibration reference; Sp4: The predetermined lifting height H2 of the device gimbal (6) can be obtained according to the number of rotations of the lifting motor (5). The difference Δ between H1 and H2 is the false position. After the robot performs multiple false position detections at different positions, the average value of Δ is taken as the setting value for this correction. Sp5: By adjusting the correction setpoint, the actual lifting height H1 of the equipment is equal to the predetermined lifting height H2 of the equipment, thus achieving adaptive height correction; When the camera (3) performs surface detection on the ceiling, the detection method used is: RANSAC random sampling fitting. Sp2-1: Consider a model with a minimum sampling set of cardinality n, where n is the minimum number of samples required to initialize the model parameters; and a sample set P, where the number of samples in set P is #(P)>n. Randomly select a subset S of P containing n samples from P to initialize the model M. Sp2-2: The set of samples in the remainder set SC = P\S whose error with model M is less than a certain set threshold t, together with S, constitute S*. S* is considered to be the set of interior points, and they constitute the consistent set of S. Sp2-3: If #(S*)≥N, it is considered that the correct model parameters have been obtained, and the new model M* is recalculated using the least squares method with the set S*; a new S is randomly selected again, and the above process is repeated. Sp2-4: If no consistent set is found after a certain number of samplings, the algorithm fails; otherwise, the largest consistent set obtained after sampling is selected to determine the internal and external points, and the algorithm ends.

2. The method for calibrating lifting height according to claim 1, characterized in that: When the camera (3) performs surface detection on the ceiling, it takes the average value of the angle α by detecting it multiple times, and uses it as the adjustment parameter. Then, by adjusting the locking mechanism (4), the main lifting (1) and the robot chassis are fixed to eliminate the deviation angle of the equipment gimbal (6). When α is not 0, when the main lifting (1) is stationary, the locking structure is adjusted to make α 0, so that the deviation angle of the equipment gimbal (6) can be adjusted.

3. The method for calibrating lifting height according to claim 1, characterized in that: When correcting the set value, when the desired height increases by H1, the motor is sent an increase of H1+Δ based on the existing Δ value to estimate the false position. At this time, the actual increase is H=H1+Δ-Δ, which is close to the desired value.

Images