Coordinated steering control method and system for bridge deck construction equipment

Abstract

This invention discloses a collaborative steering control method and system for bridge deck construction equipment, relating to the field of bridge construction. The method includes: collecting and analyzing bridge deck construction status data through a bridge deck sensing network to obtain bridge deck construction reference path coordinates; performing multi-axis trajectory tracking calculations on the bridge deck construction equipment to establish an alignment time sequence; using the sequence as a time sequence control anchor point, analyzing the time sequence steering control parameters of the equipment's multiple axes to obtain the steering control parameters of each axis node; and performing target collaboration verification to determine the collaborative steering control strategy for multi-axis collaborative steering control of the bridge deck construction equipment. This application solves the technical problems of high cost and poor equipment coordination in existing collaborative steering control modes for bridge deck construction equipment, which can easily lead to operational conflicts. It achieves the technical effects of reducing the hardware cost of construction equipment, improving the coordination of multi-axis construction equipment, and avoiding path conflicts and driving deadlocks during operation.

Description

Technical Field

[0001] This application relates to the field of bridge construction, and in particular to a collaborative steering control method and system for bridge deck construction equipment. Background Technology

[0002] Steering control of multi-axle, long-vehicle construction equipment on bridge decks is crucial for ensuring safety and efficiency in the confined spaces of bridge and tunnel construction, directly impacting construction progress and structural safety. The industry commonly employs an onboard independent sensing and control solution, relying on equipment such as beam transport vehicles equipped with LiDAR, high-precision positioning modules, and onboard computing units. This allows the equipment to autonomously perceive road conditions and perform steering calculations, with communication between devices facilitating coordination. However, this onboard autonomous control mode significantly increases the hardware cost and weight of individual equipment units and is prone to path conflicts and driving lock-up due to coordination disorder between devices, making it unsuitable for confined bridge deck operations.

[0003] At present, the collaborative steering control of bridge deck construction equipment has technical problems such as high cost of vehicle-mounted autonomous control mode and poor equipment coordination, which can easily lead to operational conflicts. Summary of the Invention

[0004] This application provides a collaborative steering control method and system for bridge deck construction equipment. It establishes a bridge deck perception network, collects and analyzes bridge deck construction status data through this network to obtain bridge deck construction reference path coordinates, performs multi-axis trajectory tracking calculations on the construction equipment based on these reference path coordinates, and establishes a multi-axis alignment time sequence. Using this time sequence as anchor points, it analyzes the time-series steering control parameters of the equipment's multiple axes, verifies the target collaboration of the steering control parameters for each axis, determines the collaborative steering control strategy, and realizes multi-axis collaborative steering control of bridge deck construction equipment. This solves the technical problems of high cost and poor equipment coordination in existing collaborative steering control modes for bridge deck construction equipment, which can easily lead to operational conflicts. It achieves the technical effects of reducing the hardware cost of bridge deck construction equipment, improving the coordination of multi-axis construction equipment, and avoiding path conflicts and driving deadlocks during operation.

[0005] This application provides a collaborative steering control method for bridge deck construction equipment, comprising: establishing a bridge deck perception network; collecting and analyzing bridge deck construction status data through the bridge deck perception network to obtain bridge deck construction reference path coordinates; performing multi-axis trajectory tracking calculation on the bridge deck construction equipment based on the bridge deck construction reference path coordinates to establish an alignment time sequence for multi-axis bridge deck construction; using the alignment time sequence as a time sequence control anchor point to analyze the time sequence steering control parameters of the equipment's multiple axes to obtain steering control parameters for each axis node; and performing target collaboration verification based on the steering control parameters of each axis node to determine a collaborative steering control strategy for multi-axis collaborative steering control of the bridge deck construction equipment.

[0006] In one possible implementation, a bridge deck sensing network is established, and the following processing is performed: Based on the geometric features of the bridge deck construction area and the access requirements of construction equipment, the deployment spacing, array, fixing method, and identification and calibration information of the sensing nodes are configured; according to the deployment spacing and array, multiple sensing nodes are deployed within the bridge deck construction area, each sensing node acting as a terminal node, communicating with the edge server gateway via a wireless communication protocol, thus establishing a self-organizing bridge deck sensing network covering the entire bridge deck construction area; wherein, the sensing nodes include vibration sensors, geomagnetic sensors, strain sensors, and cameras.

[0007] In a possible implementation, bridge deck construction status data is collected and analyzed through a bridge deck sensing network to obtain bridge deck construction reference path coordinates. The following processing is then performed: Local data acquisition and preprocessing are performed through each sensing node of the bridge deck sensing network. This includes distortion correction, semantic segmentation, and morphological processing of images captured by cameras to extract the local coordinates of the ink line centerline; disturbance detection is performed on geomagnetic sensor signals to identify the passage of construction equipment and record timestamps; vibration and strain signals are filtered and feature extracted; coordinate transformation is performed based on the processed local coordinate point set of the ink line to generate global coordinates; and ink line segments from adjacent nodes are spliced ​​together to generate initial coordinates. The preliminary ink line point set is prepared; based on the geomagnetic event timestamp and node coordinates, the actual passing position of the construction equipment is calculated, and the preliminary ink line point set is curve matched with the actual passing position to calculate the lateral deviation sequence. Based on the lateral deviation sequence, the preliminary ink line point set is normalized to obtain the calibrated bridge deck construction reference path coordinate set; based on the vibration and strain characteristics, the equivalent stiffness coefficient at each position on the bridge deck is calculated, and the equivalent stiffness coefficient is attached as an attribute to the corresponding point in the bridge deck construction reference path coordinate set to output the final bridge deck construction reference path coordinates. The bridge deck construction reference path coordinates include the three-dimensional coordinates, curvature, slope, and bridge deck stiffness coefficient of each point.

[0008] In a possible implementation, multi-axis trajectory tracking calculations are performed on the bridge deck construction equipment based on the bridge deck construction reference path coordinates to establish an alignment time sequence for multi-axis bridge deck construction. The following processing is then performed: the steering connection relationship between the multi-axis wheel sets of the bridge deck construction equipment is analyzed, and the steering connection relationship includes at least the relative position constraints between the axes of each wheel set, the torsional stiffness constraints of the frame, and the kinematic coupling relationship of the wheel set rotation angle; based on the continuous geometric features of the steering connection relationship and the bridge deck construction reference path coordinates, multi-axis collaborative alignment is performed to determine the expected motion state of each wheel set relative to the reference path and the difference in expected motion states between each wheel set; based on the expected motion state and the difference in expected motion states, an alignment time sequence is generated, which is used to characterize the alignment state of each wheel set relative to the reference path at each moment during the journey and the mutual alignment relationship between each wheel set.

[0009] In a possible implementation, the desired motion state of each wheelset relative to a reference path is determined, and the following processing is performed: based on the longitudinal distance between the axis of each wheelset and the geometric center of the vehicle, a reference point corresponding to each wheelset is determined on the coordinates of the bridge construction reference path; based on the lateral offset of the axis of each wheelset, the reference point is offset along the normal of the reference path to obtain the desired trajectory point of each wheelset axis; differential geometric analysis is performed on the desired trajectory point to obtain the desired curvature of each wheelset axis at each time moment, and based on the vehicle kinematics model, the desired curvature is converted into the desired rotation angle of each wheelset, which is taken as the desired motion state of each wheelset relative to the reference path.

[0010] In a possible implementation, the alignment timing sequence is used as the timing control anchor point to analyze the timing steering control parameters of the equipment's multi-axis system, obtaining the steering control parameters of each axis node. The following processing is then performed: Using the desired turning angle of each wheel group in the alignment timing sequence as the control target anchor point, a basic command is generated; the actual turning angle of each wheel group is obtained, and the actual turning angle difference between adjacent wheel groups is calculated; when the actual turning angle difference between adjacent wheel groups exceeds the corresponding turning angle difference limit, a turning angle correction amount in the opposite direction is applied to the corresponding adjacent wheel group; the actual load of each wheel group is obtained, and when the actual load of any wheel group deviates from the load balance threshold, a load compensation correction amount is applied to the turning angle command corresponding to that wheel group; the basic steering command, the turning angle correction amount, and the load compensation correction amount are superimposed and, after amplitude limiting processing, the steering control parameters of each wheel group are obtained.

[0011] In a possible implementation, target coordination verification is performed based on the steering control parameters of each axle node to determine the coordinated steering control strategy. The following processing is then performed: using the steering control parameters of all axle nodes as initial values, the predicted driving trajectory of the vehicle's geometric center is predicted; the lateral tracking deviation, heading deviation, and predicted angle difference between adjacent axle wheel sets are calculated between the predicted driving trajectory and the bridge construction reference path coordinates; when the lateral tracking deviation, heading deviation, or any predicted angle difference exceeds the corresponding allowable range, a global path correction and a global coordination correction are generated and allocated to the corresponding axle wheel sets; the global coordination correction and the global path correction are superimposed on the steering control parameters and iterated multiple times until the angle difference of all adjacent wheel sets meets the threshold and the trajectory tracking deviation is within the allowable range, and the iterated parameters are used as the final coordinated steering control strategy.

[0012] In possible implementations, the following processing is also performed: a bridge deck boundary constraint region is generated based on the bridge deck edge line, the guardrail edge line, or the component installation control line; when predicting the predicted driving trajectory of the vehicle's geometric center and the predicted trajectories of each axle and wheel group, if any predicted trajectory enters the bridge deck boundary constraint region, a boundary avoidance correction amount is generated, and the boundary avoidance correction amount is allocated to the corresponding axle and wheel group.

[0013] In a possible implementation, the following processing is performed: the cooperative steering control strategy includes a set of steering control parameters corresponding to at least one of the following modes: straight driving mode, curve tracking mode, and lateral movement mode, wherein the straight driving mode, curve tracking mode, and lateral movement mode are switched according to the curvature of the bridge deck construction reference path, the lateral deviation between the construction equipment and the target position, the heading deviation, and the remaining adjustment distance.

[0014] This application also provides a collaborative steering control system for bridge deck construction equipment, comprising: a bridge deck construction status data acquisition and analysis module for establishing a bridge deck perception network, acquiring and analyzing bridge deck construction status data through the bridge deck perception network to obtain bridge deck construction reference path coordinates; a multi-axis trajectory tracking and calculation module for performing multi-axis trajectory tracking and calculation on the bridge deck construction equipment based on the bridge deck construction reference path coordinates to establish an alignment time sequence for multi-axis bridge deck construction; a time-series steering control parameter analysis module for using the alignment time sequence as a time-series control anchor point to analyze the time-series steering control parameters of the equipment's multiple axes to obtain steering control parameters for each axis node; and a multi-axis collaborative steering control module for performing target collaborative verification based on the steering control parameters of each axis node to determine a collaborative steering control strategy for multi-axis collaborative steering control of the bridge deck construction equipment.

[0015] The proposed method and system for collaborative steering control of bridge deck construction equipment, as described in this application, first establishes a bridge deck perception network. This network is used to collect and analyze bridge deck construction status data, obtaining reference path coordinates for the construction. Next, based on these reference path coordinates, multi-axis trajectory tracking calculations are performed on the bridge deck construction equipment to establish an alignment time sequence for multi-axis bridge deck construction. Then, using this alignment time sequence as a time-series control anchor point, time-series steering control parameters are analyzed for the equipment's multiple axes, obtaining steering control parameters for each axis node. Finally, target collaboration verification is performed based on the steering control parameters of each axis node to determine the collaborative steering control strategy for multi-axis collaborative steering control of the bridge deck construction equipment. Through this process, the proposed method and system achieve the technical effects of reducing the hardware cost of bridge deck construction equipment, improving the collaboration of multi-axis construction equipment, and avoiding path conflicts and driving lock-up during operation. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a flowchart illustrating a collaborative steering control method for bridge deck construction equipment provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the structure of a cooperative steering control system for bridge deck construction equipment provided in an embodiment of this application.

[0019] Explanation of reference numerals in the attached diagram: 10 for bridge deck construction status data acquisition and analysis module, 20 for multi-axis trajectory tracking and calculation module, 30 for time-series steering control parameter analysis module, and 40 for multi-axis cooperative steering control module. Detailed Implementation

[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0021] This application provides a cooperative steering control method for bridge deck construction equipment, applicable to narrow spaces such as bridge decks and tunnels, for multi-axle cooperative steering control of bridge deck construction equipment with long bodies and multi-axle wheel sets, such as beam transport vehicles. Figure 1 As shown, the method includes: Step S100: Establish a bridge deck perception network, collect and analyze bridge deck construction status data through the bridge deck perception network, and obtain the bridge deck construction reference path coordinates.

[0022] Specifically, a distributed bridge deck sensing network is constructed based on pre-embedded intelligent sensing nodes to replace the high-precision sensing equipment on construction vehicles. Edge servers integrate all node data to generate a reference path with bridge deck stiffness attributes, abandoning the independent sensing and calculation mode of a single vehicle. First, the sensing node network deployment is completed, then multi-source data is preprocessed locally. After coordinate transformation, trajectory calibration, and stiffness inversion, a global reference path integrating three-dimensional coordinates, curvature, slope, and stiffness coefficients is output, providing a unique global benchmark for multi-axis collaborative control.

[0023] In one possible implementation, a bridge deck sensing network is established. Step S100 further includes step S110, which configures the spacing, array, fixing method, and identification and calibration information of sensing nodes based on the geometric features of the bridge deck construction area and the passage requirements of construction equipment. The sensing nodes include vibration sensors, geomagnetic sensors, strain sensors, and cameras. Specifically, the spacing is matched to the bridge deck curve radius values. For example, geometric parameters of straight sections, curved sections, and slope change points in the bridge deck construction area are collected, along with data on the wheel track width of the construction equipment. The spacing of sensing nodes is set to 10 to 20 meters on straight sections, and reduced to 5 to 10 meters on curved sections and slope change points. A single-row or double-row array is selected to form the sensing array based on the wheel track width. The fixing method involves pre-embedding the nodes into pre-reserved holes in the bridge deck pavement or using detachable bases for temporary fixing. A combined calibration method using a total station and RTK-GNSS is employed. First, the total station is set up and aligned with the bridge deck control points to collect the three-dimensional coordinates of the nodes. Then, the absolute coordinates in the WGS84 coordinate system are obtained through RTK-GNSS. After coordinate system transformation, a unique ID is bound to the node. The sensing node integrates a three-axis vibration sensor, a fluxgate magnetometer, a resistance strain gauge sensor, and a wide-angle industrial camera. The node is powered by a combination of solar cells and lithium batteries to achieve multi-dimensional data acquisition.

[0024] Step S120: Based on the deployment spacing and array, multiple sensing nodes are deployed within the bridge deck construction area. Each sensing node acts as a terminal node, communicating with the edge server gateway via a wireless communication protocol to establish a self-organizing bridge deck sensing network covering the entire construction area. Specifically, all sensing nodes are installed on-site according to the deployment parameters determined in step S110. Each sensing node is set as a network terminal node. LoRaWAN or NB-IoT low-power wide-area network transmission protocols are selected to establish communication links between the sensing nodes and the edge server gateway. The nodes automatically complete network topology matching. For example, nodes on curved sections use mesh networking to improve communication redundancy, while nodes on straight sections use star networking to reduce power consumption. The LoRaWAN protocol sets the communication frequency band to 470MHz-510MHz, and NB-IoT relies on operator base stations for transmission, constructing a self-organizing sensing network that fully covers the construction area. Nodes upload data periodically to ensure stable data transmission to the edge server.

[0025] In one possible implementation, bridge deck construction status data is collected and analyzed through a bridge deck perception network to obtain the coordinates of the bridge deck construction reference path. Step S100 further includes step S130, where local data acquisition and preprocessing are performed through each sensing node of the bridge deck perception network. This includes distortion correction, semantic segmentation, and morphological processing of images captured by the camera to extract the local coordinates of the ink line centerline; disturbance detection of geomagnetic sensor signals to identify the passage events of construction equipment and record the timestamps; and filtering and feature extraction of vibration and strain signals. Specifically, the sensing nodes have built-in processing chips that perform local preprocessing. After the camera acquires the construction ink line image, lens distortion errors are eliminated using the Zhang Zhengyou calibration method. The U-Net semantic segmentation network is used to distinguish the ink line from the bridge deck background. Image noise is removed through opening operation morphological processing, and the local pixel coordinates of the ink line centerline are extracted. The geomagnetic sensor collects magnetic field data in real time, sets a dynamic disturbance threshold, detects magnetic field disturbance signals by threshold comparison, eliminates interference signals from construction machinery, determines the events of construction equipment passing through nodes, and synchronously records the timestamps of the events. The signals collected by the vibration sensor and strain sensor are filtered for environmental noise by a Butterworth low-pass filter, and the signal amplitude and frequency characteristic data are extracted. The preprocessed data is then uploaded via a wireless network.

[0026] Step S140 involves performing coordinate transformation based on the processed local coordinate set of ink lines to generate global coordinates, and then stitching together ink line segments from adjacent nodes to generate a preliminary ink line point set. Specifically, after receiving the local coordinates of the ink lines, the edge server calls the node world coordinates calibrated in step S110 and converts the pixel local coordinates into engineering global coordinates through coordinate mapping. The ink line coordinate data transmitted from adjacent sensing nodes are read sequentially, and ink line segments are stitched together according to the node deployment order. Duplicate coordinate points are removed to form a continuous preliminary ink line point set, which serves as the basic path data.

[0027] Step S150: Based on the geomagnetic event timestamp and node coordinates, the actual passing position of the construction equipment is calculated. The preliminary ink line point set is then curve-matched with the actual passing position to calculate the lateral deviation sequence. Based on the lateral deviation sequence, the preliminary ink line point set is normalized to obtain the calibrated bridge deck construction reference path coordinate set. Specifically, the edge server combines the timestamps recorded by the geomagnetic sensor with the corresponding node coordinates, and calculates the actual passing coordinates of the equipment using linear interpolation based on the geomagnetic timestamp difference and the equipment's travel speed. The preliminary ink line point set and the actual passing position are curve-matched using cubic spline curve fitting, and the lateral offset between the ink line and the actual travel trajectory is calculated point by point to form a lateral deviation sequence. The coordinates of the preliminary ink line point set are adjusted point by point along the reference path normal direction to eliminate the lateral deviation, complete the path calibration, and generate the calibrated reference path coordinate set.

[0028] Step S160: Based on the vibration and strain characteristics, the equivalent stiffness coefficient at each location on the bridge deck is calculated by inversion. This equivalent stiffness coefficient is then appended as an attribute to the corresponding point in the bridge deck construction reference path coordinate set, outputting the final bridge deck construction reference path coordinates. These coordinates include the three-dimensional coordinates, curvature, slope, and bridge deck stiffness coefficient for each point. Specifically, the edge server calculates the equivalent stiffness coefficient at the corresponding bridge deck location through stiffness inversion based on the bridge deck deformation value measured by strain sensors and the natural frequency measured by vibration sensors, combined with the elastic modulus parameters of the bridge deck pavement material. The three-dimensional coordinates, curvature, and slope data are bound to the corresponding coordinate points, integrating them to form the final bridge deck construction reference path coordinates containing complete attributes, which are used for trajectory calculation.

[0029] Step S200: Based on the bridge deck construction reference path coordinates, perform multi-axis trajectory tracking calculation on the bridge deck construction equipment to establish an alignment time sequence for multi-axis bridge deck construction.

[0030] Specifically, it breaks through the traditional independent steering control logic of a single vehicle, uses the final bridge construction reference path coordinates as a benchmark, analyzes the kinematic coupling relationship of multi-axle wheel sets, calculates the motion state of each wheel set in combination with the path geometric features, and constructs a standardized wheel set coordination timing sequence to ensure the coordinated action of wheel sets during the driving of long-body multi-axle equipment.

[0031] In one possible implementation, multi-axis trajectory tracking calculations are performed on the bridge deck construction equipment based on the bridge deck construction reference path coordinates to establish an alignment time sequence for multi-axis bridge deck construction. Step S200 further includes step S210, which analyzes the steering connection relationship between the multi-axis wheel sets of the bridge deck construction equipment. The steering connection relationship includes at least the relative position constraints between the axes of each wheel set, the torsional stiffness constraints of the frame, and the kinematic coupling relationship of the wheel set rotation angle. Specifically, the mechanical design parameters of the construction equipment are retrieved to determine the longitudinal and lateral relative position constraints between the axes of each wheel set, the frame torsional stiffness limit parameters are collected, a wheel set rotation angle linkage relationship model is established, and the rotation angle linkage rules of the other wheel sets when a single wheel set rotates are clarified, thus completing the quantitative analysis of the steering connection relationship.

[0032] Step S220: Based on the continuous geometric characteristics of the steering connection relationship and the bridge deck construction reference path coordinates, multi-axis collaborative alignment is performed to determine the expected motion state of each wheel set relative to the reference path and the differences in expected motion states between wheel sets. Specifically, combined with the steering connection relationship constraints, the continuous curvature and slope variation characteristics of the reference path are analyzed. The adaptation relationship between each wheel set and the reference path is matched through kinematic calculations. The expected motion parameters of each wheel set are calculated separately, and the parameters of each wheel set are compared to determine the difference in expected motion states between wheel sets.

[0033] Step S230: Based on the desired motion state and the difference between desired motion states, an alignment timing sequence is generated. This alignment timing sequence characterizes the alignment state of each wheelset relative to the reference path at each moment during travel, as well as the mutual alignment relationship between wheelsets. Specifically, timing nodes are divided according to the equipment's travel mileage. Each timing node corresponds to the desired turning angle of each wheelset and the coordination deviation value between wheelsets. An alignment timing sequence containing time nodes, wheelset numbers, desired turning angles, and coordination differences is generated, which is a timing control linked list used to standardize the timing logic of wheelset coordinated actions. The edge server synchronously issues timing commands according to the travel speed to avoid frame torsion caused by asynchronous steering of multi-axle wheelsets.

[0034] In one possible implementation, determining the desired motion state of each wheelset relative to the reference path, step S220 further includes step S221, which determines the reference point corresponding to each wheelset on the bridge construction reference path coordinates based on the longitudinal distance between the axis of each wheelset and the vehicle's geometric center. Specifically, the edge server establishes a vehicle coordinate system with the vehicle's geometric center as the origin, reads the longitudinal offset parameters of each wheelset axis, and, along the mileage direction of the global reference path, reverses the path coordinates at the corresponding mileage according to this distance, matching a corresponding path reference point for each wheelset.

[0035] Step S222: Based on the lateral offset of each wheelset axis, the reference point is offset along the normal direction of the reference path to obtain the desired trajectory point of each wheelset axis. Specifically, preset lateral offset parameters of the wheelset axis are collected, and the reference point determined in step S221 is used as a reference. The position is adjusted along the normal direction of the reference path according to the offset parameters to generate the desired trajectory point adapted to the position of the wheelset.

[0036] Step S223 involves performing differential geometric analysis on the desired trajectory points to obtain the desired curvature of each wheelset axis at each moment. Based on the vehicle kinematics model, the desired curvature is converted into the desired steering angle of each wheelset, which serves as the desired motion state of each wheelset relative to the reference path. Specifically, the finite difference method is used to calculate the continuous curvature of the sequence of desired trajectory points to obtain the desired curvature of each wheelset at different driving moments. According to the Ackermann steering kinematics model, combined with the wheelbase and track parameters, the trajectory curvature is converted into the steering angle of the wheelset. This desired steering angle is the desired motion state of the wheelset. The desired steering angle is dynamically adjusted according to the curvature magnitude for curved segments, while the desired steering angle for straight segments is zero, ensuring that the wheelset trajectory conforms to the reference path.

[0037] Step S300: Using the alignment timing sequence as the timing control anchor point, the timing steering control parameters of the equipment multi-axis are analyzed to obtain the steering control parameters of each axis node.

[0038] Specifically, using the alignment timing sequence as the control benchmark and combining it with the actual operating data of the wheelset, the basic instruction generation, angle correction, and load compensation are completed sequentially. Finally, the steering control parameters of each axle wheelset that can be directly executed are calculated, solving the problems of uneven wheelet load and excessive angle difference caused by simple trajectory tracking.

[0039] In one possible implementation, the aligned timing sequence is used as a timing control anchor point to parse the timing steering control parameters of the equipment's multi-axis system, obtaining the steering control parameters for each axis node. Step S300 further includes step S310, using the desired turning angle of each wheel group in the aligned timing sequence as a control target anchor point to generate basic instructions. Specifically, the edge server reads the desired turning angle data of the corresponding time node within the aligned timing sequence and converts this data into basic steering execution instructions, serving as the initial instructions for wheel group control.

[0040] Step S320: Obtain the actual rotation angle of each axle wheel set and calculate the actual rotation angle difference between adjacent axle wheel sets. Specifically, the actual rotation angle is collected in real time by the built-in rotation angle sensor of the wheel set. After receiving the data, the edge server calculates the actual angle difference between adjacent two wheel sets one by one to complete the rotation angle difference statistics.

[0041] Step S330: When the actual angle difference between adjacent axle wheelsets exceeds the corresponding angle difference limit, apply an angle correction amount in the opposite direction to the corresponding adjacent axle wheelsets. Specifically, a preset wheel set angle difference safety threshold is established. When the actual angle difference exceeds this threshold, angle correction amounts in the opposite direction are assigned to the two adjacent wheelsets. For example, if the preset adjacent wheel set angle difference threshold is 3 degrees, when the threshold is exceeded, the angle correction amount is calculated using a proportional-integral algorithm. A reverse correction amount is applied to the front axle wheelset, and a positive correction amount is applied to the rear axle wheelset, gradually reducing the angle difference value and preventing plastic torsion of the frame.

[0042] Step S340: Obtain the actual load of each axle wheel assembly. When the actual load of any axle wheel assembly deviates from the load balance threshold, apply a load compensation correction to the corresponding rotation angle command for that axle wheel assembly. Specifically, the wheel assembly is equipped with a pressure-type load sensor. Real-time load data is collected through the load sensor, and a load balance threshold is set. When the load of the wheel assembly is higher or lower than the threshold, the load compensation correction is calculated according to the load deviation ratio and added to the rotation angle command. For example, the load balance deviation threshold is set to 10% of the rated load. When the load is too high, the rotation angle of the corresponding wheel assembly is reduced to decrease the force. When the load is too low, the rotation angle is finely adjusted to balance the load. The compensation coefficient is calculated linearly according to the load deviation ratio.

[0043] Step S350: The basic steering command, angle correction, and load compensation correction are superimposed and then subjected to amplitude limiting processing to obtain the steering control parameters for each axle and wheel set. Specifically, the basic steering command value is added to the angle correction and load compensation correction values, and amplitude limiting processing is performed according to the maximum steering angle limit of the wheel set to prevent over-range rotation, ultimately generating the usable steering control parameters for each axle and wheel set.

[0044] Step S400: Target coordination verification is performed based on the steering control parameters of each axis node to determine a coordinated steering control strategy for multi-axis coordinated steering control of the bridge deck construction equipment. The coordinated steering control strategy includes a set of steering control parameters corresponding to at least one of the following modes: straight-line mode, curve tracking mode, and lateral movement mode. The straight-line mode, curve tracking mode, and lateral movement mode are switched based on the curvature of the bridge deck construction reference path, the lateral deviation between the construction equipment and the target position, the heading deviation, and the remaining adjustment distance.

[0045] Specifically, the edge server first initiates a collaborative verification process based on the steering control parameters of each axle wheel set as the basic data. Simultaneously, it defines the criteria for three operating modes and, combined with real-time operating conditions, completes mode switching to ultimately form an executable control strategy. First, it sets the following thresholds: curvature straight-line threshold, curvature hysteresis threshold, lateral straight-line maintenance threshold, lateral straight-line maintenance hysteresis threshold, lateral lateral movement trigger threshold, normal heading threshold, normal heading hysteresis threshold, long-distance adjustment threshold, and short-distance adjustment threshold. Furthermore, the curvature hysteresis threshold is less than the curvature straight-line threshold, the lateral straight-line maintenance hysteresis threshold is less than the lateral straight-line maintenance threshold, and the normal heading hysteresis threshold is less than the normal heading threshold. Based on these thresholds, the curvature value of the bridge construction reference path is determined. When the path curvature is less than the curvature straight-line threshold, and the lateral deviation between the construction equipment and the target path is less than the lateral straight-line maintenance threshold and the heading deviation is less than the normal heading threshold, while the remaining adjustment distance is greater than the long-distance adjustment threshold, the system enters the straight-line mode. In this mode, all wheel sets maintain the same direction and angle of steering, ensuring the vehicle's straight-line driving posture. When the path curvature is greater than or equal to the curvature straight-line threshold, or the lateral deviation is between the lateral straight-line maintenance threshold and the lateral lateral movement trigger threshold, or the heading deviation is greater than or equal to the heading normal threshold, the system switches to curve tracking mode. In this mode, steering angles are differentiated based on the reference trajectory curvature of each wheel set, and curve steering is completed following a multi-axis timing alignment sequence. When the construction equipment needs to be adjusted for alignment in a narrow area of ​​the bridge deck, and the lateral deviation is greater than or equal to the lateral lateral movement trigger threshold while the remaining adjustment distance is less than or equal to the adjustment short distance threshold, the system automatically switches to lateral movement mode. In this mode, the left and right wheel sets turn in opposite directions to achieve lateral translation and alignment of the entire vehicle. When exiting curve mode and returning to straight-line mode, the following conditions must be met simultaneously: curvature less than the curvature hysteresis threshold, lateral deviation less than the lateral straight-line maintenance hysteresis threshold, heading deviation less than the heading normal hysteresis threshold, and remaining adjustment distance greater than the adjustment long distance threshold. During mode operation, trajectory and turning angle co-verification are performed simultaneously to ensure that the strategy adapts to the construction scenario.

[0046] In one possible implementation, target collaborative verification is performed based on the steering control parameters of each axle node to determine the collaborative steering control strategy. Step S400 further includes step S410, which uses the steering control parameters of all axle nodes as initial values ​​to predict the predicted driving trajectory of the vehicle's geometric center. Specifically, the edge server calls a multi-rigid-body dynamics model to construct the constraint relationship between the frame and the wheelset. Combining the vehicle's kinematic equations, it inputs the steering control parameters of each wheelset, the vehicle's wheelbase, track width, and driving speed parameters. It simulates and deduces the position coordinates of the vehicle's geometric center time-by-time, continuously calculating according to the time series to form a continuous set of predicted driving trajectory coordinates. At the same time, it synchronously calculates the independent driving trajectory of each axle wheelet.

[0047] Step S420: Calculate the lateral tracking deviation, heading deviation, and predicted turning angle difference between adjacent axle wheel sets, based on the coordinates of the predicted driving trajectory and the bridge construction reference path. Specifically, the predicted driving trajectory coordinates are compared point-by-point with the bridge construction reference path coordinates, and the vertical distance between the two points is calculated to obtain the lateral tracking deviation. The heading deviation is obtained by comparing the tangent direction of the predicted trajectory with the tangent direction of the reference path, and the angle difference is calculated. The predicted steering angle of each wheel set is retrieved, and the angle difference between adjacent wheel sets is calculated sequentially to obtain the predicted turning angle difference. These three types of data are stored in real time on the edge server.

[0048] Step S430: When the lateral tracking deviation, heading deviation, or any predicted angle difference exceeds the corresponding allowable range, a global path correction and a global coordination correction are generated, and these are allocated to the corresponding axle and wheel sets. Specifically, preset allowable values ​​for lateral tracking deviation, heading deviation, and predicted angle difference between adjacent wheel sets are defined. When any data exceeds the corresponding threshold, a pure proportional adjustment method is used to calculate the global path correction based on the product of the deviation value and a preset proportional coefficient, which is used to adjust the trajectory to fit the reference path. The global coordination correction is calculated based on the excessive angle difference value, and weights are assigned according to the longitudinal position of the wheel set on the frame, with the front axle wheel set receiving a higher weight than the rear axle wheel set, thus allocating the two types of corrections to the corresponding axle and wheel sets.

[0049] Step S440: The global coordination correction and global path correction are superimposed on the steering control parameters, and multiple iterations are performed until the angle difference between all adjacent wheel sets meets the threshold and the trajectory tracking deviation is within the allowable range. The iterated parameters are then used as the final cooperative steering control strategy. Specifically, the correction is added to the original steering control parameter values. After updating the parameters, the trajectory prediction and deviation calculation process is re-executed. When the angle difference between adjacent wheel sets is less than the allowable value of the predicted angle difference between adjacent wheel sets, the lateral tracking deviation is less than the allowable value of the lateral tracking deviation, and the heading deviation is less than the allowable value of the heading deviation, the iteration stops. The steering control parameters after iteration are matched with the corresponding operating mode to form the final cooperative steering control strategy.

[0050] In one possible implementation, step S400 further includes step S450, generating a bridge deck boundary constraint region based on the bridge deck edge line, the retaining wall edge line, or the component installation control line. Specifically, the edge server imports the bridge deck construction design drawings, extracts the three-dimensional coordinate data of the bridge deck edge line, the retaining wall edge line, and the component installation control line, and extends a certain distance inward from the bridge deck as a safety buffer zone based on these edge lines. The buffer zone and the prohibited passage zone together constitute the bridge deck boundary constraint region, which is then converted into coordinate range data.

[0051] Step S460: When predicting the predicted driving trajectory of the vehicle's geometric center and the predicted trajectories of each axle and wheel group, if any predicted trajectory enters the bridge surface boundary constraint area, a boundary avoidance correction is generated and allocated to the corresponding axle and wheel group. Specifically, the predicted trajectory coordinates are compared with the coordinate range of the bridge surface boundary constraint area in real time. When the trajectory coordinates are detected to fall into the constraint area, the distance and direction of the trajectory intrusion into the constraint area are calculated. The correction is calculated based on the intrusion distance, generating a boundary avoidance correction towards the center of the bridge surface. In lateral movement mode, the reverse steering angle of the two wheel groups is adjusted first. In curve tracking mode, the steering angle difference between the front and rear axle wheel groups is adjusted, while the equipment speed is reduced simultaneously to complete the boundary avoidance.

[0052] This application embodiment establishes a bridge deck perception network, collects and analyzes bridge deck construction status data through this network to obtain bridge deck construction reference path coordinates, performs multi-axis trajectory tracking calculations on construction equipment based on the reference path coordinates, and establishes a multi-axis alignment time sequence. Using this time sequence as anchor points, it analyzes the time-series steering control parameters of the equipment's multiple axes, performs target coordination verification on the steering control parameters of each axis, determines the coordination steering control strategy, and realizes multi-axis coordination steering control of bridge deck construction equipment. This solves the technical problems of high cost of vehicle-mounted autonomous control mode and poor equipment coordination that easily leads to operational conflicts in the existing coordination steering control of bridge deck construction equipment. It achieves the technical effects of reducing the hardware cost of bridge deck construction equipment, improving the coordination of multi-axis construction equipment, and avoiding path conflicts and driving deadlocks during operation.

[0053] In the above text, refer to Figure 1 A cooperative steering control method for bridge deck construction equipment according to an embodiment of the present invention is described in detail. Next, reference will be made to... Figure 2 A cooperative steering control system for bridge deck construction equipment according to an embodiment of the present invention is described.

[0054] The cooperative steering control system for bridge deck construction equipment according to embodiments of the present invention addresses the technical problems of high cost and poor equipment coordination in existing bridge deck construction equipment cooperative steering control systems, which can easily lead to operational conflicts. It achieves the technical effects of reducing the hardware cost of bridge deck construction equipment, improving the coordination of multi-axle construction equipment, and avoiding path conflicts and driving lock-up during operation. The cooperative steering control system for bridge deck construction equipment includes: a bridge deck construction status data acquisition and analysis module 10, a multi-axle trajectory tracking and calculation module 20, a timing steering control parameter analysis module 30, and a multi-axle cooperative steering control module 40.

[0055] The bridge deck construction status data acquisition and analysis module 10 is used to establish a bridge deck perception network, acquire and analyze bridge deck construction status data through the bridge deck perception network, and obtain the bridge deck construction reference path coordinates; the multi-axis trajectory tracking and calculation module 20 is used to perform multi-axis trajectory tracking and calculation on the bridge deck construction equipment based on the bridge deck construction reference path coordinates, and establish an alignment time sequence for multi-axis bridge deck construction; the time sequence steering control parameter analysis module 30 is used to use the alignment time sequence as a time sequence control anchor point to analyze the time sequence steering control parameters of the equipment's multiple axes, and obtain the steering control parameters of each axis node; the multi-axis collaborative steering control module 40 is used to perform target collaborative verification based on the steering control parameters of each axis node, determine the collaborative steering control strategy, and perform multi-axis collaborative steering control of the bridge deck construction equipment.

[0056] The detailed description of the specific configuration of the bridge deck construction status data acquisition and analysis module 10 is explained as follows: As mentioned above, to establish a bridge deck sensing network, the bridge deck construction status data acquisition and analysis module 10 may further include: a sensing node configuration unit for configuring the deployment spacing, deployment array, fixing method, and identification and calibration information of sensing nodes according to the geometric features of the bridge deck construction area and the passage requirements of construction equipment; and a self-organizing network bridge deck sensing network establishment unit for deploying multiple sensing nodes in the bridge deck construction area according to the deployment spacing and deployment array, with each sensing node acting as a terminal node and communicating with the edge server gateway through a wireless communication protocol to establish a self-organizing network bridge deck sensing network covering the entire bridge deck construction area; wherein, the sensing nodes include vibration sensors, geomagnetic sensors, strain sensors, and cameras.

[0057] The bridge deck construction status data acquisition and analysis module 10, which obtains bridge deck construction reference path coordinates through a bridge deck perception network, can further include: a local data acquisition unit for performing local data acquisition and preprocessing through each sensing node of the bridge deck perception network, including distortion correction, semantic segmentation, and morphological processing of images acquired by cameras to extract the local coordinates of the ink line centerline; disturbance detection of geomagnetic sensor signals to identify the passage events of construction equipment and record timestamps; filtering and feature extraction of vibration and strain signals; and a preliminary ink line point set generation unit for performing coordinate transformation based on the processed local coordinate point set of the ink line to generate global coordinates and splicing ink line segments of adjacent nodes. Next, a preliminary ink line point set is generated; the normal correction unit is used to back-calculate the actual passing position of the construction equipment based on the geomagnetic event timestamp and node coordinates, perform curve matching between the preliminary ink line point set and the actual passing position, calculate the lateral deviation sequence, and perform normal correction on the preliminary ink line point set based on the lateral deviation sequence to obtain the calibrated bridge deck construction reference path coordinate set; the equivalent stiffness coefficient inversion calculation unit is used to invert and calculate the equivalent stiffness coefficient at each position on the bridge deck based on the vibration and strain characteristics, and attach the equivalent stiffness coefficient as an attribute to the corresponding point in the bridge deck construction reference path coordinate set, outputting the final bridge deck construction reference path coordinates, which include the three-dimensional coordinates, curvature, slope and bridge deck stiffness coefficient of each point.

[0058] The detailed description of the specific configuration of the multi-axis trajectory tracking and calculation module 20 is as follows: As mentioned above, the multi-axis trajectory tracking and calculation of the bridge deck construction equipment is performed based on the bridge deck construction reference path coordinates to establish an alignment time sequence for multi-axis bridge deck construction. The multi-axis trajectory tracking and calculation module 20 may further include: a steering connection relationship analysis unit for analyzing the steering connection relationship between the multi-axis wheel sets of the bridge deck construction equipment, wherein the steering connection relationship includes at least the relative position constraints between the axes of each wheel set, the frame torsional stiffness constraints, and the kinematic coupling relationship of the wheel set rotation angle; a multi-axis collaborative alignment unit for performing multi-axis collaborative alignment based on the continuous geometric features of the steering connection relationship and the bridge deck construction reference path coordinates to determine the expected motion state of each wheel set relative to the reference path and the difference in expected motion states between each wheel set; and an alignment time sequence generation unit for generating an alignment time sequence based on the expected motion state and the difference in expected motion states, wherein the alignment time sequence is used to characterize the alignment state of each wheel set relative to the reference path at each moment during the driving process and the mutual alignment relationship between each wheel set.

[0059] The multi-axis collaborative alignment unit, which determines the desired motion state of each wheelset relative to the reference path, may further include: a reference point determination subunit for determining the reference point corresponding to each wheelset on the bridge construction reference path coordinates based on the longitudinal distance between the axis of each wheelset and the geometric center of the vehicle; a desired trajectory point acquisition subunit for offsetting the reference point along the normal direction of the reference path based on the lateral offset of the axis of each wheelset to obtain the desired trajectory point of each wheelset axis; and a differential geometry analysis subunit for performing differential geometry analysis on the desired trajectory point to obtain the desired curvature of the axis of each wheelset at each moment, and converting the desired curvature into the desired rotation angle of each wheelset based on the vehicle kinematics model, as the desired motion state of each wheelset relative to the reference path.

[0060] The detailed description of the specific configuration of the timing steering control parameter parsing module 30 is as follows: As mentioned above, using the aligned timing sequence as the timing control anchor point, timing steering control parameters are parsed for the multiple axes of the equipment to obtain the steering control parameters of each axis node. The timing steering control parameter parsing module 30 may further include: a basic instruction generation unit used to generate basic instructions using the expected turning angle of each wheel group in the aligned timing sequence as the control target anchor point; and an actual turning angle difference calculation unit used to obtain the actual turning angle of each axis wheel group and calculate the actual turning angle difference between adjacent axis wheel groups. The angle difference and angle correction application unit are used to apply an angle correction in the opposite direction to the corresponding adjacent axle wheel group when the actual angle difference between adjacent axle wheel groups exceeds the corresponding angle difference limit; the load compensation correction application unit is used to obtain the actual load of each axle wheel group, and apply a load compensation correction to the corresponding angle command of the axle wheel group when the actual load of any axle wheel group deviates from the load balance threshold; the steering control parameter acquisition unit is used to superimpose the basic steering command, angle correction and load compensation correction, and obtain the steering control parameters of each axle wheel group after amplitude limiting processing.

[0061] The detailed description of the specific configuration of the multi-axle cooperative steering control module 40 is explained as follows: As mentioned above, the cooperative steering control strategy is determined by performing target cooperative verification based on the steering control parameters of each axle node. The multi-axle cooperative steering control module 40 may further include: a driving trajectory prediction unit for predicting the predicted driving trajectory of the vehicle's geometric center using the steering control parameters of all axle nodes as initial values; a deviation calculation unit for calculating the lateral tracking deviation, heading deviation, and predicted angle difference between adjacent axle wheel sets between the predicted driving trajectory and the bridge construction reference path coordinates; a correction amount generation unit for generating a global path correction amount and a global coordination correction amount when the lateral tracking deviation, heading deviation, or any predicted angle difference exceeds the corresponding allowable range, and allocating the global path correction amount and the global coordination correction amount to the corresponding axle wheel set; and an iteration unit for superimposing the global coordination correction amount and the global path correction amount onto the steering control parameters and performing multiple iterations until the angle difference of all adjacent wheel sets meets the threshold and the trajectory tracking deviation is within the allowable range, and using the iterated parameters as the final cooperative steering control strategy.

[0062] The multi-axle cooperative steering control module 40 may further include: a bridge deck boundary constraint region generation unit for generating a bridge deck boundary constraint region based on the bridge deck edge line, the guardrail edge line, or the component installation control line; and a boundary avoidance correction amount generation unit for generating a boundary avoidance correction amount and allocating the boundary avoidance correction amount to the corresponding axle wheel group when predicting the predicted driving trajectory of the vehicle's geometric center and the predicted trajectories of each axle wheel group.

[0063] The multi-axis cooperative steering control module 40 may further include: the cooperative steering control strategy includes a set of steering control parameters corresponding to at least one of the following modes: straight driving mode, curve tracking mode, and lateral movement mode, wherein the straight driving mode, curve tracking mode, and lateral movement mode are switched according to the curvature of the bridge deck construction reference path, the lateral deviation between the construction equipment and the target position, the heading deviation, and the remaining adjustment distance.

[0064] The cooperative steering control system for bridge deck construction equipment provided in this embodiment of the invention can execute the cooperative steering control method for bridge deck construction equipment provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0065] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0066] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A cooperative steering control method for bridge deck construction equipment, characterized in that, include: Establish a bridge deck sensing network, and use the bridge deck sensing network to collect and analyze bridge deck construction status data to obtain bridge deck construction reference path coordinates. Based on the bridge deck construction reference path coordinates, multi-axis trajectory tracking calculations are performed on the bridge deck construction equipment to establish an alignment time sequence for multi-axis bridge deck construction. Using the alignment timing sequence as the timing control anchor point, the timing steering control parameters of the equipment multi-axis are analyzed to obtain the steering control parameters of each axis node; Based on the steering control parameters of each axis node, target coordination verification is performed to determine the coordination steering control strategy, which is used for multi-axis coordination steering control of bridge deck construction equipment.

2. The cooperative steering control method for bridge deck construction equipment according to claim 1, characterized in that, Establish a bridge deck sensing network, including: Based on the geometric characteristics of the bridge deck construction area and the passage requirements of construction equipment, configure the spacing, array, fixing method, and marking and calibration information of the sensing nodes. According to the deployment spacing and deployment array, multiple sensing nodes are deployed in the bridge deck construction area. Each sensing node acts as a terminal node and communicates with the edge server gateway through a wireless communication protocol to establish a self-organizing bridge deck sensing network covering the entire bridge deck construction area. The sensing nodes include vibration sensors, geomagnetic sensors, strain sensors, and cameras.

3. The cooperative steering control method for bridge deck construction equipment according to claim 2, characterized in that, By collecting and analyzing bridge deck construction status data through a bridge deck sensing network, the coordinates of the bridge deck construction reference path are obtained, including: Through each sensing node of the bridge deck sensing network, local data acquisition and preprocessing are performed, including distortion correction, semantic segmentation and morphological processing of images acquired by cameras to extract the local coordinates of the ink line centerline; disturbance detection of geomagnetic sensor signals to identify the passing events of construction equipment and record timestamps; and filtering and feature extraction of vibration and strain signals. Based on the local coordinate point set of the ink line obtained from the processing, coordinate transformation is performed to generate global coordinates, and ink line segments of adjacent nodes are spliced ​​together to generate a preliminary ink line point set. The actual passing position of the construction equipment is calculated by back-calculating the geomagnetic event timestamp and node coordinates. The preliminary ink line point set is then matched with the actual passing position to calculate the lateral deviation sequence. Based on the lateral deviation sequence, the normal of the preliminary ink line point set is corrected to obtain the calibrated bridge deck construction reference path coordinate set. Based on the vibration and strain characteristics, the equivalent stiffness coefficient at each location on the bridge deck is calculated by inversion, and the equivalent stiffness coefficient is attached as an attribute to the corresponding point in the bridge deck construction reference path coordinate set. The final bridge deck construction reference path coordinates are then output, which include the three-dimensional coordinates, curvature, slope, and bridge deck stiffness coefficient of each point.

4. The cooperative steering control method for bridge deck construction equipment according to claim 1, characterized in that, Based on the bridge deck construction reference path coordinates, multi-axis trajectory tracking calculations are performed on the bridge deck construction equipment to establish an alignment time sequence for multi-axis bridge deck construction, including: The steering connection relationship between the multi-axle wheel sets of the bridge deck construction equipment is analyzed. The steering connection relationship includes at least the relative position constraints between the axes of each wheel set, the torsional stiffness constraints of the frame, and the kinematic coupling relationship of the wheel set rotation angle. Based on the continuous geometric features of the steering connection relationship and the bridge deck construction reference path coordinates, multi-axis collaborative alignment is performed to determine the expected motion state of each wheel group relative to the reference path and the differences in expected motion states between wheel groups. Based on the desired motion state and the difference between the desired motion states, an alignment time sequence is generated. The alignment time sequence is used to characterize the alignment state of each wheelset relative to the reference path at each moment during the driving process and the mutual alignment relationship between the wheelsets.

5. The cooperative steering control method for bridge deck construction equipment according to claim 4, characterized in that, Determine the desired motion state of each wheelset relative to the reference path, including: Based on the longitudinal distance between the axis of each wheel set and the geometric center of the vehicle, determine the reference point corresponding to each wheel set on the bridge construction reference path coordinates; Based on the lateral offset of each wheelset axis, the reference point is offset along the normal of the reference path to obtain the desired trajectory point of each wheelset axis. Differential geometric analysis is performed on the desired trajectory points to obtain the desired curvature of the axis of each wheelset at each time. Based on the vehicle kinematics model, the desired curvature is converted into the desired rotation angle of each wheelset, which is taken as the desired motion state of each wheelset relative to the reference path.

6. The cooperative steering control method for bridge deck construction equipment according to claim 5, characterized in that, Using the aligned timing sequence as the timing control anchor point, the timing steering control parameters of the equipment's multiple axes are analyzed to obtain the steering control parameters of each axis node, including: Using the desired rotation angle of each wheel group in the alignment timing sequence as the control target anchor point, basic instructions are generated; Obtain the actual rotation angle of each axle and wheel group, and calculate the actual rotation angle difference between adjacent axle and wheel groups; When the actual angle difference between adjacent axle and wheel sets exceeds the corresponding angle difference limit, an angle correction amount in the opposite direction is applied to the corresponding adjacent axle and wheel sets. Obtain the actual load of each axle and wheel group; when the actual load of any axle and wheel group deviates from the load balance threshold, apply a load compensation correction amount to the rotation angle command corresponding to that axle and wheel group. The basic steering command, angle correction, and load compensation correction are superimposed and then subjected to amplitude limiting to obtain the steering control parameters for each axle and wheel group.

7. The cooperative steering control method for bridge deck construction equipment according to claim 1, characterized in that, Based on the steering control parameters of each axis node, target coordination verification is performed to determine the coordinated steering control strategy, including: Using the steering control parameters of all axle nodes as initial values, predict the driving trajectory of the vehicle's geometric center; Calculate the lateral tracking deviation, heading deviation, and predicted turning angle difference between adjacent axle and wheel sets between the predicted driving trajectory and the bridge construction reference path coordinates; When the lateral tracking deviation, heading deviation, or any predicted angle difference exceeds the corresponding allowable range, a global path correction and a global coordination correction are generated, and the global path correction and global coordination correction are allocated to the corresponding axle and wheel group. The global coordination correction and global path correction are superimposed on the steering control parameters and iterated multiple times until the angle difference of all adjacent wheel sets meets the threshold and the trajectory tracking deviation is within the allowable range. The iterated parameters are then used as the final cooperative steering control strategy.

8. The cooperative steering control method for bridge deck construction equipment according to claim 7, characterized in that, Also includes: Generate the bridge deck boundary constraint area based on the bridge deck edge line, the protective wall edge line, or the component installation control line; When predicting the predicted driving trajectory of the vehicle's geometric center and the predicted trajectories of each axle and wheel group, if any predicted trajectory enters the bridge surface boundary constraint area, a boundary avoidance correction amount is generated and the boundary avoidance correction amount is allocated to the corresponding axle and wheel group.

9. The cooperative steering control method for bridge deck construction equipment according to claim 1, characterized in that, The coordinated steering control strategy includes a set of steering control parameters corresponding to at least one of the following modes: straight driving mode, curve tracking mode, and lateral movement mode. The straight driving mode, curve tracking mode, and lateral movement mode are switched according to the curvature of the bridge deck construction reference path, the lateral deviation between the construction equipment and the target position, the heading deviation, and the remaining adjustment distance.

10. A cooperative steering control system for bridge deck construction equipment, characterized in that, The system is used to implement the cooperative steering control method for bridge deck construction equipment according to any one of claims 1-9, the system comprising: The bridge deck construction status data acquisition and parsing module is used to establish a bridge deck perception network, and to acquire and parse bridge deck construction status data through the bridge deck perception network to obtain the bridge deck construction reference path coordinates. The multi-axis trajectory tracking and calculation module is used to perform multi-axis trajectory tracking and calculation on the bridge deck construction equipment based on the bridge deck construction reference path coordinates, and to establish an alignment time sequence for multi-axis bridge deck construction. The timing steering control parameter parsing module is used to parse the timing steering control parameters of the equipment multi-axis using the aligned timing sequence as the timing control anchor point, and obtain the steering control parameters of each axis node. The multi-axis cooperative steering control module is used to perform target cooperative verification based on the steering control parameters of each axis node, determine the cooperative steering control strategy, and perform multi-axis cooperative steering control of bridge deck construction equipment.

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