Method for quickly positioning and installing concrete truss floor support plate

Abstract

This invention belongs to the field of building construction, specifically relating to a method for rapid positioning and installation of concrete truss floor decking. The method includes: acquiring scanned point cloud data; constructing a digital twin model based on the scanned point cloud data and a preset building information model (BIM) to determine a virtual spatial contour representing the theoretical position of the floor decking; acquiring real-time pose data of the floor decking during hoisting, determining a first deviation, and determining a first control command to drive the floor decking to the target pose based on the first deviation; identifying the actual physical edge of the floor decking after it is initially placed on the work surface, determining a second deviation, and determining a second control command for precise position calibration of the floor decking when the second deviation exceeds a preset tolerance range; and outputting the fixed point position information of the floor decking based on the digital twin model after the floor decking is calibrated and positioned in response to the second control command. This invention significantly improves construction efficiency.

Description

Technical Field

[0001] This invention belongs to the technical field of building construction, and specifically relates to a method for rapid positioning and installation of concrete truss floor decking. Background Technology

[0002] Concrete truss floor decking is a precast component widely used in modern building structures, and its installation accuracy directly affects the safety and construction quality of the overall structure.

[0003] In related technologies, the installation of concrete truss floor decking mainly relies on manual operation. Typically, construction workers need to measure and mark the theoretical installation position of the floor decking on the work surface beforehand. During hoisting, ground command personnel guide the tower crane operator to roughly position the decking via walkie-talkie or hand gestures. After the floor decking is close to the installation position, multiple workers on the high-altitude work surface make manual fine adjustments using pry bars, pulling, and other methods until its edges are aligned with the pre-set marks.

[0004] This traditional installation method has many drawbacks: First, it is inefficient, requiring a lot of time for manual measurement, direction, and fine-tuning; second, the installation accuracy is limited, relying entirely on the experience and responsibility of the workers, and is easily affected by human factors; third, it is labor-intensive and has high safety risks, as workers manually adjusting floor decking weighing several tons at heights is extremely prone to accidents; finally, the level of digitalization and informatization in the construction process is low, making it difficult to effectively trace and manage the quality of the installation process. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, namely that the installation of floor decking in the prior art mainly relies on manual labor, resulting in low installation efficiency, poor accuracy, high labor intensity, high safety risks, and low level of informatization, this invention proposes a method for rapid positioning and installation of concrete truss floor decking in its first aspect, comprising:

[0006] Acquire scanned point cloud data of the construction site;

[0007] A digital twin model is constructed based on the scanned point cloud data and the preset building information model;

[0008] Based on the digital twin model, a virtual spatial contour is determined to characterize the theoretical location of the floor decking.

[0009] The real-time pose data of the floor decking during hoisting is obtained, the first deviation between the real-time pose data and the preset target pose in the digital twin model is determined, and the first control command to drive the floor decking to move toward the target pose is determined based on the first deviation.

[0010] After the floor decking is initially placed on the work surface, the current image data of the floor decking is acquired to identify the actual physical edge of the floor decking and determine the second deviation between the actual physical edge and the virtual space contour. When the second deviation exceeds the preset tolerance range, a second control command for precise position calibration of the floor decking is determined.

[0011] After the floor decking is calibrated and positioned in response to the second control command, the fixed point position information of the floor decking is output in conjunction with the digital twin model.

[0012] In some preferred embodiments, constructing a digital twin model based on the scanned point cloud data and a preset building information model includes:

[0013] The scanned point cloud data is subjected to noise reduction processing to extract the feature point cloud that represents the upper flange surface of the steel beam and the key support structure.

[0014] The theoretical model of the corresponding floor structure in the preset building information model is iteratively registered with the feature point cloud to obtain the rigid body transformation matrix used to align the theoretical model and the feature point cloud.

[0015] The rigid body transformation matrix is ​​applied to perform batch correction of the global coordinates of all components in the preset building information model, and the design coordinates, geometric dimensions and weight attributes of the floor deck components in the corrected model are used as initial state data to construct the digital twin model.

[0016] In some preferred embodiments, determining the virtual spatial contour for characterizing the theoretical location of the floor decking based on the digital twin model includes:

[0017] Retrieve the target floor decking component in the current hoisting sequence from the digital twin model, and obtain the local coordinates of the vertices of the polygonal outline of the target floor decking component in the design coordinate system and the coordinates of the theoretical installation positioning point of the target floor decking component in the world coordinate system;

[0018] Based on the theoretical installation positioning point coordinates and the local coordinates, the precise coordinate set of the vertices of the contour polygon in the world coordinate system is obtained by coordinate transformation;

[0019] Connect the vertices in the precise coordinate set to determine a polygonal mesh surface that matches the design shape of the target floor deck, and define the polygonal mesh surface as the virtual space outline.

[0020] In some preferred embodiments, acquiring the real-time pose data of the floor decking during hoisting includes:

[0021] The pulse signal emitted by the ultra-wideband positioning tag attached to the suspension point of the floor deck is received, and the arrival time of the pulse signal is measured by at least four positioning base stations with known coordinates.

[0022] The distance between the positioning tag and each positioning base station is calculated based on the arrival time, and the three-dimensional spatial coordinates of the positioning tag in the construction global coordinate system are solved by the least squares method.

[0023] The real-time roll angle and pitch angle measured by the tilt sensor fixed on the floor deck together constitute the six-degree-of-freedom real-time pose data of the floor deck.

[0024] In some preferred embodiments, determining the first control command to move the floor decking towards the target pose based on the first deviation includes:

[0025] The first deviation is decomposed into linear displacement deviation components along the three coordinate axes and angular displacement deviation components around the three coordinate axes.

[0026] A motion control optimization function is established with the objective of minimizing the linear displacement deviation component and the angular displacement deviation component. The motion control optimization function includes the kinematic constraints of the hoisting system.

[0027] Solve the motion control optimization function to obtain the optimal control parameter sequence. The control parameter sequence is used to indicate the desired speed or displacement setpoint for each motion degree of freedom of the hoisting equipment in the next few control cycles. The control parameter sequence constitutes the first control command.

[0028] In some preferred embodiments, acquiring current image data of the floor decking to identify the actual physical edges of the floor decking includes:

[0029] The current image data covering the floor deck is acquired by at least one image acquisition device fixed above the work surface;

[0030] Perform grayscale conversion and contrast enhancement preprocessing operations on the current image data;

[0031] The Canny edge detection operator is applied to process the preprocessed image to extract the pixel-level edge contours belonging to the floor deck area;

[0032] Based on the internal parameter matrix and external parameter matrix of the image acquisition device, the feature points in the pixel-level edge contour are mapped to the world coordinate system through inverse perspective projection transformation, generating the actual physical edge represented by a three-dimensional spatial point set.

[0033] In some preferred embodiments, determining the second control command for precise position calibration of the floor deck includes:

[0034] Based on the spatial vector of the second deviation, plan a smooth motion trajectory that allows the floor deck to translate and rotate from its current position to align with the virtual space outline;

[0035] The smooth motion trajectory is discretized into multiple sequentially executed micro-displacement steps;

[0036] For each micro-displacement step, the theoretical force direction and displacement acting on multiple calibration points at the bottom of the floor deck are calculated;

[0037] The force direction and displacement amount corresponding to all micro-displacement steps are encoded into a machine-readable instruction list in chronological order, and the instruction list is the second control instruction.

[0038] In some preferred embodiments, the step of outputting the fixed point location information of the floor decking in conjunction with the digital twin model includes:

[0039] In the digital twin model, all connection point objects that have an assembly relationship with the in-place floor decking components are traversed, and the local coordinates of each connection point object in the design coordinate system and its topological relationship relative to the floor decking body are obtained.

[0040] Based on the final actual pose fed back to the digital twin model after the floor deck is calibrated and positioned, the local coordinates of all connection points are uniformly transformed to the absolute coordinates in the world coordinate system of the construction site through rigid body transformation.

[0041] The absolute coordinates and attributes of all connection points are encapsulated into a structured data packet, and the data packet is sent to the designated construction guidance terminal for parsing and graphical representation.

[0042] In some preferred embodiments, the method further includes:

[0043] After the floor deck is calibrated and positioned in response to the second control command, the calibrated real-time pose data is finally verified against the preset target pose in the digital twin model.

[0044] If the final verification passes, the operation of outputting the fixed point location information will be triggered.

[0045] In some preferred embodiments, the method further includes:

[0046] After outputting the location information of the fixed point, a confirmation signal for the completion of construction at the fixed point is received;

[0047] Based on the confirmation signal, the status marker of the corresponding floor deck component in the digital twin model is updated to "fixed", and the construction completion timestamp and operator information are stored as metadata in the digital twin model.

[0048] The beneficial effects of this invention are:

[0049] Compared to existing technologies, this invention, by constructing a digital twin model aligned with the actual construction site, ensures that the installation position and orientation of the floor decking meet design requirements, effectively improving the overall quality of the project. Simultaneously, this invention transforms the traditional manual, sequential operation mode into an automated, parallel processing flow, significantly shortening the time from hoisting to fixing the floor decking and substantially improving construction efficiency.

[0050] On the other hand, this invention further replaces high-risk operations such as manual prying and pulling of heavy objects by high-altitude workers through automated control, reducing the number of on-site workers and high-risk operations, and greatly reducing the probability of safety accidents such as falls from heights and being struck by objects. Attached Figure Description

[0051] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0052] Figure 1 This is a flowchart illustrating a method for rapid positioning and installation of concrete truss floor decking proposed in an embodiment of the present invention.

[0053] Figure 2 This is a schematic diagram of the frame of a rapid positioning and installation system for concrete truss floor decking proposed in an embodiment of the present invention;

[0054] Figure 3 This is a schematic diagram of the structure of a computer system proposed in an embodiment of the present invention. Detailed Implementation

[0055] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0056] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0057] Please refer to Figure 1 This invention provides a method for rapid positioning and installation of concrete truss floor decking, comprising:

[0058] Step S10: Obtain scanned point cloud data of the construction site;

[0059] Step S20: Construct a digital twin model based on the scanned point cloud data and the preset building information model;

[0060] Step S30: Based on the digital twin model, determine the virtual spatial contour used to characterize the theoretical position of the floor decking;

[0061] Step S40: Obtain the real-time pose data of the floor deck during hoisting, determine the first deviation between the real-time pose data and the preset target pose in the digital twin model, and determine the first control command to drive the floor deck to move toward the target pose based on the first deviation.

[0062] Step S50: After the floor decking is initially placed on the work surface, the current image data of the floor decking is acquired to identify the actual physical edge of the floor decking and determine the second deviation between the actual physical edge and the virtual space contour. When the second deviation exceeds the preset tolerance range, a second control command for precise position calibration of the floor decking is determined.

[0063] Step S60: After the floor decking is calibrated and positioned in response to the second control command, the fixed point position information of the floor decking is output in conjunction with the digital twin model.

[0064] Specifically, this embodiment takes the construction of a concrete floor slab in a large industrial plant as an application scenario to further illustrate the specific implementation process of the rapid positioning and installation method for concrete truss floor slabs described in this embodiment.

[0065] Specifically, after the steel structure installation of the concrete floor slab is completed and accepted, the construction party can use a 3D laser scanning device to scan the floor and obtain scan point cloud data of the construction site containing the precise coordinates of the upper surfaces of all steel beams. For example, this data is transmitted to the modeling workstation deployed on site via the network.

[0066] The workstation synchronously retrieves the pre-defined building information model (BIM) for this floor from the project data center. This model includes the model number, geometric dimensions, and theoretical coordinates of all completed concrete truss floor slabs. The workstation runs dedicated modeling software that, based on the scanned point cloud data and the pre-defined BIM, executes automated coordinate alignment and model fusion algorithms to construct a digital twin model reflecting the actual spatial state of the current floor. This model serves as the unified spatial reference for all subsequent steps.

[0067] For the floor decking with the number KB-012 that is about to be installed, its design shape and theoretical installation coordinates can be read based on the digital twin model to determine its precise three-dimensional theoretical placement position and posture, and a virtual spatial outline composed of triangular mesh patches that overlaps with it can be generated. This outline data is sent to the mobile terminal of the on-site construction personnel.

[0068] Furthermore, the construction team can use a tower crane to lift the KB-012 floor decking away from the storage yard. During the lifting process, the real-time pose data (including three-dimensional coordinates and horizontal attitude angle) of the floor decking can be continuously acquired by the sensing unit preset on the floor decking. This real-time data is compared with the target pose preset for KB-012 in the digital twin model several times per second to calculate the spatial difference between the two, i.e., the first deviation.

[0069] Based on the first deviation, the system uses its built-in trajectory planning module to perform real-time calculations and generate dynamic instructions to guide the tower crane operator in making fine adjustments, serving as the first control instruction. As an example, this first control instruction can be displayed on the guidance screen in the tower crane cab as a graphical arrow and distance value, assisting the operator in hoisting the floor slab above the target steel beam area and initially positioning it.

[0070] After the KB-012 floor decking is initially placed on the steel beam work surface, a fixed-point industrial camera positioned above the work area is triggered. The camera automatically captures and uploads the current image data covering the floor decking to the system. The system runs an image analysis algorithm to process the image, identify the precise position of the floor decking edge in the image, and then, in conjunction with the camera calibration parameters, converts it into the actual physical edge in the real-world coordinate system, calculating the second deviation between the actual physical edge and the aforementioned virtual spatial contour.

[0071] For example, if an installation error of 8 mm is found at one corner of the panel, which exceeds the preset tolerance range of 5 mm, a quantitative adjustment plan is determined and sent as a second control command to the handheld device of the installer in that area, instructing him to "use the hydraulic fine-tuning jack to push the floor deck 8 mm to the north side at the northwest corner of the floor deck". The construction worker operates according to the command to complete the precise position calibration of the floor deck.

[0072] Furthermore, after the floor decking is calibrated and positioned in response to the second control command, the accurate spatial positions of all welded or bolted joints are calculated by combining the connection structure information of the floor decking of this model pre-stored in the digital twin model.

[0073] In some embodiments, this location information can be output as a visual highlight mark and overlaid on the corresponding position of the floor deck in the field of vision of the augmented reality (AR) glasses worn by the on-site technician, that is, providing the location information of the fixing points of the floor deck. At this time, the welding team of the construction party can efficiently complete the construction of all fixing points based on this intuitive guidance.

[0074] Finally, after fixing is completed, the final actual installation coordinates of the floor deck are recorded, and the status of the corresponding component in the digital twin model is updated to "installed".

[0075] Furthermore, in the above embodiments, the step of constructing a digital twin model based on the scanned point cloud data and a preset building information model includes:

[0076] The scanned point cloud data is subjected to noise reduction processing to extract the feature point cloud that represents the upper flange surface of the steel beam and the key support structure.

[0077] The theoretical model of the corresponding floor structure in the preset building information model is iteratively registered with the feature point cloud to obtain the rigid body transformation matrix used to align the theoretical model and the feature point cloud.

[0078] The rigid body transformation matrix is ​​applied to perform batch correction of the global coordinates of all components in the preset building information model, and the design coordinates, geometric dimensions and weight attributes of the floor deck components in the corrected model are used as initial state data to construct the digital twin model.

[0079] In this embodiment, the acquired raw scanned point cloud data is first preprocessed. For example, noise reduction can be performed using a statistical outlier removal algorithm to filter out discrete noise caused by dust, reflections, or moving people on site, thus obtaining a clean point cloud.

[0080] Subsequently, a region growing segmentation algorithm is applied to extract feature point clouds that can clearly characterize the planar features of the upper flange surface of the steel beam and the geometric morphology of key support structures (such as shear studs and temporary support brackets), transforming the unorganized massive point cloud into an ordered set of points representing key structural features.

[0081] Based on this, the theoretical model of the corresponding floor structure (specifically, the 3D surface model of load-bearing components such as steel beams and columns) from the preset building information model is imported into the registration module. For example, the iterative nearest neighbor (ICP) registration algorithm can be used to perform multiple rounds of iterative nearest neighbor search and pose optimization between the surface point set of the theoretical model and the feature point cloud extracted in the previous step, ultimately obtaining the optimal rigid body transformation matrix. This matrix precisely includes rotation and translation parameters and defines the correction amount required to map the theoretical model space to the actual measurement space.

[0082] Based on this, the rigid body transformation matrix is ​​applied to perform a one-time batch correction of the global coordinates of all components in the preset building information model. At this time, the theoretical positions of all components in the model are aligned with the actual coordinate system of the construction site. Then, the design coordinates, geometric dimensions, and weight attributes of each floor deck component in the corrected model are read, and this design information is firmly bound to the corrected spatial position as its initial state data in the digital twin world.

[0083] Further, in the above embodiments, determining the virtual spatial contour for characterizing the theoretical location of the floor decking based on the digital twin model includes:

[0084] Retrieve the target floor decking component in the current hoisting sequence from the digital twin model, and obtain the local coordinates of the vertices of the polygonal outline of the target floor decking component in the design coordinate system and the coordinates of the theoretical installation positioning point of the target floor decking component in the world coordinate system;

[0085] Based on the theoretical installation positioning point coordinates and the local coordinates, the precise coordinate set of the vertices of the contour polygon in the world coordinate system is obtained by coordinate transformation;

[0086] Connect the vertices in the precise coordinate set to determine a polygonal mesh surface that matches the design shape of the target floor deck, and define the polygonal mesh surface as the virtual space outline.

[0087] In this embodiment, when it is necessary to generate a positioning reference for a certain floor decking, the target floor decking component in the current hoisting sequence is first retrieved from the digital twin model. The component object is located in the model by its unique ID (such as "FL-205"), and the local coordinates of the vertices of the polygonal outline of the target floor decking component in the design coordinate system (i.e., a list of vertices in a coordinate system with the geometric center of the floor decking itself as the origin) are obtained. At the same time, the coordinates of the theoretical installation positioning point of the target floor decking component in the world coordinate system are obtained (this positioning point is usually a specific corner point or center point of the board, and its world coordinates have been determined by the correction process of the above embodiment).

[0088] Next, coordinate transformation is performed. In this embodiment, based on the spatial relationship between the theoretical installation positioning point coordinates and the local coordinates, coordinate transformation calculation is performed to transform all vertices of the outline polygon from their own local design coordinate system to the global construction site world coordinate system, thereby obtaining the precise coordinate set of these vertices in the world coordinate system.

[0089] Based on this, the vertices in the precise coordinate set are connected according to the connection order of the polygon vertices to form the boundary loop of the floor deck surface. Based on this boundary loop, a polygonal mesh surface (usually composed of triangular facets) that matches the design shape of the target floor deck is determined. This mesh surface is defined as the virtual spatial outline for subsequent real-time visual comparison and deviation calculation, and can be sent to AR devices for spatial registration and overlay display.

[0090] Further, in the above embodiments, obtaining the real-time pose data of the floor decking during hoisting includes:

[0091] The pulse signal emitted by the ultra-wideband positioning tag attached to the suspension point of the floor deck is received, and the arrival time of the pulse signal is measured by at least four positioning base stations with known coordinates.

[0092] The distance between the positioning tag and each positioning base station is calculated based on the arrival time, and the three-dimensional spatial coordinates of the positioning tag in the construction global coordinate system are solved by the least squares method.

[0093] The real-time roll angle and pitch angle measured by the tilt sensor fixed on the floor deck together constitute the six-degree-of-freedom real-time pose data of the floor deck.

[0094] In this embodiment, before the floor decking is hoisted, ultra-wideband positioning tags are firmly attached to the hoisting points of the floor decking. After the hoisting begins, the tags emit pulse signals at a high frequency (e.g., 100 times per second). At the floor construction site, several positioning base stations with known precise coordinates are pre-deployed according to an optimal geometric layout (usually a non-coplanar arrangement). These base stations synchronously receive and measure the arrival time of the pulse signals.

[0095] Based on this, spatial calculations are performed. Based on the arrival time, the distance between the positioning tag and each positioning base station can be calculated using the time difference of arrival principle. It is easy to understand that, due to measurement errors, the least squares method can be used to solve this overdetermined system of equations, thereby obtaining the three-dimensional spatial coordinates (X, Y, Z) of the positioning tag in the global construction coordinate system.

[0096] When acquiring attitude information, for example, at least one dual-axis tilt sensor can be fixed on the floor deck to measure the real-time roll and pitch angles of the floor deck plane relative to the horizontal reference. The three-dimensional spatial coordinates (X, Y, Z) calculated by UWB are fused with the (roll, pitch) data measured by the tilt sensor to form six-degree-of-freedom real-time pose data that can completely describe the position and attitude of the floor deck in space.

[0097] Further, in the above embodiments, determining the first control command to drive the floor deck to move toward the target pose based on the first deviation includes:

[0098] The first deviation is decomposed into linear displacement deviation components along the three coordinate axes and angular displacement deviation components around the three coordinate axes.

[0099] A motion control optimization function is established with the objective of minimizing the linear displacement deviation component and the angular displacement deviation component. The motion control optimization function includes the kinematic constraints of the hoisting system.

[0100] Solve the motion control optimization function to obtain the optimal control parameter sequence. The control parameter sequence is used to indicate the desired speed or displacement setpoint for each motion degree of freedom of the hoisting equipment in the next few control cycles. The control parameter sequence constitutes the first control command.

[0101] In this embodiment, after receiving the first deviation (a six-dimensional vector containing position and attitude differences), the control unit first decomposes it into linear displacement deviation components (ΔX, ΔY, ΔZ) along the three coordinate axes and angular displacement deviation components (Δα, Δβ, Δγ) around the three coordinate axes.

[0102] Next, a motion control optimization function is used to minimize the linear displacement deviation component and the angular displacement deviation component. This function includes the kinematic constraints of the hoisting system, such as the maximum speed and acceleration limits of the tower crane's hoisting, luffing, and slewing mechanisms, as well as the dynamic constraints to avoid large swings of the hoisting ropes.

[0103] Then, a real-time solution is performed. Specifically, the motion control optimization function is solved in each control cycle (e.g., 0.1 seconds) to obtain the optimal sequence of control parameters in a future time window (e.g., the next 2 seconds). This sequence of control parameters is specifically used to indicate the desired speed or displacement setpoints for each degree of freedom of the hoisting equipment in the next few control cycles, forming the first control command sent to the tower crane semi-automatic guidance system or displayed to the operator.

[0104] Further, in the above embodiments, acquiring the current image data of the floor decking to identify the actual physical edges of the floor decking includes:

[0105] The current image data covering the floor deck is acquired by at least one image acquisition device fixed above the work surface;

[0106] Perform grayscale conversion and contrast enhancement preprocessing operations on the current image data;

[0107] The Canny edge detection operator is applied to process the preprocessed image to extract the pixel-level edge contours belonging to the floor deck area;

[0108] Based on the internal parameter matrix and external parameter matrix of the image acquisition device, the feature points in the pixel-level edge contour are mapped to the world coordinate system through inverse perspective projection transformation, generating the actual physical edge represented by a three-dimensional spatial point set.

[0109] In this embodiment, after the floor decking is initially in place, at least one image acquisition device (such as a high-resolution industrial camera) fixed above the work surface acquires the current image data covering the floor decking from a preset optimal viewing angle.

[0110] Subsequently, image preprocessing is performed, such as grayscale conversion and contrast enhancement preprocessing on the original color or grayscale image, to enhance the grayscale difference between the edge of the floor deck and the background steel beam and suppress the effect of uneven lighting.

[0111] Then, edge extraction is performed. For example, the Canny edge detection operator can be applied to process the preprocessed image. This operator can robustly extract the pixel-level edge contours belonging to the floor deck area by calculating the image gradient, non-maximum suppression, and double threshold detection, that is, the boundary line between the floor deck and the surrounding environment in the image.

[0112] Finally, based on the pre-calibrated internal parameter matrix (including focal length, principal point, and distortion coefficient) and external parameter matrix (the position and orientation of the camera in the world coordinate system) of the image acquisition device, the feature points in the pixel-level edge contour obtained in the previous step are back-projected from the two-dimensional image plane to the three-dimensional space through the inverse perspective projection transformation, generating the actual physical edge represented by a series of three-dimensional coordinate points.

[0113] Further, in the above embodiments, determining the second control command for precisely calibrating the position of the floor deck includes:

[0114] Based on the spatial vector of the second deviation, plan a smooth motion trajectory that allows the floor deck to translate and rotate from its current position to align with the virtual space outline;

[0115] The smooth motion trajectory is discretized into multiple sequentially executed micro-displacement steps;

[0116] For each micro-displacement step, the theoretical force direction and displacement acting on multiple calibration points at the bottom of the floor deck are calculated;

[0117] The force direction and displacement amount corresponding to all micro-displacement steps are encoded into a machine-readable instruction list in chronological order, and the instruction list is the second control instruction.

[0118] In this embodiment, after determining the second deviation, a smooth motion trajectory is first planned based on the spatial vector of the second deviation (including translation and rotation components) to make the floor deck translate and rotate from its current position to align with the virtual space contour, so as to ensure a smooth adjustment process and avoid secondary disturbances.

[0119] The continuous smooth trajectory described above is discretized into multiple sequentially executed micro-displacement steps (e.g., 10 steps), each step containing a small displacement and rotation.

[0120] For each micro-displacement step, based on the rigid kinematics model of the floor deck and the preset positions of the fine-tuning action points (e.g., hydraulic fine-tuners arranged at the three corners of the bottom of the floor deck), the theoretical force direction and displacement acting on multiple calibration action points at the bottom of the floor deck are calculated in reverse to ensure that the floor deck moves along the predetermined trajectory.

[0121] Finally, the force direction and displacement amount corresponding to all micro-displacement steps are encoded into a machine-readable instruction list in chronological order. For example, the list format could be: [Step 1: Point A extends by 0.5mm; Point B retracts by 0.2mm; ...]. This instruction list is the second control instruction that can directly drive automated fine-tuning equipment to execute or guide manual precision operations.

[0122] Further, in the above embodiments, the step of outputting the fixed point location information of the floor decking in conjunction with the digital twin model includes:

[0123] In the digital twin model, all connection point objects that have an assembly relationship with the in-place floor decking components are traversed, and the local coordinates of each connection point object in the design coordinate system and its topological relationship relative to the floor decking body are obtained.

[0124] Based on the final actual pose fed back to the digital twin model after the floor deck is calibrated and positioned, the local coordinates of all connection points are uniformly transformed to the absolute coordinates in the world coordinate system of the construction site through rigid body transformation.

[0125] The absolute coordinates and attributes of all connection points are encapsulated into a structured data packet, and the data packet is sent to the designated construction guidance terminal for parsing and graphical representation.

[0126] In this embodiment, after the floor decking is calibrated and in place, the digital twin model traverses all connection point objects (such as the data object of each stud or weld point) that have an assembly relationship with the floor decking component that is in place, and obtains the local coordinates of each connection point object in the design coordinate system and its topological relationship relative to the floor decking body (for example, located at the center of the lower chord of the second truss node from the west side, 150mm from the edge of the plate).

[0127] Next, coordinate transformation is performed. Based on the final actual pose (precise six-degree-of-freedom pose) fed back to the digital twin model after the floor deck is calibrated and positioned, rigid body transformation (applying the rotation matrix and translation vector corresponding to the pose) is used to uniformly transform the local coordinates of all connection points to the absolute coordinates in the world coordinate system of the construction site.

[0128] Finally, the absolute coordinates and attributes (such as type M16 stud) of all connection points are encapsulated into a structured data packet (such as JSON format), and the data packet is sent to a designated construction guidance terminal (such as AR glasses or a tablet computer). After receiving the packet, the terminal parses and graphically displays it, for example, rendering a virtual icon of a specific color and shape (such as a flashing red ring) at the corresponding coordinates in three-dimensional space, thus clearly and intuitively outputting the fixed point location information to the construction personnel.

[0129] Furthermore, in the above embodiments, the method further includes:

[0130] After the floor deck is calibrated and positioned in response to the second control command, the calibrated real-time pose data is finally verified against the preset target pose in the digital twin model.

[0131] If the final verification passes, the operation of outputting the fixed point location information will be triggered.

[0132] In this embodiment, after the floor deck is calibrated and positioned in response to the second control command, a verification procedure is initiated. The real-time pose data after calibration is collected by a positioning sensor or vision method, and then the data is finally verified against the preset target pose in the digital twin model.

[0133] In some preferred embodiments, this verification employs a final acceptance criterion (e.g., ±3 mm) that is more stringent than the initial tolerance.

[0134] If the final verification passes, it indicates that the installation accuracy of the floor decking fully meets the design requirements, triggering the output of the fixed point position information. If the verification fails, the residual deviation is recorded, and the fine-tuning command can be regenerated or an alarm can be triggered for manual review. This ensures that only components with fully compliant accuracy will proceed to the final fixing process, guaranteeing construction quality from a process perspective.

[0135] Furthermore, in the above embodiments, the method further includes:

[0136] After outputting the location information of the fixed point, a confirmation signal for the completion of construction at the fixed point is received;

[0137] Based on the confirmation signal, the status marker of the corresponding floor deck component in the digital twin model is updated to "fixed", and the construction completion timestamp and operator information are stored as metadata in the digital twin model.

[0138] In this embodiment, after the location information of the fixing point is output, the welding or bolting operation is completed. The construction supervisor clicks the confirmation button on the terminal interface and then receives a confirmation signal confirming the completion of the construction for the fixing point.

[0139] Based on the confirmation signal, the status marker of the corresponding floor deck component in the digital twin model is first updated from "in place" to "fixed". Simultaneously, the timestamp of the completion of this operation and the operator information are stored as metadata, linked with the design information and actual installation posture data of the floor deck component, in the database of the digital twin model.

[0140] Furthermore, please refer to Figure 2 The second embodiment of the present invention proposes a rapid positioning and installation system for concrete truss floor slabs, comprising:

[0141] The data acquisition module 210 is used to acquire scanned point cloud data of the construction site;

[0142] The model building module 220 is used to build a digital twin model based on the scanned point cloud data and the preset building information model;

[0143] The first processing module 230 is used to determine a virtual spatial outline representing the theoretical position of the floor decking based on the digital twin model.

[0144] The second processing module 240 is used to acquire the real-time pose data of the floor deck during the hoisting process, determine the first deviation between the real-time pose data and the preset target pose in the digital twin model, and determine the first control command to drive the floor deck to move toward the target pose based on the first deviation.

[0145] The third processing module 250 is used to acquire the current image data of the floor deck after the floor deck is initially placed on the work surface, so as to identify the actual physical edge of the floor deck, determine the second deviation between the actual physical edge and the virtual space outline, and determine the second control command for precise position calibration of the floor deck when the second deviation exceeds the preset tolerance range.

[0146] The data output module 260 is used to output the fixed point position information of the floor deck after the floor deck is calibrated and positioned in response to the second control command, in conjunction with the digital twin model.

[0147] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the system described above can be found in the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0148] The following is for reference. Figure 3 It shows a schematic diagram of the structure of a computer system suitable for implementing the system and method embodiments of the present invention. Figure 3 The server shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0149] like Figure 3 As shown, the computer system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on programs stored in Read Only Memory (ROM) 302 or programs loaded from storage section 308 into Random Access Memory (RAM) 303. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0150] The following components are connected to the input / output interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the input / output interface 305 as needed. A removable medium 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 310 as needed so that computer programs read from it can be installed into the storage section 308 as needed.

[0151] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit 301, it performs the functions defined in the methods of the present invention. It should be noted that the computer-readable medium described above in the present invention can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.

[0152] More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, portable compact disk read-only memory, optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can transmit, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0153] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including local area networks (LANs) or wide area networks (WANs), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0154] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0155] The terms “first”, “second”, etc., are used to distinguish similar objects, not to describe or indicate a specific order or sequence.

[0156] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent in such process, method, article, or apparatus / device.

[0157] The technical solution of the present invention has now been described in conjunction with the preferred embodiments shown in the accompanying drawings.

[0158] The above description is merely an embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the present invention should be included within the scope of the claims of the present invention.

Claims

1. A method for rapid positioning and installation of concrete truss floor decking, characterized in that, include: Acquire scanned point cloud data of the construction site; A digital twin model is constructed based on the scanned point cloud data and the preset building information model; Based on the digital twin model, a virtual spatial contour is determined to characterize the theoretical position of the floor decking. The target floor decking component in the current hoisting sequence is retrieved from the digital twin model, and the local coordinates of the polygonal vertices of the target floor decking component in the design coordinate system and the coordinates of the theoretical installation positioning point of the target floor decking component in the world coordinate system are obtained. Based on the coordinates of the theoretical installation positioning point and the local coordinates, the precise coordinate set of the polygonal vertices in the world coordinate system is calculated through coordinate transformation. The vertices in the precise coordinate set are connected to determine a polygonal mesh surface consistent with the designed shape of the target floor decking, and this polygonal mesh surface is defined as the virtual spatial contour. The real-time pose data of the floor decking during hoisting is obtained, the first deviation between the real-time pose data and the preset target pose in the digital twin model is determined, and the first control command to drive the floor decking to move toward the target pose is determined based on the first deviation. After the floor decking is initially placed on the work surface, the current image data of the floor decking is acquired to identify the actual physical edge of the floor decking, determine the second deviation between the actual physical edge and the virtual space contour, and determine a second control command for precise position calibration of the floor decking when the second deviation exceeds the preset tolerance range. After the floor decking is calibrated and positioned in response to the second control command, the fixed point position information of the floor decking is output in conjunction with the digital twin model.

2. The method according to claim 1, characterized in that, The step of constructing a digital twin model based on the scanned point cloud data and a preset building information model includes: The scanned point cloud data is subjected to noise reduction processing to extract the feature point cloud that represents the upper flange surface of the steel beam and the key support structure. The theoretical model of the corresponding floor structure in the preset building information model is iteratively registered with the feature point cloud to obtain the rigid body transformation matrix used to align the theoretical model and the feature point cloud. The rigid body transformation matrix is ​​applied to perform batch correction of the global coordinates of all components in the preset building information model, and the design coordinates, geometric dimensions and weight attributes of the floor deck components in the corrected model are used as initial state data to construct the digital twin model.

3. The method according to claim 1, characterized in that, The acquisition of real-time position and orientation data of the floor decking during hoisting includes: The pulse signal emitted by the ultra-wideband positioning tag attached to the suspension point of the floor deck is received, and the arrival time of the pulse signal is measured by at least four positioning base stations with known coordinates. The distance between the positioning tag and each positioning base station is calculated based on the arrival time, and the three-dimensional spatial coordinates of the positioning tag in the construction global coordinate system are solved by the least squares method. The real-time roll angle and pitch angle measured by the tilt sensor fixed on the floor deck together constitute the six-degree-of-freedom real-time pose data of the floor deck.

4. The method according to claim 1 or 3, characterized in that, The first control command for moving the floor deck towards the target pose based on the first deviation includes: The first deviation is decomposed into linear displacement deviation components along the three coordinate axes and angular displacement deviation components around the three coordinate axes. A motion control optimization function is established with the objective of minimizing the linear displacement deviation component and the angular displacement deviation component. The motion control optimization function includes the kinematic constraints of the hoisting system. Solve the motion control optimization function to obtain the optimal control parameter sequence. The control parameter sequence is used to indicate the desired speed or displacement setpoint for each motion degree of freedom of the hoisting equipment in the next few control cycles. The control parameter sequence constitutes the first control command.

5. The method according to claim 1, characterized in that, The step of acquiring the current image data of the floor decking to identify the actual physical edges of the floor decking includes: The current image data covering the floor deck is acquired by at least one image acquisition device fixed above the work surface; Perform grayscale conversion and contrast enhancement preprocessing operations on the current image data; The Canny edge detection operator is applied to process the preprocessed image to extract the pixel-level edge contours belonging to the floor deck area; Based on the internal parameter matrix and external parameter matrix of the image acquisition device, the feature points in the pixel-level edge contour are mapped to the world coordinate system through inverse perspective projection transformation, generating the actual physical edge represented by a three-dimensional spatial point set.

6. The method according to claim 1, characterized in that, The determination of the second control command for precise position calibration of the floor deck includes: Based on the spatial vector of the second deviation, plan a smooth motion trajectory that allows the floor deck to translate and rotate from its current position to align with the virtual space outline; The smooth motion trajectory is discretized into multiple sequentially executed micro-displacement steps; For each micro-displacement step, the theoretical force direction and displacement acting on multiple calibration points at the bottom of the floor deck are calculated; The force direction and displacement amount corresponding to all micro-displacement steps are encoded into a machine-readable instruction list in chronological order, and the instruction list is the second control instruction.

7. The method according to claim 1, characterized in that, The step of combining the digital twin model to output the fixed point location information of the floor decking includes: In the digital twin model, all connection point objects that have an assembly relationship with the in-place floor decking components are traversed, and the local coordinates of each connection point object in the design coordinate system and its topological relationship relative to the floor decking body are obtained. Based on the final actual pose fed back to the digital twin model after the floor deck is calibrated and positioned, the local coordinates of all connection points are uniformly transformed to the absolute coordinates in the world coordinate system of the construction site through rigid body transformation. The absolute coordinates and attributes of all connection points are encapsulated into a structured data packet, and the data packet is sent to the designated construction guidance terminal for parsing and graphical representation.

8. The method according to claim 1, characterized in that, The method further includes: After the floor deck is calibrated and positioned in response to the second control command, the calibrated real-time pose data is finally verified against the preset target pose in the digital twin model. If the final verification passes, the operation of outputting the fixed point location information will be triggered.

9. The method according to claim 1, characterized in that, The method further includes: After outputting the location information of the fixed point, a confirmation signal for the completion of construction at the fixed point is received; Based on the confirmation signal, the status marker of the corresponding floor deck component in the digital twin model is updated to "fixed", and the construction completion timestamp and operator information are stored as metadata in the digital twin model.

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