A high-precision positioning method for a steel binding robot for super-high-rise buildings based on flexible cable driving

Abstract

The application relates to a high-precision positioning method of a flexible cable-driven super-high-rise building steel binding robot, and relates to the technical field of automatic steel binding, and comprises the following steps: acquiring real-time flexible cable deformation data of a plurality of first position points of a steel binding robot and real-time flexible cable vibration data of a plurality of second position points; 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 yes, acquiring a steel image after a binding mechanism of the steel binding robot moves to a next position to be bound, and determining the position to be bound; determining a position compensation parameter according to the position to be bound and a 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, so that the positioning precision and efficiency of the steel binding robot are improved.

Description

Technical Field

[0001] This invention relates to the field of automated rebar tying technology, and in particular to a high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive. Background Technology

[0002] Rebar tying robots are a type of construction robot primarily used to replace manual labor in the rebar tying process. This robot consists of a walking mechanism, a tying mechanism, a control system, a power system, and a mobile app. It features self-movement, automatic recognition, automatic tying, and automatic path planning. It is mainly suitable for tying rebar in various precast concrete components, such as composite slabs, precast walls, and standardized pavements. Compared to manual labor, rebar tying robots offer significant advantages. For example, manually tying the rebar of a precast component requires at least four people and 20 minutes, while a rebar tying robot can complete one tying point per second on average, making it 4-5 times more efficient than manual tying. Simultaneously, robotic operation reduces worker fatigue, improves worker safety, and ensures the uniformity and stability of the tied rebar. Rebar tying robots for ultra-high-rise buildings based on flexible cable drive use flexible cables instead of traditional rigid links, significantly reducing the weight of the mechanism and the inertia of moving parts. This overcomes the limitations of hinge angles and link extension lengths, thus exhibiting significant advantages in terms of workspace, load-to-weight ratio, and adaptability.

[0003] In existing technologies, the flexible cables in rebar tying robots for super high-rise buildings, driven by flexible cables, undergo elastic deformation under stress, leading to a discrepancy between the actual and theoretical lengths, thus affecting positioning accuracy. This is particularly true in super high-rise buildings, where the flexible cables must withstand significant weight and loads, resulting in even more pronounced elastic deformation. Furthermore, the complex construction environment of super high-rise buildings, with wind loads and vibrations, can impact the robot's positioning. Flexible cable-driven systems are highly sensitive to vibration, which can cause positioning errors. Existing technologies cannot compensate for the elastic deformation of the cable and external disturbances in real time, leading to a decrease in positioning accuracy.

[0004] Therefore, there is a need to provide a high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, in order to improve the positioning accuracy and efficiency of the rebar tying robot. Summary of the Invention

[0005] This invention provides a high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive. The rebar tying robot includes a support unit, a moving mechanism, a lifting mechanism, and a tying mechanism. The method comprises: acquiring real-time flexible cable deformation data at multiple first position points of the rebar tying robot; acquiring real-time flexible cable vibration data at multiple second position points of the rebar tying robot; determining, based on the real-time flexible cable deformation data at the multiple first position points and the real-time flexible cable vibration data at the multiple second position points, whether secondary positioning is required at the next tying trajectory point; if secondary positioning is required at the next tying trajectory point, acquiring a rebar image after the tying mechanism of the rebar tying robot moves to the next tying position; determining the tying position based on the rebar image; acquiring the real-time position of the tying mechanism of the rebar tying robot; determining position compensation parameters based on the tying position and the real-time position of the tying mechanism of the rebar tying robot; and adjusting the position of the tying mechanism of the rebar tying robot based on the position compensation parameters.

[0006] Furthermore, real-time flexible cable deformation data of multiple first position points of the rebar tying robot are acquired, including: determining multiple first test conditions, wherein the first test conditions include the weight of the tying wire and motion parameters; under each first test condition, acquiring test flexible cable deformation data of multiple first test positions of the rebar tying robot and test positioning error of the tying mechanism of the rebar tying robot as the tying mechanism moves from a first test trajectory point to a second test trajectory point; determining multiple first position points of the rebar tying robot; and acquiring real-time flexible cable deformation data of multiple first position points of the rebar tying robot.

[0007] Furthermore, determining multiple first position points of the rebar tying robot includes: under each first test condition, determining the average flexible cable deformation at each first test position based on the test flexible cable deformation data at multiple first test positions of the rebar tying robot; for each first test position, calculating the correlation coefficient between the flexible cable deformation and the positioning error at the first test position based on the average flexible cable deformation at the first test position and the test positioning error of the tying mechanism of the rebar tying robot under each first test condition; and determining multiple first position points of the rebar tying robot based on the correlation coefficient between the flexible cable deformation and the positioning error at each first test position.

[0008] Furthermore, real-time flexible cable vibration data of multiple second position points of the rebar tying robot are acquired, including: determining multiple second test conditions, wherein the second test conditions include environmental wind conditions and motion parameters; under each second test condition, acquiring test flexible cable vibration data of multiple second test positions of the rebar tying robot and test positioning error of the rebar tying robot's tying mechanism as the tying mechanism moves from the first test trajectory point to the second test trajectory point; determining multiple second position points of the rebar tying robot; and acquiring real-time flexible cable vibration data of multiple second position points of the rebar tying robot.

[0009] Furthermore, determining multiple second position points of the rebar tying robot includes: under each second test condition, determining the vibration amplitude of the flexible cable at each second test position based on the test flexible cable vibration data of multiple second test positions of the rebar tying robot; for each second test position, calculating the correlation coefficient between the flexible cable vibration and the positioning error at the second test position based on the vibration amplitude of the flexible cable at the second test position and the test positioning error of the tying mechanism of the rebar tying robot under each second test condition; and determining multiple second position points of the rebar tying robot based on the correlation coefficient between the flexible cable vibration and the positioning error at each second test position.

[0010] Furthermore, based on the real-time flexible cable deformation data from multiple first position points and the real-time flexible cable vibration data from multiple second position points, it is determined whether secondary positioning should be performed at the next binding trajectory point. This includes: for each first position point, extracting the real-time flexible cable deformation feature vector based on the real-time flexible cable deformation data of the first position point; for each second position point, extracting the real-time flexible cable vibration feature vector based on the real-time flexible cable vibration data of the second position point; constructing an error prediction model, and using the error prediction model to predict the positioning error of the next binding trajectory point based on 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 the cumulative positioning error of the next binding trajectory point based on the positioning error of the next binding trajectory point; and determining whether secondary positioning should be performed at the next binding trajectory point based on the cumulative positioning error of the next binding trajectory point.

[0011] Furthermore, based on the rebar image, the location to be tied is determined, including: converting the rebar image into a grayscale image; converting the grayscale image into a binarized image; and determining the location to be tied based on the neighborhood window and the binarized image.

[0012] Furthermore, based on the neighborhood window and the binarized image, the position to be tied is determined, including: determining the image coordinates of the rebar intersection position based on the neighborhood window and the binarized image; transforming the image coordinates of the rebar intersection position from the image coordinate system to the camera coordinate system to determine the camera coordinates of the rebar intersection position; transforming the camera coordinates of the rebar intersection position from the camera coordinate system to the first coordinate system to determine the first coordinates of the rebar intersection position, wherein the origin of the first coordinate system is determined based on the tying mechanism of the rebar tying robot; and determining the position to be tied based on the first coordinates of the rebar intersection position.

[0013] Furthermore, the real-time position of the rebar tying robot's tying mechanism is obtained by: setting multiple positioning tags within the working area of ​​the rebar tying robot; and obtaining the real-time position of the rebar tying robot's tying mechanism through the multiple positioning tags and a reader / writer set on the rebar tying mechanism.

[0014] Furthermore, based on the position to be bound and the real-time position of the binding mechanism of the rebar binding robot, position compensation parameters are determined, including: determining horizontal axis compensation parameters based on the horizontal axis coordinates corresponding to the position to be bound and the horizontal axis coordinates corresponding to the real-time position of the binding mechanism of the rebar binding robot; determining vertical axis compensation parameters based on the vertical axis coordinates corresponding to the position to be bound and the vertical axis coordinates corresponding to the real-time position of the binding mechanism of the rebar binding robot, wherein the position compensation parameters include horizontal axis compensation parameters and vertical axis compensation parameters.

[0015] Compared with existing technologies, the high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive provided in this specification has at least the following advantages:

[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 degree of automation 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] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0020] Figure 1 This is a structural diagram of a rebar tying robot for super high-rise buildings based on flexible cable drive, as shown in one embodiment of this application.

[0021] 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.

[0022] Figure 3 This is a flowchart illustrating, in one embodiment of the present application, a method for determining whether secondary positioning should be performed at the next binding trajectory point.

[0023] In the diagram, 1 is the support unit; 2 is the lifting mechanism; 3 is the moving mechanism; and 4 is the binding mechanism. Detailed Implementation

[0024] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below.

[0025] Figure 1 This is a structural diagram of a rebar tying robot for super high-rise buildings based on flexible cable drive, as shown in one embodiment of this application. Figure 1 As shown, a super high-rise building rebar tying robot based on flexible cable drive includes a support part 1, a moving mechanism 3, a lifting mechanism 2, and a tying mechanism 4.

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

[0027] The moving mechanism 3 includes a guide slider, a control motor, and a moving wheel fixedly mounted on the output shaft of the control motor. The inner wall of the guide slider slides against the outer wall of the guide rail, achieving a sliding connection between the guide slider and the guide rail. The control motor is fixedly mounted on the inner wall of the guide slider, and the sliding of the guide slider is controlled by the rotation of the moving wheel. The radial outer wall of the moving wheel rolls against the outer wall of the guide rail. The control motor drives the moving wheel to rotate, thereby controlling the guide slider to move along the outer wall of the guide 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] As a key consumable in rebar tying operations, the weight of binding wire directly affects the operation of the tying mechanism. Binding wires of different specifications and materials have varying weights. Setting different test conditions for binding wire weights allows us to examine the stress on the flexible cable and the stability of the tying mechanism when the rebar tying robot handles binding wires of different weights. For example, lighter binding wire may result in less tension on the flexible cable, while heavier binding wire may subject the flexible cable to greater tension, thus affecting the degree of deformation of the flexible cable and the positioning accuracy of the tying mechanism.

[0040] Motion parameters encompass multiple aspects of the lashing mechanism during its movement, such as speed, acceleration, and trajectory. Different speeds affect the efficiency of the lashing mechanism in completing the lashing operation and may also influence the dynamic response of the flexible cable; changes in acceleration may cause the flexible cable to be subjected to additional inertial forces, further altering its deformation state.

[0041] To comprehensively and accurately evaluate the performance of the rebar tying robot under different working conditions, it is necessary to set up a variety of representative primary test conditions. This involves simulating various situations that might occur in actual work. Based on actual work requirements and the robot's design parameters, a series of different tying wire weight values ​​are determined; for example, light, medium, and heavy tying wires can be selected, each corresponding to a different weight. Simultaneously, various combinations of motion parameters are set, including different moving speeds (e.g., slow, medium, fast), accelerations (e.g., small, medium, large accelerations), and motion trajectories (e.g., straight lines, curves). These combinations of tying wire weights and motion parameters form a variety of primary test conditions.

[0042] Multiple initial test locations can be determined manually. Strain sensors can be installed at each initial test location to collect deformation data of the flexible cable at that location.

[0043] Starting from the first test trajectory point, the binding mechanism of the rebar 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 rebar binding robot are obtained. The deviation between the final position coordinates of the binding mechanism of the rebar 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 rebar binding robot.

[0044] In some embodiments, determining a plurality of first position points of the rebar tying robot includes:

[0045] Under each first test condition, based on the test flexible cable deformation data of multiple first test positions of the rebar tying robot, the mean value of flexible cable deformation at each first test position is determined. Specifically, during the process of the rebar tying robot's tying mechanism moving from the first test trajectory point to the second test trajectory point, the deformation data of the flexible cable will fluctuate due to the influence of the motion state. The mean value of flexible cable deformation at the first test position can be obtained by averaging the flexible cable deformation values ​​at multiple consecutive time points during the process of the rebar tying robot's tying mechanism moving from the first test trajectory point to the second test trajectory point.

[0046] For each first test position, the correlation coefficient between the flexible cable deformation and the positioning error at the first test position is calculated based on the mean flexible cable deformation at the first test position and the test positioning error of the binding mechanism of the rebar binding robot under each first test condition.

[0047] Based on the correlation coefficient between the flexible cable deformation and the positioning error at each first test position, multiple first position points of the rebar tying robot are determined.

[0048] Specifically, the first location point is a specific location used for subsequent real-time monitoring of the deformation data of the flexible cable. Determining these location points helps to comprehensively and systematically understand the deformation of the flexible cable at different locations, providing detailed data support for the performance analysis and optimization of the robot. These location points should cover the key stress-bearing 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 between the flexible cable deformation 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 deformation and the positioning error, that is, the more significant the impact of the flexible cable deformation on the positioning error. This helps to identify the locations of the flexible cable that have a significant impact on the positioning accuracy of the binding mechanism, providing a basis for subsequently determining the first position point.

[0050] Collect the mean flexible cable deformation and the corresponding binding mechanism positioning error data for each first test location under each first test condition. For example, for a certain first test location, under n first test conditions, obtain n mean flexible cable deformation values ​​d1, d2, ..., dn and n binding mechanism positioning errors e1, e2, ..., en. Use the correlation coefficient calculation formula to calculate the correlation coefficient between flexible cable deformation and positioning error.

[0051] A first correlation coefficient threshold is set, which can be determined based on actual needs and experience. For example, the first correlation coefficient threshold can be set to 0.7. The correlation coefficient between the flexible cable deformation and the positioning error at each first test location is compared with the set threshold. If the absolute value of the correlation coefficient at a certain first test location is greater than or equal to the first correlation coefficient threshold, then that location is considered to have a significant impact on the positioning accuracy of the binding mechanism and is identified as a first location point. All first test locations that meet the conditions are selected; these locations are the multiple first location points of the rebar binding robot. For example, after comparison, it is found that the absolute value of the correlation coefficient at 5 first test locations is greater than or equal to 0.7, then these 5 locations are identified as first location points.

[0052] Strain sensors can be set at each first position point to acquire real-time flexible cable deformation data at multiple first position points of the rebar tying robot.

[0053] Step 120: Obtain real-time flexible cable vibration data at multiple second position points of the rebar tying robot.

[0054] Specifically, it includes:

[0055] Multiple second test conditions are determined, including environmental wind conditions and motion parameters;

[0056] Under each second 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 vibration data of multiple second test positions of the rebar binding robot and the test positioning error of the binding mechanism of the rebar binding robot are obtained.

[0057] Determine multiple secondary position points for the rebar tying robot;

[0058] Real-time flexible cable vibration data were acquired at multiple second position points of the rebar tying robot.

[0059] Specifically, the construction site environment of super high-rise buildings is complex, and wind conditions have a significant impact on the vibration of flexible cables. Different wind speeds, wind directions, and wind force change frequencies alter the stress state of the flexible cables, thus affecting their vibration. For example, strong winds may cause the flexible cables to generate large vibration amplitudes, while light winds may result in relatively small vibrations. Therefore, it is necessary to set different wind speed levels (e.g., light, moderate, strong winds), different wind directions (e.g., tailwind, headwind, crosswind), and different wind force change frequencies (e.g., steady wind, gusts) to simulate wind conditions in the actual environment. Motion parameters cover multiple aspects of the binding mechanism during movement, such as movement speed, acceleration, and movement trajectory. Different combinations of motion parameters affect the dynamic response of the flexible cables, thereby affecting their vibration characteristics. For example, rapid movement speeds may cause the flexible cables to generate greater vibrations, while complex movement trajectories may increase the complexity of the flexible cable vibration. Based on actual work requirements and robot design parameters, combined with the environmental characteristics of super high-rise building construction sites, a series of different combinations of wind speed, wind direction, and wind force change frequencies, as well as different combinations of movement speed, acceleration, and movement trajectory, are determined. These environmental wind conditions and motion parameters are combined to form a variety of secondary test conditions.

[0060] Vibration sensors are installed at each of the second test locations to collect vibration data of the flexible cable. These sensors can monitor the vibration amplitude, frequency, and other information of the flexible cable in real time. Vibration data at each second test location is continuously recorded as the binding mechanism moves from the first test trajectory point to the second test trajectory point.

[0061] Starting from the first test trajectory point, the binding mechanism of the rebar binding robot is controlled to move from the first test trajectory point to the second test trajectory point. After the movement is completed, high-precision positioning and measurement equipment (such as a laser rangefinder, vision positioning system, etc.) is used to obtain the final position coordinates of the binding mechanism of the rebar binding robot. The deviation between the final position coordinates of the binding mechanism of the rebar 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 rebar binding robot.

[0062] In some embodiments, determining a plurality of second location points for the rebar tying robot includes:

[0063] Under each second test condition, the vibration amplitude of the flexible cable at each second test position is determined based on the vibration data of the flexible cable at multiple second test positions of the rebar tying robot.

[0064] For each second test position, the correlation coefficient between the flexible cable vibration and the positioning error at the second test position is calculated based on the vibration amplitude of the flexible cable at the second test position and the test positioning error of the binding mechanism of the rebar binding robot under each second test condition.

[0065] Based on the correlation coefficient between the flexible cable vibration and the positioning error at each second test position, multiple second position points of the rebar tying robot are determined.

[0066] The secondary location points are specific positions used for subsequent real-time monitoring of the flexible cable's vibration data. Determining these locations helps to comprehensively and systematically understand the vibration of the flexible cable at different positions, providing detailed data support for robot performance analysis and optimization. These location points should cover the key stress-bearing parts and vibration-prone areas of the flexible cable. Based on the structural characteristics of the rebar tying robot, the layout of the flexible cable, and actual working requirements, several representative secondary location points were initially determined through theoretical analysis and simulation calculations.

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

[0068] Vibration of the flexible cable can affect the positioning accuracy of the binding mechanism. By calculating the correlation coefficient between flexible cable vibration and 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 flexible cable vibration and positioning error, indicating a more significant impact of flexible cable vibration on positioning error. This helps identify the locations of the flexible cable that have a significant impact on the positioning accuracy of the binding mechanism, providing a basis for subsequently determining the second position point.

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

[0070] A second correlation coefficient threshold is set, which can be determined based on actual needs and experience. For example, the second correlation coefficient threshold can be set to 0.7. The correlation coefficient between the flexible cable vibration and the positioning error at each second test location is compared with the set threshold. If the absolute value of the correlation coefficient at a certain second test location is greater than or equal to the second correlation coefficient threshold, then that location is considered to have a significant impact on the positioning accuracy of the binding mechanism and is identified as a second location point. All second test locations that meet the conditions are selected; these locations are the multiple second location points of the rebar binding robot. For example, after comparison, it is found that the absolute value of the correlation coefficient at four second test locations is greater than or equal to 0.7, then these four locations are identified as second location points.

[0071] Step 130: Based on the real-time flexible cable deformation data of multiple first position points and the real-time flexible cable vibration data of multiple second position points, determine whether to perform secondary positioning at the next binding trajectory point.

[0072] Figure 3 This is a flowchart illustrating, in one embodiment of this application, a method for determining whether secondary positioning is required at the next binding trajectory point, as shown below. Figure 3 As shown, step 130 may specifically include:

[0073] For each first location point, extract the real-time flexible cable deformation feature vector of the first location point based on the real-time flexible cable deformation data of the first location point;

[0074] For each second position point, extract the real-time flexible cable vibration feature vector of the second position point based on the real-time flexible cable vibration data of the second position point;

[0075] An error prediction model is constructed, and the positioning error of the next binding trajectory point is predicted based on 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] Calculate the cumulative positioning error of the next binding trajectory point based on the positioning error of the next binding trajectory point;

[0077] Based on the cumulative positioning error of the next binding trajectory point, determine whether to perform secondary positioning at the next binding trajectory point.

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

[0079] Mean Deformation: The average value of the deformation data of the flexible cable within a certain time window is calculated, reflecting the average degree of deformation of the flexible cable during that time period.

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

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

[0082] Deformation frequency: The frequency components of the deformation data are analyzed by methods such as Fourier transform to determine the main frequency of the flexible cable deformation. The frequency characteristics may be related to the robot's motion state and external environmental factors.

[0083] The extracted features are combined into a vector in a certain order, which is the real-time flexible cable deformation feature vector of the first position point. For example, if four features are extracted: deformation mean, deformation variance, maximum deformation value, and deformation frequency, 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 location point, the real-time flexible cable vibration data at that location point is preprocessed to remove noise and outliers. Wavelet denoising methods can be used, selecting appropriate wavelet basis functions and decomposition levels based on the characteristics of the vibration signal to effectively remove noise interference. Key parameters reflecting the vibration characteristics of the flexible cable are extracted from the preprocessed real-time flexible cable vibration data at the second location point to construct a feature vector. For example:

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

[0086] Vibration frequency: The main frequency components of the vibration signal determined through 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, which serves as the real-time flexible cable vibration feature vector at the second position point.

[0089] The error prediction model works by using extracted flexible cable deformation and vibration feature vectors to establish a mapping relationship between features and positioning errors, thereby predicting the positioning error of the next binding trajectory point. The error prediction model can be a neural network model.

[0090] A large amount of historical data was collected, including the flexible cable deformation feature vector at the first position point, the flexible cable vibration feature vector at the second position point, and the actual positioning error of the corresponding next binding trajectory point under different working conditions. This data was divided into training and testing sets. The error prediction model was trained using the training set, and its parameters were adjusted to ensure it accurately learned the mapping relationship between features and positioning errors. Cross-validation and other methods were used during training to evaluate the performance of the error prediction model and prevent overfitting.

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

[0092] Cumulative positioning error reflects the overall positioning deviation of the rebar tying robot's tying mechanism from its starting position to the current tying trajectory point and the predicted next tying trajectory point. By calculating the cumulative positioning error, the positioning performance of the rebar tying robot can be more comprehensively evaluated, and it can be determined whether the robot's positioning is within the allowable error range. The cumulative positioning error can be calculated using the following formula:

[0093]

[0094] Among them, △L all To accumulate the positioning error, M is the number of trajectory points between the most recent trajectory point that completed secondary positioning and the next binding trajectory point, and ΔL is the cumulative positioning error. m The positioning error predicted by the error prediction model for the m-th trajectory point between the most recently completed secondary positioning trajectory point and the next binding trajectory point is ΔL. next The positioning error for the next binding trajectory point.

[0095] Secondary positioning is used to improve the positioning accuracy of the rebar tying robot. When the cumulative positioning error exceeds a certain threshold, it indicates that the positioning of the rebar tying robot has deviated from the expected position, and secondary positioning is required to correct the error and ensure the quality of the rebar tying operation.

[0096] Based on the precision requirements of rebar tying operations and the performance indicators of the rebar tying robot, a reasonable cumulative positioning error threshold is set. This threshold can be determined through experiments and experience. For example, based on the requirements of building codes for rebar tying positions and combined with the positioning accuracy capability of the rebar tying robot, an error threshold that can guarantee tying quality can be set. The cumulative positioning error of the next tying trajectory point is compared with the set error threshold. If the cumulative positioning error is greater than or equal to the error threshold, it is determined that secondary positioning is required at the next tying trajectory point; if the cumulative positioning error is less than the error threshold, it is determined that secondary positioning is not required, and the robot can continue the tying operation as planned.

[0097] Step 140: If it is determined that secondary positioning will be performed at the next binding trajectory point, then after the binding mechanism of the rebar binding robot moves to the next binding position, the rebar image is obtained.

[0098] Specifically, an image acquisition device can be installed on the binding mechanism. After the binding mechanism of the rebar binding robot moves to the next binding position, the image of the rebar can be acquired through the image acquisition device.

[0099] Step 150: Determine the binding position based on the rebar image.

[0100] Specifically, it includes:

[0101] Convert the rebar image to a grayscale image;

[0102] Convert a grayscale image to a binary image;

[0103] The location to be ligated is determined based on the neighborhood window and the binarized image.

[0104] Specifically, color steel bar images contain information from three channels: red (R), green (G), and blue (B), resulting in a large data volume and relatively complex processing. Grayscale images, on the other hand, only contain brightness information. Converting a color image to grayscale significantly reduces the data volume, lowers the computational complexity of subsequent image processing, and preserves the image's main features, facilitating subsequent binarization and other operations. A weighted average method is used to convert the color image to a grayscale image by traversing each pixel in the image.

[0105] For each pixel in a grayscale image, if its grayscale value is greater than or equal to a threshold T, the pixel's value is set to 255 (white), representing the target region; if its grayscale value is less than the threshold T, the pixel's value is set to 0 (black), representing the background region. By iterating through each pixel in the image and applying the above rules for binarization, a binarized image can be obtained. The threshold can be selected by maximizing the inter-class variance.

[0106] In some embodiments, determining the location to be ligated based on a neighborhood window and a binarized image includes:

[0107] Based on the neighborhood window and the binarized image, determine the image coordinates of the rebar intersection location;

[0108] Transform the image coordinates of the rebar intersection location from the image coordinate system to the camera coordinate system to determine the camera coordinates of the rebar intersection location;

[0109] Transform the camera coordinates at the rebar intersection position from the camera coordinate system to the first coordinate system to determine the first coordinates of the rebar intersection position. The origin of the first coordinate system is determined based on the rebar binding mechanism of the rebar binding robot.

[0110] Determine the binding position based on the first coordinate of the rebar intersection.

[0111] Specifically, the neighborhood window is a small window that slides across the image to analyze the distribution of pixels within it. The window size can be chosen based on the thickness of the rebar and the image resolution; for example, a 5×5 or 7×7 window can be selected. The neighborhood window slides across the binarized image, and for each window location, the distribution of white pixels (representing rebar) within the window is statistically analyzed. The presence of rebar intersections can be determined by calculating the number and shape characteristics of connected regions within the white pixels of the window. For example, if multiple connected regions exist within the window and these regions intersect, a rebar intersection is considered likely at that window location. When a rebar intersection is detected, the image coordinates of the window's center point are recorded as the image coordinates of the rebar intersection location.

[0112] Image coordinates are based on image pixels, while camera coordinates are a three-dimensional coordinate system based on the camera's optical center. Converting image coordinates to camera coordinates allows us to link two-dimensional image information with three-dimensional spatial information.

[0113] Before performing coordinate transformation, the camera needs to be calibrated to determine its intrinsic and extrinsic parameters. The camera's intrinsic parameters include focal length and principal point coordinates, while its extrinsic parameters include the camera's rotation matrix and translation vector. These parameters can be obtained using camera calibration algorithms (such as the Zhang Zhengyou calibration method). Based on the parameters obtained from the camera calibration, a pinhole camera model can be used for coordinate transformation.

[0114] The origin of the first coordinate system can be the center point of the reader on the tying mechanism of the rebar tying robot. Converting the camera coordinates to coordinates in the first coordinate system allows the coordinate information to directly correspond to the operating space of the rebar tying robot, facilitating the robot's positioning and tying operations based on the coordinate information. Determining the transformation relationship between the camera coordinate system and the first coordinate system is typically achieved through hand-eye calibration. Hand-eye calibration is the process of determining the relative position and attitude relationship between the camera and the robot. Through hand-eye calibration, the rotation matrix and translation vector from the camera coordinate system to the first coordinate system can be obtained. Using the known camera coordinates and the transformation relationship obtained from hand-eye calibration, the camera coordinates at the rebar intersection position are transformed from the camera coordinate system to the first coordinate system.

[0115] The binding position is relative to the robot's binding mechanism. By combining the real-time position of the binding mechanism with the first coordinate of the rebar intersection, the position where the robot needs to go to perform the 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 robot's sensors (such as encoders, inertial measurement units, etc.).

[0116] The world coordinate system is a fixed, global coordinate system used to describe the position and orientation of various objects in the entire work environment. It typically uses a fixed reference point (such as a corner of a building or a specific mark on the ground) as its origin and defines the directions of the X, Y, and Z axes. The transformation relationship between the world coordinate system and the first coordinate system can be predetermined using methods such as hand-eye calibration. Based on this transformation relationship, the first coordinate of the rebar intersection position is transformed to determine the coordinate value of the position to be tied in the world coordinate system.

[0117] Step 160: Obtain the real-time position of the rebar tying robot's tying mechanism.

[0118] Specifically, it includes:

[0119] Multiple positioning tags are set up within the working area of ​​the rebar tying robot;

[0120] The real-time position of the rebar tying robot's tying mechanism is obtained by using multiple positioning tags and readers set on the tying mechanism.

[0121] Specifically, positioning tags (e.g., ultra-wideband (UWB) positioning tags) are devices used to emit specific signals, providing the robot with position reference information. Each positioning tag has unique identification information, and its spatial location can be determined using this information and the signals it emits. By strategically placing multiple positioning tags within the working area of ​​the rebar tying robot, a positional network covering the entire area can be constructed. This ensures that the robot's tying mechanism can receive signals from at least some of the positioning tags at any location within the working area, thereby enabling real-time monitoring of the robot's tying mechanism's position.

[0122] For areas that the rebar tying robot frequently passes through or requires precise operations during its work, such as areas with dense rebar intersections, the density of positioning tags can be appropriately increased to improve the positioning accuracy in these areas.

[0123] The working area of ​​the rebar tying robot can be divided into multiple sub-areas, and the density of positioning tags in each sub-area can be determined using the following formula:

[0124]

[0125] Where γ is the density of the location tags in the sub-region, n is the number of rebar intersections included in the sub-region, n0 is the preset number of rebar intersections (a positive integer), γ0 is the preset density of the location tags (a positive integer), and [] represents the integer part extraction operation.

[0126] Understandably, the above formula calculates the ratio of the number of rebar intersections within a sub-region to the preset number of rebar intersections. This ratio reflects the density of rebar intersections within the sub-region relative to a preset standard. Multiplying this ratio by the preset positioning tag density yields an intermediate result, representing the theoretical value of the positioning tag density adjusted based on the density of rebar intersections within the sub-region. Finally, the integer part of this intermediate result is rounded to obtain the final sub-region positioning tag density. This allows for the placement of more positioning tags in critical areas with a high number of rebar intersections, thereby improving the robot's positioning accuracy in these areas and ensuring that the robot can more accurately reach the rebar intersections for binding operations.

[0127] A reader / writer is a device used to receive signals emitted by positioning tags. It can parse the tag's identification information and signal parameters, and calculate the position of the binding mechanism based on this information. The reader / writer is typically mounted on the binding mechanism of a rebar binding robot, moving with the binding mechanism and receiving signals from surrounding positioning tags in real time. The reader / writer records the arrival time of the positioning tag's signal and calculates the distance between the reader / writer and the positioning tag based on the signal propagation speed (approximately the speed of light in air). When the reader / writer receives signals from at least three positioning tags, its three-dimensional coordinate position in space can be determined using triangulation.

[0128] Step 170: Determine the position compensation parameters based on the position to be tied and the real-time position of the tying mechanism of the rebar tying robot.

[0129] Specifically, it includes:

[0130] Based on the horizontal axis coordinates corresponding to the position to be tied and the horizontal axis (i.e., X-axis) coordinates corresponding to the real-time position of the tying mechanism of the rebar tying robot, the horizontal axis compensation parameter is determined. The horizontal axis compensation parameter can be the difference ΔX between the horizontal axis coordinates corresponding to the position to be tied and the horizontal axis coordinates corresponding to the real-time position of the tying mechanism of the rebar tying robot.

[0131] Based on the vertical axis (i.e., Y-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 rebar binding robot, the vertical axis compensation parameter is determined. The position compensation parameter includes the horizontal axis compensation parameter and the vertical axis compensation parameter. 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 rebar binding robot.

[0132] Based on 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 rebar binding robot, the height direction compensation parameter is determined. 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 rebar binding robot.

[0133] Step 180: Adjust the position of the binding mechanism of the rebar binding robot based on the position compensation parameters.

[0134] Specifically, the controller of the rebar tying robot receives ΔX, ΔY, and ΔZ values, generates corresponding control commands based on these parameters, and controls the moving mechanism and lifting mechanism to adjust the position of the rebar tying mechanism of the robot.

[0135] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, wherein, The rebar tying robot includes a support unit, a moving mechanism, a lifting mechanism, and a tying mechanism, characterized in that the method includes: Acquire real-time flexible cable deformation data at multiple first position points of the rebar tying robot; Real-time flexible cable vibration data were acquired at multiple second position points of the rebar tying robot. Based on the real-time deformation data of the flexible cable at multiple first position points and the real-time vibration data of the flexible cable at multiple second position points, it is determined whether to perform secondary positioning of the binding mechanism of the rebar binding robot at the next binding trajectory point. If it is determined that secondary positioning is required at the next binding trajectory point, the image of the rebar is acquired after the binding mechanism of the rebar binding robot moves to the next binding position. Determine the location to be tied based on the image of the reinforcing bars; Obtain the real-time position of the rebar tying robot's tying mechanism; The position compensation parameters are determined based on the position to be tied and the real-time position of the tying mechanism of the rebar tying robot. The position of the rebar tying robot's tying mechanism is adjusted based on the position compensation parameters. Determine multiple initial position points for the rebar tying robot, including: Under each first test condition, the mean value of flexible cable deformation at each first test position is determined based on the test flexible cable deformation data at multiple first test positions of the rebar tying robot, wherein the first test condition includes the weight of the tying wire and motion parameters; For each first test position, the correlation coefficient between the flexible cable deformation and the positioning error at the first test position is calculated based on the mean flexible cable deformation at the first test position and the test positioning error of the binding mechanism of the rebar binding robot under each first test condition. Based on the correlation coefficient between the flexible cable deformation and the positioning error at each first test position, multiple first position points of the rebar binding robot are determined. Determine multiple secondary position points for the rebar tying robot, including: Under each second test condition, the vibration amplitude of the flexible cable at each second test position is determined based on the vibration data of the flexible cable at multiple second test positions of the rebar tying robot. The second test conditions include environmental wind conditions and motion parameters. For each second test position, the correlation coefficient between the flexible cable vibration and the positioning error at the second test position is calculated based on the vibration amplitude of the flexible cable at the second test position and the test positioning error of the binding mechanism of the rebar binding robot under each second test condition. Based on the correlation coefficient between the flexible cable vibration and the positioning error at each second test position, multiple second position points of the rebar tying robot are determined.

2. The high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive according to claim 1, characterized in that, Real-time flexible cable deformation data at multiple first position points of the rebar tying robot are acquired, including: Determine multiple first test conditions; 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. Determine multiple initial position points for the rebar tying robot; Real-time deformation data of the flexible cable at multiple first position points of the rebar tying robot are obtained.

3. The high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive according to claim 1, characterized in that, Real-time flexible cable vibration data were acquired at multiple second position points of the rebar tying robot, including: Determine multiple second test conditions; Under each second 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 vibration data of multiple second test positions of the rebar binding robot and the test positioning error of the binding mechanism of the rebar binding robot are obtained. Determine multiple secondary position points for the rebar tying robot; Real-time flexible cable vibration data were acquired at multiple second position points of the rebar tying robot.

4. A high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, as described in any one of claims 1-3, characterized in that, Based on real-time flexible cable deformation data from multiple first location points and real-time flexible cable vibration data from multiple second location points, it is determined whether secondary positioning should be performed at the next binding trajectory point, including: For each first location point, extract the real-time flexible cable deformation feature vector of the first location point based on the real-time flexible cable deformation data of the first location point; For each second position point, extract the real-time flexible cable vibration feature vector of the second position point based on the real-time flexible cable vibration data of the second position point; An error prediction model is constructed, and the positioning error of the next binding trajectory point is predicted based on 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. Calculate the cumulative positioning error of the next binding trajectory point based on the positioning error of the next binding trajectory point; Based on the cumulative positioning error of the next binding trajectory point, determine whether to perform secondary positioning at the next binding trajectory point.

5. A high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, as described in any one of claims 1-3, characterized in that, Based on the rebar image, determine the locations to be tied, including: Convert the rebar image to a grayscale image; Convert a grayscale image to a binary image; The location to be ligated is determined based on the neighborhood window and the binarized image.

6. A high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, as described in claim 5, is characterized in that... Based on the neighborhood window and the binarized image, the location to be ligated is determined, including: Based on the neighborhood window and the binarized image, determine the image coordinates of the rebar intersection position; Transform the image coordinates of the rebar intersection location from the image coordinate system to the camera coordinate system to determine the camera coordinates of the rebar intersection location; Transform the camera coordinates at the rebar intersection position from the camera coordinate system to the first coordinate system to determine the first coordinates of the rebar intersection position. The origin of the first coordinate system is determined based on the rebar binding mechanism of the rebar binding robot. Determine the binding position based on the first coordinate of the rebar intersection.

7. A high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, as described in any one of claims 1-3, characterized in that, Obtain the real-time position of the rebar tying robot's tying mechanism, including: Multiple positioning tags are set up within the working area of ​​the rebar tying robot; The real-time position of the rebar tying robot's tying mechanism is obtained by using multiple positioning tags and readers set on the tying mechanism.

8. A high-precision positioning method for a rebar tying robot for super high-rise buildings based on flexible cable drive, as described in any one of claims 1-3, characterized in that, Based on the location to be tied and the real-time position of the tying mechanism of the rebar tying robot, determine the position compensation parameters, including: The horizontal axis compensation parameters are determined based on the horizontal axis coordinates corresponding to the position to be tied and the horizontal axis coordinates corresponding to the real-time position of the tying mechanism of the rebar tying robot. Based on the longitudinal coordinates of the position to be tied and the longitudinal coordinates of the real-time position of the tying mechanism of the rebar tying robot, the longitudinal compensation parameters are determined, wherein the position compensation parameters include the transverse compensation parameters and the longitudinal compensation parameters.

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