A construction robot system and control method based on laser line dynamic tracking positioning

Abstract

The application discloses a kind of building robot systems and control method based on laser line dynamic tracking positioning.The system includes main control module, laser tracking module, operation control module and sensor driving module;Laser tracking module includes laser line position sensor and filter and tracking algorithm unit;Dark environment box of laser line position sensor is equipped with projection film, camera module is located at the back of projection film and opposite projection film, light inlet area S and axial depth L satisfy 30≤S / L≤80;Its omni-directional rotation adjusting mechanism includes lifting motor and cloud platform rotation motor, lifting motor drives sensor and terminal executor synchronous lifting, cloud platform rotation motor only drives sensor rotation.The method extracts center coordinate by shooting laser line pattern, calculates deflection angle θ And adjust height h, by main control module control motor self-adjusting and complete paving brick.The application can clearly collect laser line under strong light, with high precision, fast response, suitable for high-precision construction operation.

Description

Technical Field

[0001] This invention belongs to the field of construction robot control technology, specifically relating to a construction robot system and control method based on laser line dynamic tracking and positioning. Background Technology

[0002] In the field of building decoration and construction, especially in interior decoration work, processes such as tile laying and wall treatment require extremely high positioning accuracy, such as aligning tile joints and tile surfaces, typically within the millimeter range. The industry commonly uses laser emitters to project horizontal and / or vertical visible laser lines into the construction area as a reference benchmark. This laser line benchmark serves as a reference for both workers and construction robots that automate the work. Construction robots can replace workers in automating tasks such as mortar laying, tile laying, and wall treatment during indoor construction. However, the position of a construction robot frequently changes during construction, and given the complex conditions of construction sites, ensuring the long-term stability, accurate identification, movement positioning, and automated operation of construction robots remains a hot research topic and a key technical challenge to be overcome in this field.

[0003] In existing technologies, there are already many techniques for laser-based construction positioning. For example, Chinese patent document CN120486240A discloses a bridge assembly method, in which a sensor receives positioning laser light and can also perform feedback and calibration by calculating the laser reception angle. However, the laser positioning technology used in this type of construction differs significantly from the laser positioning technology used in the decoration and construction field of this invention. The former is generally used for static positioning and is usually used as an auxiliary method, with relatively low requirements for environmental conditions and accuracy. In contrast, the latter involves dynamic tracking positioning by robots during mobile construction, with a high degree of automation, extremely high construction accuracy requirements, and is easily affected by environmental conditions. How to provide high-precision, stable, and low-cost positioning technology for continuously operating mobile construction robots has always been a technical challenge to be solved in this field.

[0004] Installing sensors on mobile construction robots to receive positioning lasers is a common solution; however, existing solutions still have many problems. Due to the extremely complex lighting environment at construction sites, robots often need to operate near doors, windows, skylights, or unclosed balconies during construction. In sunny weather, the local ambient light intensity in these areas often exceeds 3000 lux. Under direct sunlight, the photosensitive elements of ordinary light intensity recognition sensors are prone to overexposure, causing all pixels in the image to become saturated, and the laser line features to be completely submerged in the background light, leading to recognition failure. This necessitates stopping work and waiting for manual intervention until the lighting conditions improve or the laser line is manually blocked, severely impacting construction continuity, environmental adaptability, and automation levels.

[0005] To address the issue of laser line recognition failure in strong light environments, existing technologies primarily employ two solutions. The first solution involves adding a filter to the front end of the sensor to reduce overexposure risk by filtering out ambient light outside the laser band. However, while filtering out ambient light, the filter also attenuates laser energy, leading to decreased laser line brightness, blurred imaging, and consequently affecting positioning accuracy. The second solution utilizes a carrier frequency recognition sensor with strong resistance to strong light. This sensor locates the laser by identifying a specific frequency modulated in the transmitted signal and can operate normally in environments with light levels exceeding 40,000 lux. However, the measurement accuracy of this type of sensor is lower than the first solution, often failing to meet the requirements of high-precision construction processes such as tile laying. Furthermore, the transmitter and receiver must be strictly paired, requiring the use of specific models from the same brand, limiting equipment selection and increasing procurement costs, thus hindering large-scale application.

[0006] Furthermore, during construction robot operations, uneven ground, robot vibrations, and changes in the actuator's own posture can cause multi-dimensional relative offsets between the sensors and the laser reference line. Existing sensors typically only output simple deviation information, making it difficult to comprehensively reflect the spatial relationship between the robot's end effector and the laser reference line. When the deviation is large, relying solely on the robot's end effector for fine-tuning limits the adjustment range and response speed, often requiring manual intervention for recalibration, which impacts construction efficiency and accuracy. Summary of the Invention

[0007] To address the problems in related technologies, such as the easy failure of laser line recognition in construction robots under strong light environments, the limited dimension of sensor output deviation information, and slow response speed under large deviations, this invention provides a construction robot system and control method based on laser line dynamic tracking and positioning. The system uses a laser line position sensor to capture a projection film pattern, and then uses filtering and tracking algorithms to calculate the adjustment height and deflection angle. The main control module controls the lifting motor to synchronously raise and lower the sensor and the end effector, and the gimbal rotation motor to drive the sensor to rotate and track, achieving high-precision real-time tracking of the laser baseline and enabling construction operations.

[0008] The technical solution of the present invention is implemented as follows: a construction robot system based on laser line dynamic tracking and positioning, including a main control module, and a laser tracking module, a motion control module and a sensor driving module respectively connected to the main control module; The laser tracking module includes a laser line position sensor and a filtering and tracking algorithm unit; the laser line position sensor is fixed on the actuator of the motion control module, and the camera module of the laser line position sensor is connected to the filtering and tracking algorithm unit; the laser line position sensor also has a dark environment chamber, a projection film, and an omnidirectional rotation adjustment mechanism; The dark environment chamber is composed of a front cylinder and a rear cylinder connected to each other. The front cylinder has a light inlet at its front end, the area of ​​which is S. The axial depth of the front cylinder is L. When S is measured in square millimeters and L is measured in millimeters, the values ​​of S and L satisfy: 30 ≤ S / L ≤ 80. The projection film is placed inside the dark environment chamber, and the camera module is located behind the projection film and facing it. The omnidirectional rotation adjustment mechanism includes a lifting component and a self-rotating component. The lifting component is driven by a lifting motor, and the self-rotating component is driven by a gimbal rotation motor. The motion control module includes a motor drive unit and a terminal actuator. The terminal actuator is used for construction processes that require laser line guidance for absolute spatial positioning, including but not limited to grouting, brick laying, and leveling. The laser line position sensor is fixedly connected to the terminal actuator in the height direction. The lifting motor is used to drive the laser line position sensor and the terminal actuator to move up and down synchronously. The gimbal rotation motor drives the laser line position sensor to rotate. The laser tracking module is configured to: capture a laser line pattern using a laser line position sensor, obtain the adjustment height h of the lifting motor and the deflection angle θ of the gimbal rotation motor after filtering and tracking algorithm unit, and output them to the main control module; The main control module controls the lifting motor according to the adjusted height h, and controls the gimbal rotation motor according to the deflection angle.

[0009] By employing a front and rear cylinder structure within a dark environment chamber and limiting the ratio of the light inlet area S to the axial depth L, while placing the camera module behind and directly facing the projection film, the system effectively attenuates oblique ambient light and suppresses overexposure under strong light, ensuring clear acquisition of the laser line pattern. A filtering and tracking algorithm unit calculates the adjustment height of the lifting motor and the deflection angle of the gimbal rotation motor from the image, achieving two-dimensional deviation compensation in both horizontal and vertical directions. The laser line position sensor and the end effector are fixedly connected in the vertical direction, and the lifting motor synchronously drives both to rise and fall, ensuring that the paving height matches the sensor's detection height. The gimbal rotation motor only rotates the sensor, allowing it to independently track the laser line without affecting the actuator's posture, thus decoupling the motion. The main control module controls the lifting motor and gimbal rotation motor separately based on the received adjustment height and deflection angle, forming a closed-loop control system. This significantly improves the tracking accuracy of the construction robot in strong light environments and the automation level of grouting, paving, and leveling operations.

[0010] As a further improvement to the above scheme, the deflection angle θ of the gimbal rotation motor is θ = arctan(b / L), where b is the width of the single-sided shadow formed by the front edge of the front cylinder in the laser line pattern, and L is the axial depth of the front cylinder; the adjustment height h of the lifting motor is the height offset between the center of the laser line pattern and the calibrated target position.

[0011] The deflection angle and adjustment height are calculated directly using geometric formulas, which reduces the computational load, increases the response time, and improves the real-time performance of the system.

[0012] As a further improvement to the above solution, the self-rotating assembly includes a rotating flange, a primary rotating seat, a transition bushing, and a secondary rotating seat; the primary rotating seat is fixed to the upper surface of the rotating flange, the transition bushing is fitted onto the outer ring of the primary rotating seat, and the inner ring of the secondary rotating seat is fitted onto the outer ring of the transition bushing.

[0013] The multi-stage nesting structure improves the rotational stability and positioning accuracy of the self-rotating component, and enhances the stability of the sensor tracking the laser line.

[0014] As a further improvement to the above solution, the laser line position sensor also includes a limiting component, which is used to limit the rotation angle range of the gimbal rotation motor to ±360°.

[0015] Limiting the rotation angle range by using a limiting component prevents mechanical damage and improves the safety and reliability of the system.

[0016] As a further improvement to the above solution, the sensor driving module is also connected to a lidar, an IMU, and an IO module.

[0017] By connecting LiDAR, IMU, and IO modules, the system is provided with environmental perception, attitude measurement, and expansion interfaces, enhancing the robot's localization and environmental adaptability.

[0018] A control method for a construction robot based on laser line dynamic tracking and positioning, applied to the construction robot system described above, includes the following steps: S1. The laser line pattern on the projection film is captured in real time by the camera module of the laser line position sensor, and the acquired image data is transmitted to the filtering and tracking algorithm unit. S2. The filtering and tracking algorithm unit processes the image data, extracts the center coordinates of the laser line, and calculates the deflection angle θ of the gimbal rotation motor and the adjustment height h of the lifting motor. S3. Output the adjustment height h and deflection angle θ to the main control module; S4. The main control module controls the gimbal rotation motor and the lifting motor to perform self-adjustment based on the deflection angle θ and the adjustment height h; S5. The main control module controls the terminal actuator to perform construction operations that require laser line guidance. Based on the positioning data provided by the lidar and IMU, the terminal actuator is moved to the target operation coordinates and the corresponding construction actions are performed. The construction operations include grouting, bricklaying, or leveling.

[0019] Through a complete closed-loop process of image acquisition, deviation calculation, master control decision-making, motor self-adjustment and paving operation, an integrated process from laser line recognition to position correction and paving execution is realized, ensuring the real-time performance and control accuracy of the system under dynamic tracking.

[0020] As a further improvement to the above scheme, the self-adjustment includes: When a single-sided shadow appears on the left side of the laser line pattern and the height h=0 is adjusted, the main control module drives the gimbal rotation motor to rotate the deflection angle θ counterclockwise, thereby causing the laser line position sensor to rotate. When a single-sided shadow appears on the right end of the laser line pattern and the height h=0 is adjusted, the main control module drives the gimbal rotation motor to rotate the deflection angle θ clockwise, thereby causing the laser line position sensor to rotate. When the laser line pattern does not show a single-sided shadow but the adjustment height h ≠ 0, if the adjustment height h > 0, the main control module drives the lifting motor to rise to the adjustment height h, causing the laser line position sensor and the terminal actuator to rise synchronously; if the adjustment height h < 0, the lifting motor drives the lifting motor to descend to the absolute value of the adjustment height |h|, causing the laser line position sensor and the terminal actuator to descend synchronously. When the laser line pattern simultaneously shows a shadow on one side and the adjustment height h≠0, the main control module first drives the gimbal rotation motor to rotate the deflection angle θ, thereby driving the laser line position sensor to rotate, and then drives the lifting motor to move, thereby driving the laser line position sensor and the terminal actuator to lift and lower synchronously. When the laser line pattern does not show a shadow on one side and the height adjustment h=0, the main control module does not drive the gimbal rotation motor and the lifting motor.

[0021] Specific motion rules for the gimbal rotary motor and lifting motor are given for horizontal deviation, height deviation and combined deviation respectively. The order of horizontal compensation first and height compensation is adopted to ensure decoupling of the two degrees of freedom motion, efficient adjustment, avoid interference and oscillation, and significantly improve the system's tracking stability and adjustment accuracy of the laser line.

[0022] As a further improvement to the above solution, when the construction operation is paving bricks: a movement path is planned based on the positioning data provided by the lidar and IMU, and the terminal actuator is moved to the target paving coordinates; a brick is grabbed and adsorbed by a vacuum suction cup; the brick is pressed down onto the working surface so that the bottom surface of the brick is in contact; the vibrator is started to compact the brick; the vacuum suction cup is released and the terminal actuator is reset. When the construction operation is grouting: the terminal actuator is moved to the target coordinates according to the positioning data provided by the lidar and IMU; the lifting motor is controlled according to the height adjustment h to make the terminal actuator reach the specified height; at the same time, the gimbal rotation motor assists the target plate to face the laser emitter; When the construction operation is leveling: the terminal actuator is moved to the target coordinates according to the positioning data provided by the lidar and IMU; the lifting motor is controlled according to the height adjustment h to make the terminal actuator reach the specified height; at the same time, the gimbal rotation motor assists the target plate to face the laser emitter.

[0023] Through a complete paving process including path planning, vacuum adsorption, pressing and bonding, vibration compaction, and reset and release, the automated and precise paving of bricks is achieved, ensuring the tight fit and compaction quality between the bricks and the working surface, and improving paving efficiency and consistency.

[0024] As a further improvement to the above scheme, the extraction of the laser line center coordinates specifically involves: The laser line pattern is subjected to dimensionality reduction and downsampling. The color image is converted into a single-channel grayscale image to achieve the first dimensionality reduction. Downsampling is achieved by sampling at intervals along the laser line direction. The one-dimensional coordinate point set of the edge straight line segment is extracted to achieve the second dimensionality reduction. Then, cluster analysis is performed on the point set to determine the center coordinates of the laser line. The cluster analysis uses an adaptive cluster radius, and the formula for calculating the cluster radius is as follows: ; in, Let the initial radius be , For reference length, It is the mean of the angle between the straight line segment and the horizontal line.

[0025] By significantly reducing image computation through two rounds of dimensionality reduction and downsampling, and combined with clustering analysis based on adaptive cluster radius, the center coordinates of the laser line can be extracted quickly and accurately, significantly improving recognition efficiency and robustness.

[0026] As a further improvement to the above scheme, the filtering and tracking algorithm unit uses an adaptive super-green index algorithm to extract laser line features. Specifically, it calculates the average grayscale image and its brightness standard deviation σ. When 2≤σ<15, the enhanced super-green index is used, and when σ≥15, the standard super-green index is used.

[0027] The super-green index model is adaptively selected based on the standard deviation of image brightness, which can highlight the laser line features under different lighting conditions and improve the robustness of extraction and the accuracy of recognition.

[0028] Compared with traditional processing methods, the present invention has the following advantages: (1) By using a dark environment box structure to mechanically attenuate ambient light, the laser line pattern can still be clearly obtained under strong light conditions with an ambient light intensity of more than 3000 lux, which fundamentally avoids the problem of recognition failure caused by overexposure of the photosensitive element.

[0029] (2) The laser tracking module has a built-in filtering and tracking algorithm unit, which can calculate the adjustment height of the lifting motor and the deflection angle of the gimbal rotation motor. The main control module controls the lifting motor to drive the sensor and the terminal actuator to lift and lower simultaneously, and the gimbal rotation motor to drive the sensor to rotate independently, based on these two deviations. This achieves two-dimensional decoupling compensation in the horizontal angle and height direction, with fast tracking response and no impact on the posture of the construction operation.

[0030] (3) The sensor and the terminal actuator are fixed in the height direction. The lifting motor drives the two to lift synchronously to ensure that the brick laying height is consistent with the sensor detection height. The gimbal rotation motor only drives the sensor to rotate, so that the sensor can independently track the laser line, avoiding the two-stage delay in the traditional solution where the sensor is adjusted and then the actuator is notified to follow.

[0031] (4) By performing two dimensionality reductions, intermittent downsampling, and adaptive cluster radius clustering, the computational load can be significantly reduced; the adaptive super green index algorithm can automatically select the model based on the brightness standard deviation, thereby highlighting the laser line features under different lighting conditions and significantly improving the robustness and real-time performance of the recognition. Attached Figure Description

[0032] Figure 1 This is a block diagram of a construction robot system based on laser line dynamic tracking and positioning according to the present invention; Figure 2 This is a schematic cross-sectional view of the laser line position sensor of the present invention; Figure 3 This is a schematic diagram of the overall structure of the laser line position sensor of the present invention; Figure 4 This is a flowchart illustrating the steps of a construction robot control method based on laser line dynamic tracking and positioning according to the present invention. Figure 5 This is a schematic diagram showing the horizontal angle deviation between the laser line position sensor and the laser line of the present invention; Figure 6 This is a schematic diagram showing the height direction deviation between the laser line position sensor and the laser line according to the present invention; Figure 7 This is a schematic diagram of the horizontal laser line recognition results of the present invention; Figure 8 This is a diagram showing the static recognition test results of the present invention.

[0033] Figure label: 1. Lifting motor; 2. Connecting seat; 3. Lifting plate; 4. Base plate; 5. Self-rotating assembly; 6. Secondary rotating seat; 7. Transition bushing; 8. Primary rotating seat; 9. Camera module; 10. Rear cover; 11. Rear cylinder; 12. Projection film; 13. Front cylinder; 14. Limit pin; 15. Limit block; 16. Fixing frame. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0035] Example like Figure 1 As shown, this embodiment provides a construction robot system based on laser line dynamic tracking and positioning, including a main control module, and a laser tracking module, a motion control module, and a sensor drive module connected to the main control module. The laser tracking module includes a laser line position sensor and a filtering and tracking algorithm unit; the motion control module includes a motor drive unit and an end effector. The end effector is used for construction processes requiring laser line guidance for absolute spatial positioning, including but not limited to grouting, bricklaying, and leveling; the sensor drive module is also connected to a lidar, an IMU, and an I / O module. The lidar is used to acquire 3D point cloud data of the working environment, construct a local map, and assist in obstacle avoidance and path planning; the IMU is used to measure the robot's attitude angles (roll, pitch, yaw) and acceleration in real time, providing high-frequency attitude information to assist in dynamic compensation by the laser line position sensor; the I / O module is used to expand external sensors or actuators (such as limit switches, emergency stop buttons, etc.) to enhance the system's scalability.

[0036] like Figure 2 and Figure 3 As shown, the laser line position sensor is fixed on the terminal actuator of the motion control module, and its camera module is connected to the filtering and tracking algorithm unit via a high-speed cable. The laser line position sensor includes a base plate 4, an omnidirectional rotation adjustment mechanism mounted on the base plate 4, a camera module 9 and a projection film 12 mounted on the omnidirectional rotation adjustment mechanism, and a cylindrical housing. The cylindrical housing is composed of a front cylinder 13 and a rear cylinder 11 connected to each other. The internal spaces of the front cylinder 13 and the rear cylinder 11 together form a dark environment box, and the projection film 12 is located inside the dark environment box. The front end of the front cylinder 13 is provided with a light inlet for receiving the laser line emitted by an external laser emitter. The area of ​​the light inlet is S (unit: mm²), and the axial depth of the front cylinder 13 is L (unit: mm), and the values ​​of S and L satisfy: 30 ≤ S / L ≤ 80.

[0037] The measurement range of construction robots is typically 30mm-80mm. To achieve optimal imaging quality and anti-interference within this range, the lateral dimension of the light inlet must be matched to the measurement range. Let the light inlet be a square with a side length of a (mm), then the area of ​​the light inlet is S = a². When the side length a of the light inlet is between 30mm and 80mm, and the axial depth L of the front cylinder is approximately equal to a, the value of S / L ranges from 30 to 80. When S / L is below 30, the light inlet size is too small, and some light rays may be blocked by the edge of the front cylinder when the laser line deviates within the measurement range, resulting in a decrease in the brightness of the light spot on the projection film 12, reduced imaging clarity of the camera module 9, and a shortened recognition distance. When S / L is above 80, the light inlet size is too large or the front cylinder is too short, and oblique ambient light can reach the projection film 12 without sufficient attenuation, causing the camera module 9 to be prone to overexposure in strong light environments. Only when the S / L ratio is strictly controlled within the range of 30 to 80 can the comprehensive effects of covering the entire measurement range, ensuring laser energy, and fully attenuating ambient light be achieved simultaneously.

[0038] After being emitted by the transmitter, the laser beam propagates almost in a straight line along the optical axis. Entering the dark environment chamber through the light inlet, it is directly projected onto the surface of the projection film 12. Its propagation path almost never touches the inner walls of the front cylinder 13 and the rear cylinder 11, resulting in minimal energy loss. Ambient light, however, comes from various directions. When obliquely incident ambient light enters the dark environment chamber through the light inlet, its propagation direction forms an angle with the optical axis, and most of it directly illuminates the inner wall of the front cylinder 13. Since the inner wall of the front cylinder 13 is a non-optically reflective surface, the ambient light undergoes multiple diffuse reflections and absorptions on its surface. After several reflections, by the time it reaches the surface of the projection film 12, it has attenuated to a negligible level. This purely mechanical optical path confinement method achieves angular selective attenuation of the incident light, suppressing ambient light while maintaining almost no loss of laser energy.

[0039] The front cylinder 13 and the rear cylinder 11 are connected by a plug-in method: the front cylinder 13 has a small end boss, and the rear cylinder 11 has a cavity and a stepped surface at the bottom of the cavity. The small end boss of the front cylinder 13 is inserted into the cavity of the rear cylinder 11 and presses the projection film 12 tightly onto the stepped surface, thereby achieving precise positioning and reliable fixation of the projection film 12, avoiding displacement and loosening under vibration conditions, and ensuring optical path stability and imaging consistency.

[0040] The camera module 9 is integrated with the back cover 10. The back cover 10 is mounted on the rear end of the rear cylinder 11 via a fixing bracket 16, positioning the camera module 9 behind and directly facing the projection film 12. This allows the camera module to acquire the laser line pattern projected onto the projection film 12 and transmit the image data to the filtering and tracking algorithm unit via a high-speed cable. The camera module 9 can be a CMOS or CCD image sensor.

[0041] The omnidirectional rotation adjustment mechanism includes a lifting assembly and a self-rotating assembly 5. The lifting assembly is driven by a lifting motor 1, and the self-rotating assembly is driven by a gimbal rotation motor. Specifically, the self-rotating assembly 5 includes a rotating flange, a primary rotating seat 8, a transition bushing 7, and a secondary rotating seat 6; the primary rotating seat 8 is fixed to the upper surface of the rotating flange, the transition bushing 7 fits onto the outer ring of the primary rotating seat 8, and the inner ring of the secondary rotating seat 6 fits onto the outer ring of the transition bushing 7. The lifting assembly includes a lifting motor 1, a lifting plate 3, and a connecting seat 2. The threaded shaft of the lifting motor 1 engages with the internal threaded rod of the lifting plate 3 to drive the laser line position sensor and the terminal actuator to move up and down synchronously.

[0042] The laser line position sensor and the end effector are fixedly connected in the height direction, and to reduce transmission errors, the vertical distance between them does not exceed 20cm. The lifting motor is used to drive the laser line position sensor and the end effector to move up and down synchronously; the gimbal rotation motor is used to drive the laser line position sensor to rotate.

[0043] The base plate 4 is also provided with a limiting component, which includes a limiting pin 14 fixed on the base plate 4 and a limiting block 15 fixed on the laser line position sensor, used to limit the rotation angle range of the gimbal rotation motor to ±360°.

[0044] like Figure 4 As shown, this embodiment provides a control method for a construction robot based on laser line dynamic tracking and positioning, applied to the above system, including the following steps: S1. Image Acquisition: The laser line pattern on the projection film 12 is captured in real time by the camera module 9 of the laser line position sensor, and the acquired image data is transmitted to the filtering and tracking algorithm unit via a high-speed cable.

[0045] like Figure 5 and Figure 6 The figures shown are schematic diagrams of horizontal angular deviation and vertical directional deviation, respectively.

[0046] S2. Visual Processing and Deviation Calculation: The filtering and tracking algorithm unit processes the image data, extracts the center coordinates of the laser line, and calculates the deflection angle θ of the gimbal's rotating motor and the adjustment height h of the lifting motor. This step employs a high-real-time visual algorithm, reducing the computational load per frame through dimensionality reduction and downsampling, and improving recognition robustness through an adaptive parameter tuning algorithm. The specific process for extracting the center coordinates of the laser line is as follows: First, acquire a color image, apply different weights to the brightness of the three channels, and calculate the average brightness value of each pixel in the grayscale image: ; in, It is the brightness of the i-th element in the average grayscale image. , It is the BGR component after Gamma correction; Then, calculate the standard deviation of the brightness of each pixel in the average grayscale image. : ; in, Let be the brightness value of the i-th pixel in the average grayscale image. This represents the average brightness of each pixel in the average grayscale image. This represents the total number of pixels.

[0047] Since laser lines are typically green, to highlight the characteristics of the laser lines and suppress background interference, the filtering and tracking algorithm unit uses the standard deviation of the average grayscale image as the branch condition for extracting the super-green index, thus obtaining the grayscale image for analysis.

[0048] like If the image contrast is too low and there is no green laser line feature, no valid data will be returned directly. like Then, an enhanced super green index is used to stretch the red and green channels of the original three-channel color image to different color levels, and then saturate-cropping the red and green channels is performed: ; in, To analyze the brightness value of the pixel in the i-th column and j-th row of the grayscale image; This represents the brightness value of the pixel in the i-th column and j-th row of the green channel of the color image. This represents the brightness value of the pixel in the i-th column and j-th row of the red channel of the color image. and These are the maximum and minimum brightness values ​​of the green channel in the color image, respectively. and These are the maximum and minimum brightness values ​​of the red channel in the color image, respectively. like Then, the standard super-green index is used to directly perform saturation clipping of the red-green channels: ; The row and column containing the brightest point in the grayscale image used for calculation and analysis are denoted as the coordinates of the reference point. .

[0049] Because the laser line brightness is uneven, the brightest point deviates from the center of the laser line. Therefore, when there is no laser line and the background brightness is uneven, a standard deviation in the average grayscale image brightness will appear. In such cases, the resulting grayscale image used for analysis may lead to misidentification. Therefore, in this embodiment, the grayscale image was not used. Used as the coordinates of the laser line.

[0050] This embodiment uses a horizontal laser line as an example to explain in detail the self-adjustment method of the main control module driving the gimbal's rotary and lifting motors based on the deflection angle θ and adjustment height h. The following visual processing algorithm is applicable to horizontal, vertical, and cross laser lines.

[0051] Then, the filtering and tracking algorithm unit determines the strip sampling direction based on the preset laser line identification direction. In this embodiment, the preset direction includes three modes: horizontal laser line, vertical laser line, or cross laser line.

[0052] First, the adaptive strip width is calculated. In this embodiment, it is taken as 1 / 30 of the shorter side of the image frame, and at least 10 pixels. ; in, For the strip width, and These represent the image width and image height of the grayscale image used for analysis, respectively.

[0053] Then, starting from the center of the image, sampling is performed at intervals along the width of the image to both sides, resulting in a compact sampled image with the same height but halved width. This interval sampling method reduces the number of pixels involved in the calculation by about 50%, effectively reducing the computational load of image processing and improving real-time performance while preserving the key positional information of the laser lines.

[0054] Next, the filtering and tracking algorithm unit performs adaptive threshold binarization processing on the compact sampling image, dynamically adjusts the segmentation threshold according to local image features, and obtains a binarized image with clear laser line edges, so that the laser line edges can be clearly separated from the background.

[0055] Subsequently, edge coordinate extraction and cluster analysis are performed. The filtering and tracking algorithm unit extracts the straight line segment features of the laser line edge from the binarized image and extracts the corresponding one-dimensional coordinate point set according to the recognition direction. Since the laser line may have uneven brightness, background noise, and other interference, the filtering and tracking algorithm unit adaptively calculates the cluster radius based on the mean α of the angle between the straight line segment and the horizontal line. When identifying the horizontal portion of a horizontal laser line or a cross laser line. ; When identifying the vertical portion of a vertical laser line or a cross laser line, ; in, The cluster radius; The initial radius; For reference length, in this embodiment, half the width of the image is used when identifying horizontal laser lines, and half the height of the image is used when identifying vertical laser lines.

[0056] After clustering is completed, the clustering results will be subject to three levels of verification to ensure the reliability of the identification results: First-level verification: Calculate the total length of the identified line segments in the binarized image and determine if it is not less than half the height or width of the image. If the total length of the line segments is too small, it indicates that there may be no valid laser line features in the image, and the current recognition result is deemed invalid, returning "no valid data".

[0057] The second layer of verification involves counting the number of clusters obtained from clustering. Based on the actual shape of the laser lines, the correct number of clusters should be between 1 and 4 (e.g., a single horizontal line, a single vertical line, or a cross). If the number of clusters exceeds this range, it indicates excessive interference, and the recognition result is deemed invalid, returning "no valid data."

[0058] The third layer of verification calculates the distance between the centers of the two furthest clusters. Since the maximum width of the laser line projected onto the target is no more than 8mm, if the distance between the cluster centers is greater than 8mm (converted to pixel distance based on the pixel precision of the camera image), it indicates that these clusters may come from different light sources or noise, and the recognition result is deemed invalid, returning no valid data.

[0059] After passing the above three-layer verification, if the clustering results meet the requirements, the center coordinates of the laser line are determined based on the number of clusters as the final output.

[0060] like Figure 7 As shown, taking the identification of a horizontal laser line as an example, the row coordinates of the edge straight line segment are taken to form a one-dimensional vector. Two clusters are obtained through cluster analysis. After verification and confirmation, the center of the distance between the centers of the two clusters is taken as the final center coordinates of the laser line.

[0061] In this embodiment, the deflection angle θ and adjustment height h are calculated based on the extracted center coordinates. The width b of the single-sided shadow formed by the front edge of the front cylinder in the laser line pattern is identified, and combined with the axial depth L of the front cylinder, the deflection angle θ = arctan(b / L) of the gimbal rotation motor is calculated. The height offset between the center of the laser line pattern and the calibrated target position is identified, which is the adjustment height h of the lifting motor. Kalman filtering is used to suppress instantaneous changes in the shadow width b.

[0062] S3, Deviation Output: Output the adjustment height h and deflection angle θ to the main control module.

[0063] S4. Self-adjustment: The main control module controls the gimbal rotation motor and the lifting motor to perform self-adjustment based on the deflection angle θ and the adjustment height h. In a horizontal laser line tracking scenario, the specific rules for self-adjustment are as follows: When a single-sided shadow appears on the left side of the laser line pattern and the height h=0 is adjusted, the main control module drives the gimbal rotation motor to rotate the deflection angle θ counterclockwise, thereby causing the laser line position sensor to rotate. When a single-sided shadow appears on the right end of the laser line pattern and the height h=0 is adjusted, the main control module drives the gimbal rotation motor to rotate the deflection angle θ clockwise, thereby causing the laser line position sensor to rotate. When the laser line pattern does not show a single-sided shadow but the adjustment height h ≠ 0, if the adjustment height h > 0, the main control module drives the lifting motor to rise to the adjustment height h, causing the laser line position sensor and the terminal actuator to rise synchronously; if the adjustment height h < 0, the lifting motor drives the lifting motor to descend to the absolute value of the adjustment height |h|, causing the laser line position sensor and the terminal actuator to descend synchronously. When the laser line pattern simultaneously shows a shadow on one side and the adjustment height h≠0, the main control module first drives the gimbal rotation motor to rotate the deflection angle θ, thereby driving the laser line position sensor to rotate, and then drives the lifting motor to move, thereby driving the laser line position sensor and the terminal actuator to lift and lower synchronously. When the laser line pattern does not show a shadow on one side and the height adjustment h=0, the main control module does not drive the gimbal rotation motor and the lifting motor.

[0064] In other embodiments, for tracking vertical laser lines, the sensor cylinder can first be rotated to be perpendicular to the laser emission direction using a gimbal rotation motor, and then the gimbal rotation motor can be locked. At this point, a traverse motor can be used to drive the sensor to move laterally to eliminate lateral offset, without needing to adjust the lifting motor. For cross laser lines, similarly, the gimbal rotation motor is first adjusted to make the target plane perpendicular to the laser emission direction and then locked. Afterward, a lifting motor and a traverse motor can be used to dynamically adjust the tracking in real time according to the laser line signal: the lifting motor compensates for height deviation, and the traverse motor compensates for lateral deviation.

[0065] S5. Construction Operation: The main control module controls the terminal actuator to perform construction operations that require laser line guidance.

[0066] When the construction operation is paving bricks: The main control module constructs a local map based on the real-time 3D point cloud data of the environment collected by the LiDAR, and combines it with the robot's real-time attitude angles (roll, pitch, yaw) and acceleration information provided by the IMU to perform data fusion and plan a collision-free movement path for the end effector from its current position to the target paving coordinates; at the same time, the main control module reads the limit switch status through the IO module to ensure that the movement does not exceed the safety boundary; then, it controls the motor drive unit to move the end effector to the target paving coordinates. Next, the main control module controls the end effector to grab the bricks using a vacuum suction cup, and the IO module detects whether the vacuum pressure of the suction cup has reached the set threshold; then, it controls the end effector to press the bricks down onto the working surface, so that the bottom surface of the bricks is in contact with the working surface. During this process, the IMU provides real-time feedback on the attitude of the end effector, and the main control module corrects the pressing angle based on the IMU data; then, it starts the vibrator to vibrate and compact the bricks, and the vibration frequency and duration are dynamically adjusted according to the pressure sensor signal connected to the IO module; finally, it releases the vacuum suction cup, and after confirming that the release is in place, it controls the end effector to reset, ready for the next paving operation.

[0067] When the construction operation is grouting: the main control module moves the terminal actuator to the target coordinates according to the positioning data provided by the lidar and IMU; according to the height adjustment h, the lifting motor is controlled to make the terminal actuator reach the specified height, and at the same time the gimbal rotation motor assists the target plate to face the laser emitter.

[0068] When the construction operation is leveling: the main control module moves the terminal actuator to the target coordinates according to the positioning data provided by the lidar and IMU; according to the height adjustment h, the lifting motor is controlled to make the terminal actuator reach the specified height, and at the same time the gimbal rotation motor assists the target plate to face the laser emitter.

[0069] Then return to step S1 to form a closed-loop control of real-time dynamic tracking and construction operations.

[0070] To verify the overall technical effectiveness of the device and control method in this embodiment, a static recognition test was conducted in an indoor environment. The test conditions were: ambient light intensity of 3165 lux, S / L = 80, and the laser emitter and sensor were 7m apart horizontally and stationary. The filtering and tracking algorithm unit continuously collected the position coordinates of the laser line on the projection film 12 according to the above steps, with a sampling time of 1 minute and a sampling point count of 3000+.

[0071] like Figure 8As shown, the test results indicate that the maximum recognition result is 29.05mm, the minimum is 28.7mm, and the average is 28.86mm, with a data fluctuation range of -0.16mm to +0.19mm. This means that the recognition accuracy can reach ±0.2mm at a distance of 7m. Within a working distance of 15m, the recognition accuracy of this embodiment is better than ±0.5mm, significantly higher than existing carrier recognition schemes (±1mm / 10m).

[0072] In other embodiments, multi-sensor linkage can be implemented to track laser lines in different directions (e.g., horizontal and vertical lines). Specifically, two laser line position sensors can be used to track two laser emitters positioned at the doorway and window, forming a triangular layout with the construction robot. This upgrades single-line tracking to spatial pose positioning, meeting the omnidirectional positioning requirements in complex working environments. Furthermore, the laser line position sensors can move in tandem with the construction robot system: when the robot is laying bricks on non-horizontal surfaces such as stairs or slopes, the sensors adaptively adjust based on changes in the robot's overall posture (e.g., tilt angle, pitch angle) (e.g., height tracking via a lifting motor, angle compensation via a gimbal rotation motor), ensuring the laser line is always projected onto the effective area of ​​the projection film. This allows for smooth and high-precision brick-laying operations even on non-horizontal surfaces. In practical applications, laser emitters with black light-shielding plates on the back can be used to further suppress ambient light interference; alternatively, the laser emitter can be mounted on a movable follow-up platform, maintaining a relatively fixed distance and angle with the construction robot, thus maintaining a stable laser reference during long-distance or complex path operations.

[0073] Based on the disclosure and teachings of the foregoing specification, those skilled in the art can make changes and modifications to the above embodiments. Therefore, the present invention is not limited to the specific embodiments disclosed and described above, and some modifications and changes to the invention should also fall within the protection scope of the claims of the present invention. Furthermore, although some specific terms are used in this specification, these terms are only for convenience of explanation and do not constitute any limitation on the present invention.

Claims

1. A construction robot system based on laser line dynamic tracking and positioning, comprising a main control module, and a laser tracking module, a motion control module, and a sensor driving module respectively connected to the main control module; characterized in that, The laser tracking module includes a laser line position sensor and a filtering and tracking algorithm unit; the laser line position sensor is fixed on the actuator of the motion control module, and the camera module of the laser line position sensor is connected to the filtering and tracking algorithm unit; the laser line position sensor also has a dark environment chamber, a projection film, and an omnidirectional rotation adjustment mechanism; The dark environment chamber is composed of a front cylinder and a rear cylinder connected to each other. The front cylinder has a light inlet at its front end, the area of ​​which is S. The axial depth of the front cylinder is L. When S is measured in square millimeters and L is measured in millimeters, the values ​​of S and L satisfy: 30 ≤ S / L ≤ 80. The projection film is placed inside the dark environment chamber, and the camera module is located behind the projection film and facing it. The omnidirectional rotation adjustment mechanism includes a lifting component and a self-rotating component. The lifting component is driven by a lifting motor, and the self-rotating component is driven by a gimbal rotation motor. The motion control module includes a motor drive unit and a terminal actuator. The terminal actuator is used for construction processes that require laser line guidance for absolute spatial positioning, including grouting, brick laying, and leveling. The laser line position sensor is fixedly connected to the terminal actuator in the height direction. The lifting motor is used to drive the laser line position sensor and the terminal actuator to move up and down synchronously. The gimbal rotation motor drives the laser line position sensor to rotate. The laser tracking module is configured to: capture a laser line pattern using a laser line position sensor, obtain the adjustment height h of the lifting motor and the deflection angle θ of the gimbal rotation motor after filtering and tracking algorithm unit, and output them to the main control module; The deflection angle θ = arctan(b / L), where b is the width of the single-sided shadow formed by the front edge of the front cylinder in the laser line pattern, and L is the axial depth of the front cylinder; the adjustment height h of the lifting motor is the height offset between the center of the laser line pattern and the calibrated target position. The main control module controls the lifting motor according to the adjusted height h, and controls the gimbal rotation motor according to the deflection angle.

2. The construction robot system based on laser line dynamic tracking and positioning according to claim 1, characterized in that, The self-rotating assembly includes a rotating flange, a primary rotating seat, a transition bushing, and a secondary rotating seat; the primary rotating seat is fixed to the upper surface of the rotating flange, the transition bushing is fitted onto the outer ring of the primary rotating seat, and the inner ring of the secondary rotating seat is fitted onto the outer ring of the transition bushing.

3. The construction robot system based on laser line dynamic tracking and positioning according to claim 1, characterized in that, The laser line position sensor also includes a limiting component, which is used to limit the rotation angle range of the gimbal rotation motor to ±360°.

4. A construction robot system based on laser line dynamic tracking and positioning according to claim 1, characterized in that, The sensor driver module is also connected to a lidar, an IMU, and an I / O module.

5. A control method for a construction robot based on laser line dynamic tracking and positioning, applied to the construction robot system as described in any one of claims 1-4, characterized in that, Includes the following steps: S1. The laser line pattern on the projection film is captured in real time by the camera module of the laser line position sensor, and the acquired image data is transmitted to the filtering and tracking algorithm unit. S2. The filtering and tracking algorithm unit processes the image data, extracts the center coordinates of the laser line, and calculates the deflection angle θ of the gimbal rotating motor and the adjustment height h of the lifting motor. S3. Output the adjustment height h and deflection angle θ to the main control module; S4. The main control module controls the gimbal rotation motor and the lifting motor to perform self-adjustment based on the deflection angle θ and the adjustment height h; S5. The main control module controls the terminal actuator to perform construction operations that require laser line guidance. Based on the positioning data provided by the lidar and IMU, the terminal actuator is moved to the target operation coordinates and the corresponding construction actions are performed. The construction operations include grouting, bricklaying, or leveling.

6. The construction robot control method based on laser line dynamic tracking and positioning according to claim 5, characterized in that, The self-regulation includes: When a single-sided shadow appears on the left side of the laser line pattern and the height h=0 is adjusted, the main control module drives the gimbal rotation motor to rotate the deflection angle θ counterclockwise, thereby causing the laser line position sensor to rotate. When a single-sided shadow appears on the right end of the laser line pattern and the height h=0 is adjusted, the main control module drives the gimbal rotation motor to rotate the deflection angle θ clockwise, thereby causing the laser line position sensor to rotate. When the laser line pattern does not show a single-sided shadow but the adjustment height h ≠ 0, if the adjustment height h > 0, the main control module drives the lifting motor to rise to the adjustment height h, causing the laser line position sensor and the terminal actuator to rise synchronously; if the adjustment height h < 0, the lifting motor drives the lifting motor to descend to the absolute value of the adjustment height |h|, causing the laser line position sensor and the terminal actuator to descend synchronously. When the laser line pattern simultaneously shows a shadow on one side and the adjustment height h≠0, the main control module first drives the gimbal rotation motor to rotate the deflection angle θ, thereby driving the laser line position sensor to rotate, and then drives the lifting motor to move, thereby driving the laser line position sensor and the terminal actuator to lift and lower synchronously. When the laser line pattern does not show a shadow on one side and the height adjustment h=0, the main control module does not drive the gimbal rotation motor and the lifting motor.

7. The construction robot control method based on laser line dynamic tracking and positioning according to claim 5, characterized in that, When the construction operation is paving bricks: a movement path is planned based on the positioning data provided by the lidar and IMU, and the terminal actuator is moved to the target paving coordinates; a brick is picked up and adsorbed by a vacuum suction cup; the brick is pressed down onto the working surface so that the bottom surface of the brick is in contact with the surface; the vibrator is started to compact the brick; the vacuum suction cup is released and the terminal actuator is reset. When the construction operation is grouting: the terminal actuator is moved to the target coordinates according to the positioning data provided by the lidar and IMU; the lifting motor is controlled according to the height adjustment h to make the terminal actuator reach the specified height; at the same time, the gimbal rotation motor assists the target plate to face the laser emitter; When the construction operation is leveling: the terminal actuator is moved to the target coordinates according to the positioning data provided by the lidar and IMU; the lifting motor is controlled according to the height adjustment h to make the terminal actuator reach the specified height; at the same time, the gimbal rotation motor assists the target plate to face the laser emitter.

8. A control method for a construction robot based on laser line dynamic tracking and positioning according to claim 5, characterized in that, The specific details of extracting the center coordinates of the laser line are: The laser line pattern is subjected to dimensionality reduction and downsampling. The color image is converted into a single-channel grayscale image to achieve the first dimensionality reduction. Downsampling is achieved by sampling at intervals along the laser line direction. The one-dimensional coordinate point set of the edge straight line segment is extracted to achieve the second dimensionality reduction. Then, cluster analysis is performed on the point set to determine the center coordinates of the laser line. The cluster analysis uses an adaptive cluster radius, and the formula for calculating the cluster radius is as follows: ； in, Let the initial radius be , For reference length, It is the mean of the angle between the straight line segment and the horizontal line.

9. A construction robot control method based on laser line dynamic tracking and positioning according to claim 5, characterized in that, The filtering and tracking algorithm unit uses an adaptive super-green index algorithm to extract laser line features. Specifically, it calculates the average grayscale value of the image and its brightness standard deviation σ. When 2≤σ<15, the enhanced super-green index is used, and when σ≥15, the standard super-green index is used.

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