High-precision positioning method for super high-rise building steel bar binding robot based on flexible cable driving

Abstract

The invention relates to a high-precision positioning method for a super high-rise building steel bar binding robot based on flexible cable driving, and relates to the technical field of automatic steel bar binding, and the method comprises the steps: obtaining real-time flexible cable deformation data of a plurality of first position points of the steel bar binding robot and real-time flexible cable vibration data of a plurality of second position points of the steel bar binding robot; according to the real-time flexible cable deformation data of the multiple first position points and the real-time flexible cable vibration data of the multiple second position points, whether secondary positioning is carried out at the next binding track point or not is judged; if yes, after a binding mechanism of the reinforcing steel bar binding robot moves to the next to-be-bound position, a reinforcing steel bar image is obtained, and the to-be-bound position is determined; according to the position to be bound and the real-time position of a binding mechanism of the steel bar binding robot, position compensation parameters are determined; and the position of the binding mechanism of the reinforcing steel bar binding robot is adjusted based on the position compensation parameters, and the method has the advantage of improving the positioning precision and efficiency of the reinforcing steel bar binding robot.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic steel bar binding, and particularly to a high-precision positioning method for a super high-rise building steel bar binding robot based on flexible cable driving. BACKGROUND

[0002] The steel bar binding robot is a kind of building robot, which is mainly used to replace manual operation in the steel bar binding construction process. The robot is composed of a robot walking mechanism, a binding mechanism, a control system, a power system, an APP mobile terminal and the like, and has functions of self-moving, automatic identification, automatic binding, automatic planning of walking path and the like. It is mainly suitable for steel bar binding of various prefabricated concrete members, such as composite boards, prefabricated walls, standardized pavements and the like. Compared with manual operation, the steel bar binding robot has significant advantages. For example, it takes at least 4 people 20 minutes to complete the steel bar binding of a prefabricated member by manual operation, while the steel bar binding robot can complete one binding point in an average of one second, which is 4-5 times the efficiency of manual binding. At the same time, the robot operation can also reduce the labor intensity of workers, improve the safety factor of workers during operation, and ensure the uniformity and stability of the bound steel bars. The super high-rise building steel bar binding robot based on flexible cable driving uses flexible cables instead of traditional rigid links, which can significantly reduce the weight of the mechanism and the inertia of the moving parts, and break through the constraints of hinge rotation angle and link extension length, thus showing obvious advantages in working space, load-to-weight ratio and adaptability.

[0003] In the prior art, the flexible cable of the super high-rise building steel bar binding robot based on flexible cable driving will produce elastic deformation when subjected to force, resulting in a difference between the actual length and the theoretical length, thereby affecting the positioning accuracy. Especially in super high-rise buildings, the flexible cable needs to bear a large self-weight and load, and the elastic deformation is more significant. Moreover, the construction environment of super high-rise buildings is complex, and wind load and vibration will affect the positioning of the robot. The flexible cable driving system is sensitive to vibration, which may cause positioning errors. The existing technology cannot compensate for the elastic deformation of the cable and external interference in real time, which will cause the positioning accuracy to decrease.

[0004] Therefore, it is necessary to provide a high-precision positioning method for a super high-rise building steel bar binding robot based on flexible cable driving, for improving the positioning accuracy and efficiency of the steel bar binding robot. SUMMARY

[0005] The application provides a high-precision positioning method for a flexible cable-driven steel binding robot for super-high-rise buildings, wherein the steel binding robot comprises a support part, a moving mechanism, a lifting mechanism and a binding mechanism, and the method comprises the following steps: acquiring real-time flexible cable deformation data of a plurality of first position points of the steel binding robot; acquiring real-time flexible cable vibration data of a plurality of second position points of the steel binding robot; judging whether secondary positioning is needed at a next binding track point according to the real-time flexible cable deformation data of the plurality of first position points and the real-time flexible cable vibration data of the plurality of second position points; if it is judged that secondary positioning is needed at the next binding track point, acquiring a steel image after the binding mechanism of the steel binding robot moves to a next position to be bound; determining the position to be bound according to the steel image; acquiring a real-time position of the binding mechanism of the steel binding robot; determining a position compensation parameter according to the position to be bound and the real-time position of the binding mechanism of the steel binding robot; and adjusting the position of the binding mechanism of the steel binding robot based on the position compensation parameter.

[0006] Furthermore, the acquisition of the real-time flexible cable deformation data of the plurality of first position points of the steel binding robot comprises the following steps: determining a plurality of first test conditions, wherein the first test conditions comprise a binding wire weight and a motion parameter; under each first test condition, acquiring test flexible cable deformation data of a plurality of first test positions of the steel binding robot and test positioning errors of the binding mechanism of the steel binding robot in the process that the binding mechanism of the steel binding robot moves from a first test track point to a second test track point; determining the plurality of first position points of the steel binding robot; and acquiring the real-time flexible cable deformation data of the plurality of first position points of the steel binding robot.

[0007] Furthermore, the determination of the plurality of first position points of the steel binding robot comprises the following steps: under each first test condition, determining a flexible cable deformation average value of each first test position according to the test flexible cable deformation data of the plurality of first test positions of the steel binding robot; for each first test position, calculating a correlation coefficient of the flexible cable deformation and the positioning error of the first test position according to the flexible cable deformation average value of the first test position and the test positioning error of the binding mechanism of the steel binding robot under each first test condition; and determining the plurality of first position points of the steel binding robot according to the correlation coefficient of the flexible cable deformation and the positioning error of each first test position.

[0008] Further, the real-time flexible cable vibration data of the plurality of second position points of the steel bar binding robot is obtained, including: determining a plurality of second test conditions, wherein the second test conditions include environmental wind conditions and motion parameters; under each second test condition, obtaining test flexible cable vibration data of a plurality of second test positions of the steel bar binding robot and test positioning errors of the binding mechanism of the steel bar binding robot in a process in which the binding mechanism of the steel bar binding robot moves from a first test trajectory point to a second test trajectory point; determining a plurality of second position points of the steel bar binding robot; and obtaining real-time flexible cable vibration data of the plurality of second position points of the steel bar binding robot.

[0009] Further, the plurality of second position points of the steel bar binding robot are determined, including: under each second test condition, determining a flexible cable vibration amplitude of each second test position according to the test flexible cable vibration data of the plurality of second test positions of the steel bar binding robot; for each second test position, calculating a correlation coefficient of flexible cable vibration and positioning error of the second test position according to the flexible cable vibration amplitude of the second test position and the test positioning error of the binding mechanism of the steel bar binding robot under each second test condition; and determining the plurality of second position points of the steel bar binding robot according to the correlation coefficient of flexible cable vibration and positioning error of each second test position.

[0010] Further, whether secondary positioning is performed at the next binding trajectory point is determined according to the real-time flexible cable deformation data of the plurality of first position points and the real-time flexible cable vibration data of the plurality of second position points, including: for each first position point, extracting a real-time flexible cable deformation feature vector of the first position point according to the real-time flexible cable deformation data of the first position point; for each second position point, extracting a real-time flexible cable vibration feature vector of the second position point according to the real-time flexible cable vibration data of the second position point; constructing an error prediction model, and predicting a positioning error of the next binding trajectory point through the error prediction model according to the real-time flexible cable deformation feature vector of each first position point and the real-time flexible cable vibration feature vector of each second position point; calculating a cumulative positioning error of the next binding trajectory point according to the positioning error of the next binding trajectory point; and determining whether secondary positioning is performed at the next binding trajectory point according to the cumulative positioning error of the next binding trajectory point.

[0011] Further, the position to be bound is determined according to the steel bar image, including: converting the steel bar image into a gray-scale image; converting the gray-scale image into a binary image; and determining the position to be bound based on a neighborhood window and the binary image.

[0012] Further, based on the neighborhood window and the binary image, the position to be bound is determined, comprising: based on the neighborhood window and the binary image, the position of the steel bar intersection image coordinate is determined; the steel bar intersection position camera coordinate is determined by converting the steel bar intersection position image coordinate from the image coordinate system to the camera coordinate system; the steel bar intersection position camera coordinate is converted from the camera coordinate system to the first coordinate system to determine the steel bar intersection position first coordinate, wherein the origin of the first coordinate system is determined based on the binding mechanism of the steel bar binding robot; and the position to be bound is determined according to the steel bar intersection position first coordinate.

[0013] Further, the real-time position of the binding mechanism of the steel bar binding robot is obtained, comprising: a plurality of positioning tags are arranged in the working area of the steel bar binding robot; and the real-time position of the binding mechanism of the steel bar binding robot is obtained by the plurality of positioning tags and the reader-writer arranged on the binding mechanism of the steel bar binding robot.

[0014] Further, the position compensation parameter is determined according to the position to be bound and the real-time position of the binding mechanism of the steel bar binding robot, comprising: the horizontal axis compensation parameter is determined according to the horizontal axis coordinate corresponding to the position to be bound and the horizontal axis coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot; and the vertical axis compensation parameter is determined according to the vertical axis coordinate corresponding to the position to be bound and the vertical axis coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot, wherein the position compensation parameter comprises the horizontal axis compensation parameter and the vertical axis compensation parameter.

[0015] Compared with the prior art, the high-precision positioning method of the steel bar binding robot for super-high-rise building based on flexible cable driving provided by the present specification has at least the following beneficial effects:

[0016] 1. By acquiring real-time deformation data of the flexible cable at multiple first position points and real-time vibration data of the flexible cable at multiple second position points, the state of the flexible cable during robot movement can be comprehensively understood. The deformation and vibration of the flexible cable directly affect the positional accuracy of the binding mechanism. Combining these two types of data allows for a more accurate assessment of the robot's actual positional deviation, providing a reliable basis for subsequent secondary positioning judgments. Based on the above data, it is determined whether to perform secondary positioning at the next binding trajectory point. This mechanism can promptly detect and correct potential positioning errors. After the robot moves to the next binding position, the image of the rebar is acquired again, and the binding position is determined. Comparing this with the real-time position of the binding mechanism further improves the accuracy of positioning, ensuring that the binding operation can accurately act on the target position. Position compensation parameters are determined based on the binding position and the real-time position of the binding mechanism, and the position of the binding mechanism is adjusted based on these parameters, achieving precise fine-tuning of the robot's position. This dynamic compensation and adjustment method can effectively eliminate the influence of various factors (such as the elastic deformation of the flexible cable, vibration, external interference, etc.) on the positioning accuracy, ensure the binding quality, and reduce the need for manual adjustment and intervention in robot positioning. The robot can automatically and accurately complete the positioning and binding operations, improve the automation level of construction, and save labor costs and time.

[0017] 2. Establish multiple initial test conditions incorporating the weight and motion parameters of the binding wire. Under each condition, acquire test flexible cable deformation data and the binding mechanism's positioning error at multiple initial test locations during the binding mechanism's movement. This comprehensive testing allows for a thorough understanding of the flexible cable deformation under different operating conditions and its impact on the binding mechanism's positioning, providing a rich data foundation for accurately locating key points. Calculate the correlation coefficient between the flexible cable deformation and positioning error at each initial test location, and determine multiple initial location points based on these coefficients. The correlation coefficient quantifies the degree of association between flexible cable deformation and positioning error; selecting locations with high correlation coefficients as initial location points indicates that the flexible cable deformation at these points has a more significant impact on the binding mechanism's positioning error. By focusing on these locations, flexible cable deformation can be monitored more effectively, thereby improving positioning accuracy.

[0018] 3. Multiple secondary test conditions incorporating environmental wind conditions and motion parameters were determined, fully considering the complexity of the construction environment for super high-rise buildings. Environmental wind conditions can cause vibrations in the flexible cable, thus affecting the positioning accuracy of the binding mechanism. By conducting tests under different environmental wind conditions and motion parameters, the relationship between flexible cable vibration and positioning error can be understood, providing a basis for adapting to complex environments. After acquiring real-time flexible cable vibration data from multiple secondary location points, the vibration status of the flexible cable can be monitored in real time. Attached Figure Description

[0019] The present specification will be further illustrated in the manner of exemplary embodiments, which will be described in detail by means of the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same reference numbers represent the same structures, wherein:

[0020] Figure 1 is a structural diagram of a flexible cable driven super high-rise building steel bar binding robot shown in an embodiment of the present application;

[0021] Figure 2 is a flowchart of a high-precision positioning method of a flexible cable driven super high-rise building steel bar binding robot shown in an embodiment of the present application;

[0022] Figure 3 is a flowchart of judging whether to perform secondary positioning at the next binding track point shown in an embodiment of the present application.

[0023] In the figure, 1 is a support part; 2 is a lifting mechanism; 3 is a moving mechanism; and 4 is a binding mechanism. DETAILED DESCRIPTION

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the following will briefly introduce the drawings needed to be used in the embodiment description.

[0025] Figure 1 is a structural diagram of a flexible cable driven super high-rise building steel bar binding robot shown in an embodiment of the present application, as shown in Figure 1 A flexible cable driven super high-rise building steel bar binding robot includes a support part 1, a moving mechanism 3, a lifting mechanism 2 and a binding mechanism 4.

[0026] The support part 1 includes a bearing frame and a guide slide rail, the guide slide rail is fixedly installed on the outer wall of the bearing frame, wherein the bearing frame is a common building machine truss, and the cross section of the guide slide rail is a T-shaped structure.

[0027] The moving mechanism 3 includes a guide sliding block, a control motor and a moving wheel fixedly installed on the output shaft of the control motor, the inner wall of the guide sliding block is in sliding fit with the outer wall of the guide slide rail, realizing the sliding connection of the guide sliding block and the guide slide rail. The control motor is fixedly installed on the inner wall of the guide sliding block, and the sliding of the guide sliding block is controlled through the rotation of the moving wheel, wherein the radial outer wall of the moving wheel is in rolling fit with the outer wall of the guide slide rail, and the control motor drives the moving wheel to rotate, thereby controlling the moving of the guide sliding block along the outer wall of the guide slide rail.

[0028] The binding mechanism 4 includes a binding robotic arm, an electric slide rail, and a lifting frame. The electric slide rail is fixedly installed on the outer wall of the lifting frame, and the lifting frame provides installation space for the electric slide rail. The binding robotic arm is set on the electric slide rail, and the electric slide rail controls the movement of the binding robotic arm, thereby adjusting the position of the output end of the binding robotic arm to facilitate binding of the reinforcing bars.

[0029] The lifting frame is raised and lowered by a lifting mechanism, which in turn controls the lifting and lowering of the binding robotic arm, thus achieving the lifting and lowering adjustment of the binding robotic arm.

[0030] The movement of the binding robot arm can be controlled by sliding and adjusting the guide slider and lifting and adjusting the lifting frame, which makes it easy to change the work area. It has a simple structure, low inertia, relatively light structure, high motion stability, high positioning accuracy, large translation space, easy replacement and maintenance of components, and low cost. At the same time, the movement of the binding robot arm can be controlled by electric slide rail, which can improve the accuracy of the binding position.

[0031] Figure 2 This is a flowchart illustrating a high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, as shown in one embodiment of this application. Figure 2 As shown, a high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive may include the following steps.

[0032] Step 110: Obtain real-time flexible cable deformation data at multiple first position points of the rebar tying robot.

[0033] Specifically, it includes:

[0034] Multiple first test conditions are determined, wherein the first test conditions include the weight of the binding wire and motion parameters;

[0035] Under each first test condition, during the process of the binding mechanism of the rebar binding robot moving from the first test trajectory point to the second test trajectory point, the test flexible cable deformation data of multiple first test positions of the rebar binding robot and the test positioning error of the binding mechanism of the rebar binding robot are obtained.

[0036] Determine multiple initial position points for the rebar tying robot;

[0037] Real-time deformation data of the flexible cable at multiple first position points of the rebar tying robot are obtained.

[0038] Specifically, the first test condition is used to simulate different working conditions that the rebar tying robot may encounter in actual working scenarios, in order to comprehensively evaluate the impact of the deformation of the flexible cable at different locations under various conditions on the positioning error.

[0039] The binding wire as a key consumable in the steel bar binding operation, its weight will have a direct impact on the work of the binding mechanism. Different specifications and materials of the binding wire have different weights, setting different binding wire weight test conditions can investigate the stress of the flexible cable and the stability of the binding mechanism when the steel bar binding robot handles different weight binding wires. For example, lighter binding wires may cause the flexible cable to bear relatively small tension, while heavier binding wires may cause the flexible cable to bear greater tension, thereby affecting the deformation degree of the flexible cable and the positioning accuracy of the binding mechanism.

[0040] The motion parameters cover multiple aspects of the binding mechanism during movement, such as movement speed, acceleration, motion trajectory, etc. Different movement speeds will affect the efficiency of the binding mechanism in completing the binding operation, and may also affect the dynamic response of the flexible cable; changes in acceleration may cause the flexible cable to be subjected to additional inertial forces, further changing its deformation state.

[0041] In order to comprehensively and accurately evaluate the performance of the steel bar binding robot under different working conditions, a plurality of representative first test conditions need to be set. By simulating various situations that may occur in actual work, a series of different binding wire weight values are determined according to the actual work requirements and the design parameters of the robot, for example, three different specifications of light, medium and heavy binding wires can be selected, each corresponding to a different weight. At the same time, a plurality of motion parameter combinations are set, including different movement speeds (such as slow, medium and fast), accelerations (such as small, medium and large accelerations) and motion trajectories (such as straight line trajectories, curved trajectories, etc.). These binding wire weights and motion parameters are combined to form a plurality of first test conditions.

[0042] A plurality of first test positions can be determined manually. Strain sensors can be set at each first test position for collecting test flexible cable deformation data at the first test position.

[0043] Starting from the first test trajectory point, the binding mechanism of the steel bar binding robot is controlled to move from the first test trajectory point to the second test trajectory point. After the movement is completed, the final position coordinates of the binding mechanism of the steel bar binding robot are obtained, and the deviation between the final position coordinates of the binding mechanism of the steel bar binding robot and the theoretical coordinates of the second test trajectory point is calculated as the test positioning error of the binding mechanism of the steel bar binding robot.

[0044] In some embodiments, determining a plurality of first position points of the steel bar binding robot includes:

[0045] According to the test flexible cable deformation data of the plurality of first test positions of the steel bar binding robot under each first test condition, a flexible cable deformation average value of each first test position is determined. Specifically, during movement of the binding mechanism of the steel bar binding robot from the first test trajectory point to the second test trajectory point, the deformation data of the flexible cable fluctuates due to the influence of the motion state. The flexible cable deformation values of the first test position at a plurality of consecutive time points during movement of the binding mechanism of the steel bar binding robot from the first test trajectory point to the second test trajectory point are averaged to obtain the flexible cable deformation average value of the first test position.

[0046] For each first test position, the correlation coefficient of the flexible cable deformation and the positioning error of the binding mechanism of the steel bar binding robot is calculated according to the flexible cable deformation average value of the first test position and the test positioning error of the binding mechanism of the steel bar binding robot under each first test condition.

[0047] According to the correlation coefficient of the flexible cable deformation and the positioning error of each first test position, a plurality of first position points of the steel bar binding robot are determined.

[0048] Specifically, the first position points are specific positions for subsequent real-time monitoring of flexible cable deformation data. Determining these position points helps to comprehensively and systematically understand the deformation of the flexible cable at different positions, providing detailed data support for performance analysis and optimization of the robot. These position points should cover the key stress parts and areas prone to deformation of the flexible cable.

[0049] The deformation of the flexible cable can affect the positioning accuracy of the binding mechanism. By calculating the correlation coefficient of the flexible cable deformation and the positioning error, the degree of correlation between the two can be quantified. The greater the absolute value of the correlation coefficient, the stronger the linear relationship between the flexible cable deformation and the positioning error, that is, the more significant the influence of the flexible cable deformation on the positioning error. This helps to identify those flexible cable positions that have a greater impact on the positioning accuracy of the binding mechanism, providing a basis for subsequent determination of the first position points.

[0050] The flexible cable deformation average value of each first test position under each first test condition and the corresponding binding mechanism test positioning error data are collected. For example, for a certain first test position, n flexible cable deformation average values d1, d2, …, dn and n binding mechanism test positioning errors e1, e2, …, en are obtained under n first test conditions. The correlation coefficient of the flexible cable deformation and the positioning error is calculated using the correlation coefficient calculation formula.

[0051] A first correlation coefficient threshold value is set, which can be determined according to actual needs and experience. For example, the first correlation coefficient threshold value is set to 0.7. The correlation coefficient of the flexible cable deformation and the positioning error of each first test position is compared with the set threshold value. If the absolute value of the correlation coefficient of a certain first test position is greater than or equal to the first correlation coefficient threshold value, it is considered that this position has a significant influence on the positioning accuracy of the binding mechanism, and it is determined as a first position point. All first test positions that meet the conditions are screened out, and these positions are the plurality of first position points of the steel bar binding robot. For example, after comparison, it is found that the absolute values of the correlation coefficients of 5 first test positions are greater than or equal to 0.7, so these 5 positions are determined as the first position points.

[0052] A strain sensor can be arranged at each first position point to obtain real-time flexible cable deformation data of the plurality of first position points of the steel bar binding robot.

[0053] In step 120, real-time flexible cable vibration data of the plurality of second position points of the steel bar binding robot is obtained.

[0054] Specifically, it includes:

[0055] A plurality of second test conditions are determined, wherein the second test conditions include environmental wind conditions and motion parameters;

[0056] Under each second test condition, the test flexible cable vibration data of the plurality of second test positions of the steel bar binding robot and the test positioning error of the binding mechanism of the steel bar binding robot during the movement of the binding mechanism of the steel bar binding robot from the first test trajectory point to the second test trajectory point are obtained.

[0057] A plurality of second position points of the steel bar binding robot are determined.

[0058] Real-time flexible cable vibration data of the plurality of second position points of the steel bar binding robot is obtained.

[0059] Specifically, the construction site environment of super high-rise buildings is complex, and the wind conditions have a significant impact on the vibration of the flexible cable. Different wind speed, wind direction, and wind force variation frequency will change the stress state of the flexible cable, and then affect its vibration. For example, strong wind may cause the flexible cable to produce a larger vibration amplitude, while light wind may cause relatively smaller vibration. Therefore, it is necessary to set different wind speed levels (such as light wind, moderate wind, and strong wind), different wind directions (such as downwind, upwind, and crosswind), and different wind force variation frequencies (such as steady wind and gust) to simulate the wind conditions in the actual environment. The motion parameters cover multiple aspects of the binding mechanism during movement, such as moving speed, acceleration, motion trajectory, etc. Different combinations of motion parameters will affect the dynamic response of the flexible cable, and then affect its vibration characteristics. For example, fast moving speed may cause the flexible cable to produce greater vibration, while complex motion trajectory may increase the complexity of the flexible cable vibration. According to the actual work requirements and the design parameters of the robot, combined with the environmental characteristics of the super high-rise building construction site, a series of different combinations of wind speed, wind direction, and wind force variation frequency, as well as different combinations of moving speed, acceleration, and motion trajectory are determined. These environmental wind conditions and motion parameters are combined to form a variety of second test conditions.

[0060] Vibration sensors are set at each second test position to collect vibration data of the flexible cable. The vibration sensors can monitor the vibration amplitude, frequency, and other information of the flexible cable in real time. During the movement of the binding mechanism of the steel reinforcement binding robot from the first test trajectory point to the second test trajectory point, the vibration data of each second test position is continuously recorded.

[0061] Starting from the first test trajectory point, the binding mechanism of the steel reinforcement binding robot is controlled to move from the first test trajectory point to the second test trajectory point. After completing the movement, the final position coordinates of the binding mechanism of the steel reinforcement binding robot are obtained using high-precision positioning measurement equipment (such as laser range finder, visual positioning system, etc.), and the deviation between the final position coordinates of the binding mechanism of the steel reinforcement binding robot and the theoretical coordinates of the second test trajectory point is calculated as the test positioning error of the binding mechanism of the steel reinforcement binding robot.

[0062] In some embodiments, a plurality of second position points of the steel reinforcement binding robot are determined, including:

[0063] Under each second test condition, the vibration amplitude of the flexible cable at each second test position is determined according to the test flexible cable vibration data of the plurality of second test positions of the steel reinforcement binding robot.

[0064] For each second test position, the correlation coefficient of the flexible cable vibration and the test positioning error of the binding mechanism of the steel reinforcement binding robot at the second test position is calculated according to the vibration amplitude of the flexible cable at the second test position and the test positioning error of the binding mechanism of the steel reinforcement binding robot at the second test position under each second test condition.

[0065] Determine the plurality of second position points of the steel bar binding robot according to the correlation coefficient of the flexible cable vibration and the positioning error of each second test position.

[0066] The second position points are specific positions for subsequent real-time monitoring of flexible cable vibration data. Determining these position points helps to comprehensively and systematically understand the vibration conditions of the flexible cable at different positions, providing detailed data support for performance analysis and optimization of the robot. These position points should cover the key stress points of the flexible cable and the areas prone to vibration. Combining the structural characteristics of the steel bar binding robot, the layout of the flexible cable, and the actual work requirements, a plurality of representative second position points are preliminarily determined through theoretical analysis and simulation calculation.

[0067] Under each second test condition, the vibration data of the flexible cable will fluctuate due to the influence of various factors such as environmental wind conditions and motion parameters. Calculate the vibration amplitude of the flexible cable at each second test position.

[0068] The vibration of the flexible cable may affect the positioning accuracy of the binding mechanism. By calculating the correlation coefficient of the flexible cable vibration and the positioning error, the degree of correlation between the two can be quantified. The larger the absolute value of the correlation coefficient, the stronger the linear relationship between the flexible cable vibration and the positioning error, i.e., the more significant the influence of the flexible cable vibration on the positioning error. This helps to identify those positions of the flexible cable that have a greater impact on the positioning accuracy of the binding mechanism, providing a basis for subsequent determination of the second position points.

[0069] Collect the flexible cable vibration amplitude and corresponding binding mechanism test positioning error data at each second test position under each second test condition. For example, for a certain second test position, under n second test conditions, n flexible cable vibration amplitudes A1, A2, …, An and n binding mechanism test positioning errors e1, e2, …, en are obtained respectively. Use the correlation coefficient calculation formula (such as the Pearson correlation coefficient formula) to calculate the correlation coefficient of the flexible cable vibration and the positioning error.

[0070] Set a second correlation coefficient threshold, which can be determined according to actual needs and experience. For example, set the second correlation coefficient threshold to 0.7. Compare the correlation coefficient of the flexible cable vibration and the positioning error of each second test position with the set threshold. If the absolute value of the correlation coefficient of a certain second test position is greater than or equal to the second correlation coefficient threshold, it is considered that this position has a significant impact on the positioning accuracy of the binding mechanism, and it is determined as a second position point. Screen out all second test positions that meet the conditions, and these positions are the plurality of second position points of the steel bar binding robot. For example, after comparison, it is found that the absolute values of the correlation coefficients of 4 second test positions are greater than or equal to 0.7, so these 4 positions are determined as second position points.

[0071] Step 130, according to the real-time flexible cable deformation data of the plurality of first position points and the real-time flexible cable vibration data of the plurality of second position points, determining whether to perform secondary positioning at the next binding track point.

[0072] Figure 3 is a flowchart for determining whether to perform secondary positioning at the next binding track point in an embodiment of the present application, as shown in Figure 3 Step 130 can specifically include:

[0073] For each first position point, according to the real-time flexible cable deformation data of the first position point, extracting a real-time flexible cable deformation feature vector of the first position point;

[0074] For each second position point, according to the real-time flexible cable vibration data of the second position point, extracting a real-time flexible cable vibration feature vector of the second position point;

[0075] Constructing an error prediction model, and through the error prediction model, predicting the positioning error of the next binding track point according to the real-time flexible cable deformation feature vector of each first position point and the real-time flexible cable vibration feature vector of each second position point;

[0076] According to the positioning error of the next binding track point, calculating the cumulative positioning error of the next binding track point;

[0077] According to the cumulative positioning error of the next binding track point, determining whether to perform secondary positioning at the next binding track point.

[0078] Specifically, for each first position point, the real-time flexible cable deformation data of the first position point is preprocessed, including noise removal, filtering and other operations. For example, moving average filtering method or Kalman filtering method is used to eliminate random interference and measurement error in the data, and improve the quality and reliability of the data. Key parameters reflecting the deformation characteristics of the flexible cable are extracted from the preprocessed real-time flexible cable deformation data of the first position point to form a feature vector, for example:

[0079] Deformation mean: calculating the mean value of the flexible cable deformation data within a certain time window, reflecting the average deformation degree of the flexible cable in that time period.

[0080] Deformation variance: measuring the dispersion degree of the flexible cable deformation data around the mean value, reflecting the fluctuation of the deformation.

[0081] Maximum deformation value: recording the maximum value of the flexible cable deformation within the time window, reflecting the extreme case of the deformation.

[0082] Deformation frequency: analyzing the frequency components of the deformation data through Fourier transform and other methods to determine the main frequency of the flexible cable deformation, and the frequency feature may be related to the motion state of the robot and external environmental factors.

[0083] The extracted features are combined in a certain order into a vector, which is the real-time flexible cable deformation feature vector of the first position point. For example, if four features of deformation mean, deformation variance, maximum deformation value, and deformation frequency are extracted, the feature vector can be represented as v1=[v11, v12, v13, v14], where v11 is the deformation mean, v12 is the deformation variance, v13 is the maximum deformation value, and v14 is the deformation frequency.

[0084] For each second position point, the real-time flexible cable vibration data of the second position point is preprocessed to remove noise and outliers. Wavelet denoising and other methods can be used to effectively remove noise interference according to the characteristics of the vibration signal by selecting appropriate wavelet basis functions and decomposition levels. Key parameters that can reflect the vibration characteristics of the flexible cable are extracted from the preprocessed real-time flexible cable vibration data of the second position point to construct a feature vector. For example:

[0085] Vibration amplitude: reflects the intensity of vibration.

[0086] Vibration frequency: the main frequency component of the vibration signal determined by frequency spectrum analysis.

[0087] Vibration phase: describes the starting position of the vibration signal in time.

[0088] The extracted vibration features are combined into a vector as the real-time flexible cable vibration feature vector of the second position point.

[0089] The error prediction model is used to establish the mapping relationship between the extracted flexible cable deformation and vibration feature vectors and the positioning error, so as to realize the prediction of the positioning error of the next binding track point. The error prediction model can be a neural network model.

[0090] A large amount of historical data is collected, including the flexible cable deformation feature vectors of the first position point, the flexible cable vibration feature vectors of the second position point, and the actual positioning error of the corresponding next binding track point under different working conditions. These data are divided into training set and test set, and the training set is used to train the error prediction model to adjust the parameters of the error prediction model so that the error prediction model can accurately learn the mapping relationship between the features and the positioning error. Cross-validation and other methods can be used to evaluate the performance of the error prediction model during training to prevent overfitting.

[0091] The real-time acquired flexible cable deformation feature vector of the first position point and the flexible cable vibration feature vector of the second position point are input into the trained error prediction model, and the model outputs the positioning error prediction value of the next binding track point.

[0092] The accumulated positioning error reflects the overall positioning deviation of the binding mechanism of the steel bar binding robot from the starting position to the current binding trajectory point and the predicted next binding trajectory point. By calculating the accumulated positioning error, the positioning performance of the steel bar binding robot can be more comprehensively evaluated to determine whether the positioning of the steel bar binding robot is within the allowed error range. The accumulated positioning error can be calculated according to the following formula:

[0093]

[0094] wherein △L all is the accumulated positioning error, M is the number of trajectory points between the last completed secondary positioning trajectory point and the next binding trajectory point, △L m is the positioning error predicted by the error prediction model of the mth trajectory point between the last completed secondary positioning trajectory point and the next binding trajectory point, and △L next is the positioning error of the next binding trajectory point.

[0095] Secondary positioning is performed to improve the positioning accuracy of the steel bar binding robot. When the accumulated positioning error exceeds a certain threshold, it indicates that the positioning of the steel bar binding robot has deviated from the expected position, and secondary positioning is needed to correct the error and ensure the quality of the steel bar binding work.

[0096] According to the accuracy requirements of the steel bar binding work and the performance indicators of the steel bar binding robot, a reasonable accumulated positioning error threshold is set. This threshold can be determined through experiments and experience, for example, according to the requirements of the building specifications for steel bar binding positions, combined with the positioning accuracy capability of the steel bar binding robot, an error threshold that can guarantee the binding quality is set. The accumulated positioning error of the next binding trajectory point is compared with the set error threshold. If the accumulated positioning error is greater than or equal to the error threshold, it is determined that secondary positioning is needed at the next binding trajectory point; if the accumulated positioning error is less than the error threshold, it is determined that secondary positioning is not needed, and the robot can continue the binding work according to the original plan.

[0097] Step 140, if it is determined that secondary positioning is needed at the next binding trajectory point, after the binding mechanism of the steel bar binding robot moves to the next binding position, the steel bar image is acquired.

[0098] Specifically, an image acquisition device can be provided on the binding mechanism, and after the binding mechanism of the steel bar binding robot moves to the next binding position, the steel bar image is acquired through the image acquisition device.

[0099] Step 150, the binding position is determined according to the steel bar image.

[0100] Specifically, it includes:

[0101] convert the steel bar image into a gray-scale image;

[0102] convert the gray-scale image into a binary image;

[0103] determine the position to be bound based on the neighborhood window and the binary image.

[0104] Specifically, the color steel bar image contains information of three channels of red (R), green (G), and blue (B), and has a large amount of data and is relatively complex to process. The gray-scale image only contains brightness information, and converting the color image into a gray-scale image can greatly reduce the amount of data, reduce the computational complexity of subsequent image processing, and retain the main features of the image, facilitating subsequent binary processing and other operations. A weighted average method is used to convert the color image into a gray-scale image by traversing each pixel point in the image.

[0105] For each pixel point in the gray-scale image, if the gray-scale value is greater than or equal to the threshold T, the value of the pixel point is set to 255 (white), indicating the target region; if the gray-scale value is less than the threshold T, the value of the pixel point is set to 0 (black), indicating the background region. By traversing each pixel point in the image and applying the above rule for binary processing, a binary image can be obtained. The threshold can be selected by maximizing the inter-class variance.

[0106] In some embodiments, determining the position to be bound based on the neighborhood window and the binary image includes:

[0107] determining a steel bar intersection position image coordinate based on the neighborhood window and the binary image;

[0108] converting the steel bar intersection position image coordinate from an image coordinate system to a camera coordinate system to determine a steel bar intersection position camera coordinate;

[0109] converting the steel bar intersection position camera coordinate from the camera coordinate system to a first coordinate system to determine a steel bar intersection position first coordinate, wherein the origin of the first coordinate system is determined based on a binding mechanism of a steel bar binding robot;

[0110] determining the position to be bound according to the steel bar intersection position first coordinate.

[0111] Specifically, the neighborhood window is a small window sliding on the image for analyzing the distribution of pixels within the window. The size of the window can be selected according to the thickness of the steel bar and the resolution of the image, for example, a 5x5 or 7x7 window is selected. The neighborhood window is slid on the binary image, and for each window position, the distribution of white pixels (representing steel bars) within the window is counted. Whether there is a steel bar intersection can be determined by counting the number of connected regions of white pixels within the window, shape features, etc. For example, if there are multiple connected regions within the window and these connected regions intersect with each other, it is considered that the window position may have a steel bar intersection. When a steel bar intersection is detected, the image coordinates of the center point of the window are recorded as the image coordinates of the steel bar intersection position.

[0112] The image coordinate system is a coordinate system based on image pixels, while the camera coordinate system is a three-dimensional coordinate system based on the camera optical center. Converting image coordinates to camera coordinates can link two-dimensional image information with three-dimensional actual space information.

[0113] Before coordinate conversion, the camera needs to be calibrated to determine the intrinsic and extrinsic parameters of the camera. The intrinsic parameters of the camera include focal length, principal point coordinates, etc., and the extrinsic parameters include the rotation matrix and translation vector of the camera, which can be obtained by camera calibration algorithms (such as Zhang Zhengyou calibration method). According to the parameters obtained by camera calibration, the pinhole camera model can be used for coordinate conversion.

[0114] The origin of the first coordinate system can be the center point of the reader / writer on the binding mechanism of the steel bar binding robot. Converting camera coordinates to coordinates in the first coordinate system can make coordinate information directly correspond to the operation space of the steel bar binding robot, facilitating the steel bar binding robot to position and bind according to coordinate information. Determining the conversion relationship between the camera coordinate system and the first coordinate system can usually be achieved by hand-eye calibration. Hand-eye calibration is a process of determining the relative position and attitude relationship between the camera and the robot, and through hand-eye calibration, the rotation matrix and translation vector of the camera coordinate system to the first coordinate system can be obtained. Through the known camera coordinates and the conversion relationship obtained by hand-eye calibration, the steel bar intersection position camera coordinates are converted from the camera coordinate system to the first coordinate system.

[0115] The position to be bound is relative to the position of the robot binding mechanism, and by combining the real-time position of the binding mechanism and the first coordinate of the steel bar intersection position, the position where the robot needs to go for binding operation can be accurately determined. The real-time position coordinates (Xrobot, Yrobot, Zrobot) of the binding mechanism in the first coordinate system are obtained through the sensors (such as encoders, inertial measurement units, etc.) of the robot.

[0116] The world coordinate system is a fixed, global coordinate system used to describe the positions and attitudes of various objects in the entire work scene. It usually takes a certain fixed reference point (such as a corner of a building, a specific marker on the ground, etc.) as the origin, and defines the directions of the X, Y, and Z coordinate axes. The conversion relationship between the world coordinate system and the first coordinate system can be determined in advance by methods such as hand-eye calibration, and the coordinates of the reinforcement intersection position in the world coordinate system can be determined by coordinate transformation according to the conversion relationship between the world coordinate system and the first coordinate system.

[0117] In step 160, the real-time position of the binding mechanism of the reinforcement binding robot is obtained.

[0118] Specifically, it includes:

[0119] In the working area of the reinforcement binding robot, a plurality of positioning tags are arranged;

[0120] The real-time position of the binding mechanism of the reinforcement binding robot is obtained through the plurality of positioning tags and the reader arranged on the binding mechanism of the reinforcement binding robot.

[0121] Specifically, the positioning tag (for example, an ultra-wideband (UWB) positioning tag, etc.) is a device for emitting a specific signal, which can provide position reference information for the robot. Each positioning tag has unique identification information, and through these identification information and the signals emitted by the tags, the position of the tag in space can be determined. Reasonably arranging a plurality of positioning tags in the working area of the reinforcement binding robot can construct a position positioning network covering the entire working area, so that the binding mechanism of the reinforcement binding robot can receive signals from at least part of the positioning tags at any position in the working area, thereby realizing real-time monitoring of the position of the binding mechanism of the reinforcement binding robot.

[0122] For areas that the reinforcement binding robot frequently passes through or needs to perform accurate operations during the work process, such as areas with dense reinforcement intersections, the density of positioning tags can be appropriately increased to improve the position positioning accuracy of these areas.

[0123] The working area of the reinforcement binding robot can be divided into a plurality of sub-areas, and the density of positioning tags in the sub-areas can be determined according to the following formula:

[0124]

[0125] Where γ is the density of positioning tags in the sub-area, n is the number of reinforcement intersections included in the sub-area, n0 is a preset number of reinforcement intersections, which is a positive integer, γ0 is a preset density of positioning tags, which is a positive integer, and [] is the integer part operation.

[0126] It can be understood that the above formula calculates the ratio of the number of steel bar intersection points in the sub-region to the preset number of steel bar intersection points, which reflects the multiple of the density of steel bar intersection points in the sub-region relative to the preset standard. Multiply the above ratio by the preset positioning tag density to obtain an intermediate result, which represents the positioning tag density theoretical value adjusted according to the density of steel bar intersection points in the sub-region. Finally, take the integer part of the intermediate result to obtain the final positioning tag density of the sub-region. More positioning tags are arranged in key areas with more steel bar intersection points, thereby improving the positioning accuracy of the robot in these areas and ensuring that the robot can more accurately reach the steel bar intersection points for binding operations.

[0127] The reader / writer is a device for receiving the positioning tag transmission signal, which can analyze the identification information and signal parameters of the tag, and calculate the position of the binding mechanism according to these information. The reader / writer is usually installed on the binding mechanism of the steel bar binding robot, and moves with the binding mechanism, and receives the signals of the surrounding positioning tags in real time. The reader / writer records the arrival time of the positioning tag transmission signal, and calculates the distance between the reader / writer and the positioning tag according to the signal propagation speed (approximately the speed of light in air). When the reader / writer receives the signals of at least three positioning tags, the three-dimensional coordinate position of the reader / writer (i.e. the binding mechanism) in space can be determined by triangulation.

[0128] Step 170, determining the position compensation parameter according to the real-time position of the binding mechanism of the steel bar binding robot and the position to be bound.

[0129] Specifically includes:

[0130] According to the horizontal axis (i.e. X-axis) coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot and the horizontal axis coordinate corresponding to the position to be bound, a horizontal axis compensation parameter is determined, wherein the horizontal axis compensation parameter can be the difference ΔX between the horizontal axis coordinate corresponding to the position to be bound and the horizontal axis coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot.

[0131] According to the vertical axis (i.e. Y-axis) coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot and the vertical axis coordinate corresponding to the position to be bound, a vertical axis compensation parameter is determined, wherein the position compensation parameter includes the horizontal axis compensation parameter and the vertical axis compensation parameter, and the vertical axis compensation parameter can be the difference ΔY between the vertical axis coordinate corresponding to the position to be bound and the vertical axis coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot.

[0132] According to the height direction (i.e. Y-axis) coordinate corresponding to the position to be bound and the height direction coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot, a height direction compensation parameter is determined, wherein the height direction compensation parameter can be the difference ΔZ between the height direction coordinate corresponding to the position to be bound and the height direction coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot.

[0133] In step 180, the position of the binding mechanism of the steel bar binding robot is adjusted based on the position compensation parameter.

[0134] Specifically, the controller of the steel bar binding robot receives the ΔX, ΔY and ΔZ values, generates corresponding control instructions according to these parameters, and controls the moving mechanism and the lifting mechanism to adjust the position of the binding mechanism of the steel bar binding robot.

[0135] Finally, it should be understood that the embodiments described in the specification are only used to illustrate the principles of the embodiments of the specification. Other variations can also belong to the scope of the specification. Therefore, as an example but not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the specification are not limited to the embodiments explicitly introduced and described in the specification.

Claims

1. A high-precision positioning method for a flexible-cable-driven steel-reinforcement tying robot for super-high-rise buildings, wherein, The steel bar binding robot comprises a support part, a moving mechanism, a lifting mechanism and a binding mechanism, and the method comprises the following steps: Obtain real-time flexible cable deformation data of a plurality of first position points of the steel bar binding robot; Obtain real-time flexible cable vibration data of a plurality of second position points of the steel bar binding robot; Determine whether to perform secondary positioning at a next binding track point according to the real-time flexible cable deformation data of the plurality of first position points and the real-time flexible cable vibration data of the plurality of second position points; If it is determined to perform secondary positioning at the next binding track point, obtain a steel bar image after the binding mechanism of the steel bar binding robot moves to a next position to be bound; Determine the position to be bound according to the steel bar image; Obtain real-time position of the binding mechanism of the steel bar binding robot; Determine a position compensation parameter according to the position to be bound and the real-time position of the binding mechanism of the steel bar binding robot; Adjust the position of the binding mechanism of the steel bar binding robot based on the position compensation parameter.

2. The high-precision positioning method for a steel binding robot for super high-rise buildings based on flexible cable driving according to claim 1, characterized in that, Obtaining real-time flexible cable deformation data of a plurality of first position points of the steel bar binding robot comprises: Determining a plurality of first test conditions, wherein the first test conditions include the weight of the binding wire and the motion parameters; Under each first test condition, obtaining test flexible cable deformation data of a plurality of first test positions of the steel bar binding robot and test positioning errors of the binding mechanism of the steel bar binding robot in the process that the binding mechanism of the steel bar binding robot moves from a first test track point to a second test track point; Determining a plurality of first position points of the steel bar binding robot; Obtaining real-time flexible cable deformation data of a plurality of first position points of the steel bar binding robot.

3. The high-precision positioning method for a steel binding robot for super high-rise buildings based on flexible cable driving according to claim 2, characterized in that, Determining a plurality of first position points of the steel bar binding robot comprises: Under each first test condition, determining the average flexible cable deformation of each first test position according to the test flexible cable deformation data of the plurality of first test positions of the steel bar binding robot; For each first test position, calculating the correlation coefficient of the flexible cable deformation and the positioning error of the first test position according to the average flexible cable deformation of the first test position and the test positioning error of the binding mechanism of the steel bar binding robot under each first test condition; Determining a plurality of first position points of the steel bar binding robot according to the correlation coefficient of the flexible cable deformation and the positioning error of each first test position.

4. The high-precision positioning method for a flexible cable-driven steel binding robot for super high-rise buildings according to claim 1, characterized in that, Obtaining real-time flexible cable vibration data of a plurality of second position points of the steel bar binding robot comprises: Determining a plurality of second test conditions, wherein the second test conditions include the environmental wind conditions and the motion parameters; Under each second test condition, obtaining test flexible cable vibration data of a plurality of second test positions of the steel bar binding robot and test positioning errors of the binding mechanism of the steel bar binding robot in the process that the binding mechanism of the steel bar binding robot moves from a first test track point to a second test track point; Determining a plurality of second position points of the steel bar binding robot; Obtaining real-time flexible cable vibration data of a plurality of second position points of the steel bar binding robot.

5. The high-precision positioning method for a flexible cable-driven steel binding robot for super high-rise buildings according to claim 4, characterized in that, Determining a plurality of second position points of the steel bar binding robot comprises: determining, according to the flexible cable vibration data of the plurality of second test positions of the steel bar binding robot under each second test condition, a flexible cable vibration amplitude of each second test position; for each second test position, calculating a correlation coefficient of the flexible cable vibration and the positioning error of the second test position according to the flexible cable vibration amplitude of the second test position and the test positioning error of the binding mechanism of the steel bar binding robot under each second test condition; determining a plurality of second position points of the steel bar binding robot according to the correlation coefficient of the flexible cable vibration and the positioning error of each second test position.

6. The high-precision positioning method for a steel binding robot for super high-rise buildings based on flexible cable driving according to any one of claims 1-5, characterized in that, judging whether to perform secondary positioning at the next binding track point according to the real-time flexible cable deformation data of the plurality of first position points and the real-time flexible cable vibration data of the plurality of second position points, comprising: for each first position point, extracting a real-time flexible cable deformation feature vector of the first position point according to the real-time flexible cable deformation data of the first position point; for each second position point, extracting a real-time flexible cable vibration feature vector of the second position point according to the real-time flexible cable vibration data of the second position point; constructing an error prediction model, and predicting the positioning error of the next binding track point according to the real-time flexible cable deformation feature vector of each first position point and the real-time flexible cable vibration feature vector of each second position point through the error prediction model; calculating the cumulative positioning error of the next binding track point according to the positioning error of the next binding track point; judging whether to perform secondary positioning at the next binding track point according to the cumulative positioning error of the next binding track point.

7. The high-precision positioning method for a steel binding robot for super high-rise buildings based on flexible cable driving according to any one of claims 1-5, characterized in that, determining the to-be-bound position according to the steel bar image, comprising: converting the steel bar image into a gray-scale image; converting the gray-scale image into a binary image; determining the to-be-bound position based on the neighborhood window and the binary image.

8. The high-precision positioning method for a flexible cable-driven steel binding robot for super high-rise buildings according to claim 7, characterized in that, determining the to-be-bound position based on the neighborhood window and the binary image, comprising: determining a steel bar intersection position image coordinate based on the neighborhood window and the binary image; converting the steel bar intersection position image coordinate from an image coordinate system to a camera coordinate system to determine a steel bar intersection position camera coordinate; converting the steel bar intersection position camera coordinate from the camera coordinate system to a first coordinate system to determine a steel bar intersection position first coordinate, wherein the origin of the first coordinate system is determined based on the binding mechanism of the steel bar binding robot; determining the to-be-bound position according to the steel bar intersection position first coordinate.

9. The high-precision positioning method for a steel binding robot for super high-rise buildings based on flexible cable driving according to any one of claims 1-5, characterized in that, acquiring the real-time position of the binding mechanism of the steel bar binding robot, comprising: setting a plurality of positioning tags in the working area of the steel bar binding robot; acquiring the real-time position of the binding mechanism of the steel bar binding robot through the plurality of positioning tags and a reader-writer arranged on the binding mechanism of the steel bar binding robot.

10. The high-precision positioning method for a steel binding robot for super high-rise buildings based on flexible cable driving according to any one of claims 1-5, characterized in that, determining the position compensation parameter according to the to-be-bound position and the real-time position of the binding mechanism of the steel bar binding robot, comprising: determining a horizontal axis compensation parameter according to the horizontal axis coordinate corresponding to the to-be-bound position and the horizontal axis coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot; determining a vertical axis compensation parameter according to the vertical axis coordinate corresponding to the to-be-bound position and the vertical axis coordinate corresponding to the real-time position of the binding mechanism of the steel bar binding robot, wherein the position compensation parameter comprises the horizontal axis compensation parameter and the vertical axis compensation parameter.

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