Precise component hoisting method and system based on heterogeneous sensing cooperative sensing

Abstract

The embodiment of the invention provides a component precision hoisting method and system based on heterogeneous sensing cooperative perception, and the method comprises the steps: obtaining original acceleration information and original angular velocity information of a component through an inertial measurement unit arranged at a preset key position of the component; performing data preprocessing and filtering attitude operation on the original acceleration information and the original angular velocity information to obtain component velocity information, component position information and attitude angle information; on the basis of the component speed information, the component position information and the attitude angle information, motion trend prediction is carried out through a predetermined motion trend prediction model, and the inclination trend of the component is determined; and based on the inclination trend and the spatial distance information of the component, the hoisting positioning equipment is controlled to adjust the position of the component, so that the adjusted component is aligned to a preset mounting position, and component assembling is completed. According to the scheme, the component hoisting and positioning efficiency and precision can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of civil engineering, and in particular to a component precision hoisting method and system based on heterogeneous sensor collaborative perception. BACKGROUND

[0002] In fabricated building construction, precise positioning of hoisted prefabricated components has a key influence on construction efficiency and safety. Most current hoisting processes rely on manual visual coordination or image recognition methods for posture judgment and position alignment. Traditional hoisting auxiliary positioning mostly uses visual recognition systems to judge target positions, identifies the edges of hoisted components through cameras, and then adjusts the posture by operators or programs controlling motors. However, such methods are affected by factors such as environmental lighting, obstructions, and complex hoisted component structures, resulting in poor positioning stability, low precision, low efficiency, and frequent manual intervention. SUMMARY

[0003] Embodiments of the present application aim to provide a component precision hoisting method and system based on heterogeneous sensor collaborative perception, which can improve the efficiency and precision of component hoisting positioning.

[0004] The technical solution of the present application is implemented as follows: In a first aspect, the embodiments of the present application provide a component precision hoisting method based on heterogeneous sensor collaborative perception, which comprises: Obtaining posture information of a component through an inertial measurement unit arranged at a preset key position of the component; wherein the posture information includes original acceleration information and original angular velocity information; Performing data preprocessing and filtering posture operation on the original acceleration information and the original angular velocity information to obtain component velocity information, component position information, and attitude angle information; Based on the component velocity information, the component position information, and the attitude angle information, performing motion trend prediction through a pre-determined motion trend prediction model to determine the tilting trend of the component; Based on the tilting trend of the component and the spatial distance information, controlling a hoisting positioning device to adjust the position of the component, so that the adjusted component is aligned with a preset installation position, and component assembly is completed; wherein the spatial distance information is the spatial distance between the component and a target positioning point measured by a laser radar system.

[0005] In the above solution, the data preprocessing and filtering posture operation on the original acceleration information and the original angular velocity information to obtain component velocity information, component position information, and attitude angle information comprises: Performing data preprocessing on the original acceleration information and the original angular velocity information to obtain acceleration information and angular velocity information; Filtering attitude operation is performed on the acceleration information and the angular velocity information to obtain the member speed information, the member position information and the attitude angle information.

[0006] In the above scheme, the data preprocessing on the original acceleration information and the original angular velocity information to obtain the acceleration information and the angular velocity information comprises: Respectively performing data conversion on the original acceleration information and the original angular velocity information to obtain converted original acceleration information and converted original angular velocity information; Respectively performing error correction on the converted original acceleration information and the converted original angular velocity information through a predetermined error model to obtain corrected original acceleration information and corrected original angular velocity information; Respectively performing denoising, coordinate transformation and gravity correction on the corrected original acceleration information and the corrected original angular velocity information to obtain the acceleration information and the angular velocity information.

[0007] In the above scheme, the denoising, coordinate transformation and gravity correction on the corrected original acceleration information and the corrected original angular velocity information to obtain the acceleration information and the angular velocity information comprises: Respectively performing denoising on the corrected original acceleration information and the corrected original angular velocity information to obtain first acceleration information and first angular velocity information; Aligning an inertial measurement device coordinate system corresponding to the first acceleration information and the first angular velocity information with a motion carrier coordinate system determined by the member, and converting the first acceleration information and the first angular velocity information in the inertial measurement device coordinate system into information data in a global coordinate system through an Euler angle method; Performing gravity correction on the information data to obtain the acceleration information and the angular velocity information.

[0008] In the above scheme, the filtering attitude operation on the acceleration information and the angular velocity information to obtain the member speed information, the member position information and the attitude angle information comprises: Performing Kalman filtering processing on the acceleration information and the angular velocity information to obtain processed acceleration information and processed angular velocity information; Performing attitude solving and integral operation on the processed acceleration information and the processed angular velocity information through a predetermined three-dimensional trajectory window and a quaternion attitude solving model to obtain the member speed information, the member position information and the attitude angle information.

[0009] In the scheme, the inclination trend of the component is determined by predicting the motion trend of the component based on the component speed information, the component position information and the attitude angle information through a pre-determined motion trend prediction model, including: The load distribution information of the lifting point is obtained through the tension sensor arranged on each lifting point. The load distribution information of the lifting point is data time-aligned with the component speed information, the component position information and the attitude angle information to obtain the to-be-predicted motion information. The inclination trend of the component is determined by predicting the motion trend of the component based on the to-be-predicted motion information through the motion trend prediction model.

[0010] In the scheme, the position of the component is adjusted by the hoisting positioning device based on the inclination trend of the component and the spatial distance information, so that the adjusted component is aligned with the pre-set installation position to complete the component assembly, including: The position of the component is adjusted by the hoisting positioning device based on the inclination trend of the component and the spatial distance information to obtain the adjusted component position. The distance error is obtained by calculating the distance between the adjusted component position and the target positioning point. If the distance error is within the pre-set distance error range, the component is aligned with the pre-set installation position based on the adjusted component position to complete the component assembly. If the distance error is not within the pre-set distance error range, the component position is adjusted until the distance error between the adjusted component position and the target positioning point is within the pre-set distance error range, and the component is aligned with the pre-set installation position based on the adjusted component position to complete the component assembly.

[0011] In a second aspect, the embodiments of the present application provide a component precision hoisting system based on heterogeneous sensor collaborative perception, which comprises an acquisition module, an operation module, a determination module and a control module, wherein The acquisition module is configured to acquire attitude information of a component through an inertial measurement unit arranged at a pre-set key position of the component, wherein the attitude information comprises original acceleration information and original angular velocity information. The operation module is configured to perform data preprocessing and filtering attitude operation on the original acceleration information and the original angular velocity information to obtain component speed information, component position information and attitude angle information. The determination module is configured to determine the inclination trend of the component by predicting the motion trend of the component based on the component speed information, the component position information and the attitude angle information through a pre-determined motion trend prediction model. The control module is configured to control a hoisting positioning device to adjust the position of the component based on the inclination trend of the component and the spatial distance information, so that the adjusted component is aligned with a preset installation position, and component assembly is completed.

[0012] In a third aspect, an embodiment of the present application provides a component precision hoisting device based on heterogeneous sensor collaborative perception, including a processor and a memory. The memory is configured to store a computer program. The processor is configured to call and run the computer program from the memory to execute the method of the first aspect.

[0013] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium storing executable instructions for causing a processor to execute the method of the first aspect.

[0014] The embodiment of the present application provides a component precision hoisting method and system based on heterogeneous sensor collaborative perception. The method comprises the following steps: acquiring attitude information of a component through an inertial measurement unit arranged at a preset key position of the component; wherein the attitude information comprises original acceleration information and original angular velocity information; performing data preprocessing and filtering attitude operation on the original acceleration information and the original angular velocity information to obtain component speed information, component position information and attitude angle information; performing motion trend prediction based on the component speed information, the component position information and the attitude angle information through a pre-determined motion trend prediction model to determine an inclination trend of the component; controlling a hoisting positioning device to adjust the position of the component based on the inclination trend of the component and the spatial distance information, so that the adjusted component is aligned with a preset installation position, and component assembly is completed; wherein the spatial distance information is a spatial distance between the component and a target positioning point measured by a laser radar system. In the above scheme, the attitude and position of the hoisted component can be accurately positioned, the positioning accuracy of the component in the hoisting process is improved, and the component assembly can be accurately and efficiently completed, that is, the efficiency and accuracy of the component hoisting positioning are improved, and the construction efficiency and quality of the prefabricated building are improved. BRIEF DESCRIPTION OF DRAWINGS

[0015] The drawings incorporated into the specification and forming a part of the specification, show embodiments consistent with the present application, and together with the specification, serve to explain the technical solutions of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0016] The flowchart shown in the drawings is only an exemplary illustration, and is not necessarily required to include all contents and operations / steps, nor is it necessarily required to be executed in the order described. For example, some operations / steps can be further divided, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to actual conditions.

[0017] Figure 1 An optional flowchart of a component precision hoisting method based on heterogeneous sensor collaborative perception provided by an embodiment of the present application; Figure 2 An optional Euler angle diagram of a component precision hoisting method based on heterogeneous sensor collaborative perception provided by an embodiment of the present application; Figure 3 A three-dimensional trajectory window diagram of a component precision hoisting method based on heterogeneous sensor collaborative perception provided by an embodiment of the present application; Figure 4 A dynamic trajectory three-dimensional monitoring diagram of a component precision hoisting method based on heterogeneous sensor collaborative perception provided by an embodiment of the present application; Figure 5 A structural diagram of a component precision hoisting system based on heterogeneous sensor collaborative perception provided by an embodiment of the present application; Figure 6 A structural diagram of a component precision hoisting device based on heterogeneous sensor collaborative perception provided by an embodiment of the present application. DETAILED DESCRIPTION

[0018] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the specific technical scheme of the present application will be further described in detail below with reference to the drawings in the embodiments of the present application. The following embodiments are used to illustrate the present application, but are not used to limit the scope of the present application.

[0019] Unless otherwise defined, all technical and scientific terms used in the present application have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used in the present application are only for the purpose of describing the embodiments of the present application, and are not intended to limit the present application.

[0020] In the following description, “some embodiments”, “the embodiment”, “the embodiments of the present application” and the like are described, which describe a subset of all possible embodiments, but it can be understood that “some embodiments” can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0021] If the application file contains similar descriptions of "first / second", the following description is added: in the following description, the terms "first / second / third" involved only distinguish similar objects, and do not represent a specific order of the objects. Understandably, "first / second / third" can be interchanged in a specific order or sequence as allowed, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein.

[0022] The embodiment of the application provides a component precision hoisting method based on heterogeneous sensing cooperative perception, Figure 1 An optional flowchart of a component precision hoisting method based on heterogeneous sensing cooperative perception provided by the embodiment of the application will be described by combining Figure 1 The steps shown will be described.

[0023] S101, acquiring attitude information of the component through an inertial measurement unit arranged at a preset key position of the component; wherein the attitude information comprises original acceleration information and original angular velocity information.

[0024] In some embodiments of the application, the inertial measurement unit (IMU) is usually composed of a three-axis gyroscope, a three-axis accelerometer and a data processing calculation unit, and the inertial measurement unit of the application only uses accelerometer and gyroscope data.

[0025] For example, the IMU model can be MPU6050, and the module composition of the IMU takes MPU-6050 chip as the core, integrates three-axis accelerometer and three-axis gyroscope, and can respectively perceive acceleration and angular velocity information in X, Y and Z axis directions. Through accurate collection of motion parameters of each axis in three-dimensional space, the attitude change of the carrier can be captured in real time. The model of the IMU is not limited in the embodiment of the application.

[0026] In some embodiments of the application, the component precision hoisting method based on heterogeneous sensing cooperative perception is suitable for a building construction scene.

[0027] In some embodiments of the application, the component precision hoisting method based on heterogeneous sensing cooperative perception is suitable for a component precision hoisting system based on heterogeneous sensing cooperative perception.

[0028] In some embodiments of the application, the attitude information of the component is acquired through an inertial measurement unit arranged at a preset key position of the component; wherein the attitude information comprises original acceleration information and original angular velocity information.

[0029] Exemplarily, the preset key positions of the component can be a lifting point position, a component center position, and a component edge positioning point position. For example, the component center position: an IMU is arranged near the center of mass of the component or embedded in the component, and the pitch angle, roll angle, and yaw angle are monitored in real time. The lifting point position: a tension sensor is arranged at the lifting ring or lifting lug of each hoisted component, and the force state of each lifting point is obtained in real time. The component edge positioning point position: a laser radar is used to scan the target structure in real time at the edge position close to the installation interface or assembly node, and the relative distance and spatial deviation are measured.

[0030] It should be noted that the unit of the acceleration data and the unit of the angular velocity data output by the MPU6050 by default are raw data, and the range is-32768~32767.

[0031] S102, data preprocessing and filtering attitude operation are performed on the original acceleration information and the original angular velocity information to obtain component speed information, component position information, and attitude angle information.

[0032] In some embodiments of the present application, data preprocessing is performed on the original acceleration information and the original angular velocity information to obtain acceleration information and angular velocity information; filtering attitude operation is performed on the acceleration information and the angular velocity information to obtain component speed information, component position information, and attitude angle information.

[0033] In some embodiments of the present application, data conversion is respectively performed on the original acceleration information and the original angular velocity information to obtain converted original acceleration information and converted original angular velocity information; error correction is respectively performed on the converted original acceleration information and the converted original angular velocity information through a pre-determined error model to obtain corrected original acceleration information and corrected original angular velocity information; denoising, coordinate transformation, and gravity correction are respectively performed on the corrected original acceleration information and the corrected original angular velocity information to obtain acceleration information and angular velocity information. Filtering attitude operation is performed on the acceleration information and the angular velocity information to obtain component speed information, component position information, and attitude angle information.

[0034] S103, based on the component speed information, the component position information, and the attitude angle information, motion trend prediction is performed through a pre-determined motion trend prediction model to determine the inclination trend of the component.

[0035] In some embodiments of the present application, the tension sensor arranged on each lifting point is used to obtain the lifting point load distribution information; the lifting point load distribution information, the component speed information, the component position information, and the attitude angle information are time-aligned to obtain the to-be-predicted motion information; based on the to-be-predicted motion information, the motion trend prediction model is used to perform motion trend prediction on the component to determine the inclination trend of the component.

[0036] S104, based on the inclination trend of the component and the spatial distance information, controlling the hoisting positioning device to adjust the position of the component, aligning the adjusted component with the preset installation position, and completing the component assembly; wherein the spatial distance information is the spatial distance between the component and the target positioning point measured by the laser radar system.

[0037] In some embodiments of the present application, the spatial distance information is the spatial distance between the component and the target positioning point measured by the laser radar system. The relative spatial distance between the component and the target positioning point is measured by the laser radar system to obtain the spatial distance information. In this way, millimeter-level high-precision ranging can be achieved.

[0038] In some embodiments of the present application, based on the inclination trend of the component and the spatial distance information, the hoisting positioning device is controlled to adjust the position of the component to obtain the adjusted component position; the distance between the adjusted component position and the target positioning point is calculated to obtain the distance error; if the distance error is within the preset distance error range, the component is aligned with the preset installation position based on the adjusted component position to complete the component assembly; if the distance error is not within the preset distance error range, the component position is adjusted until the distance error between the adjusted component position and the target positioning point is within the preset distance error range, and the component is aligned with the preset installation position based on the adjusted component position to complete the component assembly.

[0039] It can be understood that, by means of the inertial measurement unit, the attitude information can be obtained, the attitude information data can be pre-processed and filtered, and the attitude operation can be performed to obtain the component speed information, the component position information and the attitude angle information, so that the attitude and position of the hoisted component can be accurately positioned, the positioning accuracy of the component in the hoisting process is improved, and the component assembly can be accurately and efficiently completed, that is, the efficiency and accuracy of the component hoisting positioning are improved, and the construction efficiency and quality of the fabricated building are improved.

[0040] In some embodiments of the present application, S102 can be implemented by S201 and S202 as follows: S201, pre-processing the original acceleration information and the original angular velocity information to obtain the acceleration information and the angular velocity information.

[0041] In some embodiments of the present application, the original acceleration information and the original angular velocity information are respectively converted to obtain the converted original acceleration information and the converted original angular velocity information; the converted original acceleration information and the converted original angular velocity information are respectively corrected by the pre-determined error model to obtain the corrected original acceleration information and the corrected original angular velocity information; the corrected original acceleration information and the corrected original angular velocity information are respectively denoised, coordinate-transformed and gravity-corrected to obtain the acceleration information and the angular velocity information.

[0042] Exemplary, acceleration and angular velocity conversion formula as follows: 1. Acceleration (m / s 2 ) MPU6050 default output acceleration data unit is raw data, range is -32768~32767. Default configuration is ±2g, 1g = 9.8m / s 2 , conversion formula as follows: Acceleration (m / s 2 ) = raw acceleration data * 9.8 2. Angular velocity (rad / s) MPU6050 default output angular velocity data unit is raw data, range is -32768~32767. Default configuration is ±250" / S, conversion formula as follows: Angular velocity (rad / s) = (raw angular velocity data / 131)*(pi / 180) It should be noted that the raw acceleration data, that is, the original acceleration information; raw angular velocity data, that is, the original angular velocity information. Acceleration and angular velocity are converted original acceleration information and converted original angular velocity information.

[0043] The main sources of IMU positioning error are: first, the attitude deviation causes the influence of gravity, and the error is difficult to eliminate; second, the element itself drifts, for example, when the accelerometer is from static to motion and then restores to static, the integrated speed should be 0 in theory, but the actual measurement result is not. This application focuses on the error modeling analysis of accelerometer and gyroscope.

[0044] The error of accelerometer and gyroscope can be divided into deterministic error and random error. Among them, the deterministic error includes scale factor, non-orthogonal error, nonlinear error, etc.; the random error mainly covers Gaussian white noise error, random walk noise error. The measurement models of the two are as follows: Measurement model of accelerometer: a o = Taka (a s + b a + v a ) Measurement model of gyroscope: w o = Tskg(w s + b g + v g ) Wherein, a o , w o is the output value of accelerometer and gyroscope after error compensation, a s , ws are true values, ka, kg are scale factors, Ta, Ts are transformation matrices caused by non-orthogonal errors, b a , b g are biases of the accelerometer and the gyroscope, v a , v g represents measurement noise.

[0045] The scale factors and the non-orthogonal transformation matrices belong to deterministic errors, and the related parameters are provided by the manufacturer when the sensors are shipped. After removing the deterministic errors, only random errors are reserved. Taking the gyroscope as an example, the error model is reconstructed as follows: w o = w s + b g + n g where n g is a measurement Gaussian white noise error, and b g is a bias random walk error.

[0046] In some embodiments of the present application, the corrected original acceleration information and the corrected original angular velocity information are respectively denoised to obtain first acceleration information and first angular velocity information; the inertial measurement device coordinate system corresponding to the first acceleration information and the first angular velocity information is aligned with the motion carrier coordinate system determined by the component; and the first acceleration information and the first angular velocity information under the inertial measurement device coordinate system are converted into information data under a global coordinate system by an Euler angle method; and the information data is subjected to gravity correction to obtain acceleration information and angular velocity information.

[0047] In some embodiments of the present application, three coordinate systems are involved. They are a global coordinate system, a carrier coordinate system and an inertial measurement device coordinate system.

[0048] 1. Global coordinate system o n x n y n z n (n system) The northeast celestial coordinate system is selected as the global coordinate system, which is defined as follows: the origin o n is located at a reference point on the earth's surface, the x n axis points to the east direction, the y n axis points to the north direction, and the z n axis points to the zenith direction. All navigation positioning calculation results need to be finally converted to this coordinate system.

[0049] 2. Carrier coordinate system o b x b y b z b (b system) The carrier coordinate system takes the center of mass of the motion carrier as the origin ob The coordinate axes are defined as: x b The axis points directly in front of the component, y b The axis points to the left side of the component, z b The axis points towards the zenith. This coordinate system forms a right-handed orthogonal coordinate system.

[0050] 3. Coordinate system of inertial measurement device o p x p y p z p (p series) The IMU coordinate system has its origin at the accelerometer sensor center. p The coordinate axes are defined as: x P The axis points directly in front of the sensor, y p The axis points to the left side of the sensor, z p The axes point towards the zenith. This application ensures that they are precisely aligned with the carrier coordinate system during installation, eliminating initial installation errors. These three coordinate axes satisfy a right-handed coordinate system.

[0051] The core of inertial positioning is to convert sensor coordinate system (p-frame) data into global coordinate system (n-frame) information.

[0052] For example, the first acceleration and first angular velocity information in the coordinate system of the inertial measurement device are converted into information data in the global coordinate system using the Euler angle method. Euler angles are as follows: Figure 2 As shown. Assuming sequential rotation around the xyz axes of the carrier coordinate system b, Euler angles are the representation of IMU attitude calculation, involving roll, pitch, and yaw angles. , , ), which respectively refer to: (roll): Roll angle, rotation around the X-axis, range [-90°, 90°], changes the left and right tilt of the object.

[0053] (pitch): Pitch angle, rotates around the Y-axis, range [-90°, 90°], changes the up and down tilt of the object.

[0054] (yaw): Heading angle, rotates around the Z-axis, range [0°, 360°], changes the orientation of the object.

[0055] S202. Filter the acceleration and angular velocity information to perform attitude calculations and obtain component velocity information, component position information and attitude angle information.

[0056] In some embodiments of the application, Kalman filtering is performed on the acceleration information and angular velocity information to obtain processed acceleration information and processed angular velocity information; through a preset three-dimensional trajectory window and a quaternion attitude solving model, the processed acceleration information and the processed angular velocity information are subjected to attitude solving and integral operation to obtain component velocity information, component position information and attitude angle information.

[0057] Exemplarily, the quaternion, the Euler angle and the direction cosine matrix are core mathematical tools for describing the spatial rotation attitude, and there is a clear conversion relationship among them. The calculation of the attitude matrix and the attitude angle is completed in the embedded controller ESP32, and the conversion of the quaternion, the Euler angle and the direction cosine matrix is performed as follows.

[0058] 1. Conversion between quaternion and Euler angle (1) Conversion from quaternion to Euler angle , , ) Given the quaternion Q = [q o q1q2 q3]T, the Euler angle (P, Y, Z) can be calculated by the following formula: , , ) :

[0059] = arctan( - 2(q,q - q2q3))

[0060] (2) Conversion from Euler angle to quaternion Given the Euler angle (P, Y, Z), the components of the quaternion can be calculated by the following formula: , , ) :

[0061] 2. Conversion between Euler angle and direction cosine matrix (1) Conversion from Euler angle to direction cosine matrix Taking the Z-Y-X rotation sequence as an example, the composite rotation is realized by multiplying the matrices of three basic rotations: R = Rx (a)Ry(P)Rz P), wherein Rz (a), Ry(P) and Rz (Y) are rotation matrices around the corresponding axes, and the matrix elements are filled by trigonometric functions, such as:

[0062]

[0063]

[0064] (2) Direction cosine matrix to Euler angle Elements are extracted from the direction cosine matrix R, as shown in the following formula, to extract the yaw angle, pitch angle, and roll angle respectively:

[0065] = arcsin(-r31)

[0066] When the pitch angle is ±90°, the gimbal locks up, and quaternions need to be used for attitude calculation.

[0067] 3. Quaternion to Directional Cosine Matrix Transformation (1) Quaternion Direction Cosine Matrix

[0068] (2) Direction cosine matrix to quaternion Solving for quaternion components using the matrix trace:

[0069]

[0070]

[0071]

[0072] Methods based on IMU dynamic positioning, such as Figure 3 As shown in the dynamic trajectory monitoring window of the precast component, the X / Y / Z three-axis translational amounts acquired by the IMU, after Kalman filtering, exhibit typical linear motion characteristics (displacement range ±150mm, positioning accuracy ≤1.2mm). However, due to the limitation of the planar projection viewing angle, the attitude angle change is not visible because its magnitude is small (<0.5°). Therefore, a three-dimensional trajectory window was further constructed, as shown in the figure. Figure 4 As shown, the six-degree-of-freedom motion information is fused into a continuous spatiotemporal trajectory (sampling frequency of 100Hz) through quaternion attitude calculation. Figure 3The middle red trajectory line represents the actual displacement path of the IMU, and the blue reference line corresponds to the quaternion attitude calculation model. This visualization system not only realizes the synchronous presentation of multi-dimensional motion parameters (displacement error band ±3σ = 1.5mm, angle calculation accuracy ±0.05°), but also intuitively displays the data acquisition characteristics of the IMU under complex motion conditions through parameterized labeling of the coordinate axes (X / Y / Z range ±200mm), providing data support for the continuous position output of the subsequent servo control system.

[0073] It can be understood that the acceleration information and the angular velocity information are subjected to Kalman filtering processing to obtain processed acceleration information and processed angular velocity information; through a preset three-dimensional trajectory window and a quaternion attitude calculation model, attitude calculation and integral operation are performed on the processed acceleration information and the processed angular velocity information to obtain component velocity information, component position information and attitude angle information, so that high-precision hoisting positioning of the component can be realized, and repeated lifting and manual correction can be avoided.

[0074] In some embodiments of the present application, the basic architecture of the component hoisting positioning information data transmission mainly covers three key parts: data acquisition terminal, wireless transmission device (such as WIFI router) and classification server.

[0075] 1. Data acquisition terminal. In the process of hoisting the prefabricated component, the IMU sensor is the data acquisition terminal. The IMU sensor can accurately and in real time collect dynamic information such as displacement, angle and acceleration of the prefabricated component during hoisting. After processing the sensor information obtained by the data acquisition terminal, the data is sent to the WIFI router in a stable and efficient transmission state by means of wireless communication.

[0076] 2. WIFI router. The WIFI router plays a key role in the intermediate transmission hub in the entire data transmission architecture. It can reliably receive data from the data acquisition terminal and quickly and accurately forward these data to the classification server, thereby smoothly realizing wireless data transmission. In the prefabricated component hoisting positioning system, the existence of WIFI greatly reduces the cost and complexity problems brought by traditional wiring. At the same time, it also significantly improves the flexibility and real-time performance of data transmission. Even in the case of complex and variable construction site environment, WIFI can ensure stable transmission of data between the acquisition terminal and the server.

[0077] 3. Classification Server. The classification server is the core processing unit of the entire data transmission architecture. It is responsible for receiving prefabricated component hoisting and positioning data transmitted via Wi-Fi, and for comprehensively storing, deeply analyzing, and meticulously classifying this data. In terms of storage, the classification server can securely and long-term preserve data. In the analysis phase, the server uses pre-set algorithms and models to process the collected displacement, angle, and other data to determine the real-time position and attitude information of the prefabricated components. In terms of classification, the server categorizes and organizes the data according to different application requirements, providing strong support for various subsequent applications. This provides accurate position and attitude information, enabling precise positioning and safe hoisting of prefabricated components.

[0078] The basic operation flow of the component location data acquisition system is as follows: The IMU data acquisition terminal records the displacement and attitude data of the precast component in real time, calculates its position and attitude, and transmits the data to the classification server via a WiFi router. The router only acts as an intermediary for data transmission in the system and does not affect the integrity and real-time performance of the data. After calculation, the system updates the spatial pose of the precast component to ensure precise control during the hoisting process.

[0079] Understandably, this application can achieve high-precision hoisting and positioning of components, avoiding repeated lifting and manual correction; improve the real-time performance of component attitude control and enhance the system's dynamic response capability; adapt to complex, dynamic, and multi-interference on-site construction environments through collaborative perception fusion algorithms and predictive control; reduce high-risk manual intervention and improve the overall construction safety level and intelligence level.

[0080] Based on the component precision hoisting method based on heterogeneous sensing collaborative perception in the above embodiments, this application also provides a component precision hoisting system based on heterogeneous sensing collaborative perception, such as... Figure 5 As shown, Figure 5 This is a schematic diagram of a component precision hoisting system based on heterogeneous sensing collaborative perception, provided in an embodiment of this application. The component precision hoisting system 5 based on heterogeneous sensing collaborative perception includes: an acquisition module 501, a calculation module 502, a determination module 503, and a control module 504, wherein... The acquisition module 501 is used to acquire the attitude information of the component through an inertial measurement unit arranged at a preset key position of the component; wherein, the attitude information includes: original acceleration information and original angular velocity information; The calculation module 502 is used to perform data preprocessing and filtering attitude calculation on the original acceleration information and the original angular velocity information to obtain component velocity information, component position information and attitude angle information; The determination module 503 is configured to perform motion trend prediction based on the component speed information, the component position information and the attitude angle information through a pre-determined motion trend prediction model, and determine the inclination trend of the component. The control module 504 is configured to control a hoisting positioning device to adjust the position of the component based on the inclination trend of the component and the spatial distance information, so that the adjusted component is aligned with a preset installation position, and component assembly is completed. The spatial distance information is a spatial distance between the component and a target positioning point measured by a laser radar system.

[0081] Based on the component precision hoisting method based on heterogeneous sensor collaborative perception in the above embodiments, the embodiment of the present application further provides a component precision hoisting device based on heterogeneous sensor collaborative perception, as shown in Figure 6 Figure 6 A component precision hoisting device based on heterogeneous sensor collaborative perception provided by the embodiment of the present application, the component precision hoisting device 6 based on heterogeneous sensor collaborative perception includes a processor 601 and a memory 602. The memory 602 is configured to store a computer program, and the processor 601 is configured to call and run the computer program from the memory to execute the component precision hoisting method based on heterogeneous sensor collaborative perception as described in the above embodiments.

[0082] In the embodiment of the present application, the above processor 601 can be at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor. It can be understood that for different devices, the electronic devices used to implement the above processor functions can also be other, and the embodiment of the present application does not make specific limitations.

[0083] The embodiment of the present application provides a computer readable storage medium, which stores a computer program, and is used to implement the component precision hoisting method based on heterogeneous sensor collaborative perception as described in any of the above embodiments when executed by a processor.

[0084] ​Exemplarily, the program instruction corresponding to the component precision hoisting method based on heterogeneous sensor collaborative perception in the embodiment can be stored on a storage medium such as an optical disc, a hard disk, a U disk, and the like. When the program instruction corresponding to the component precision hoisting method based on heterogeneous sensor collaborative perception in the embodiment is read by an electronic device or executed, the component precision hoisting method based on heterogeneous sensor collaborative perception can be implemented as described in any of the above embodiments.

[0085] In addition, each function module in the embodiments of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function module.

[0086] The integrated unit, if realized in the form of a software function module and not sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the embodiments can be embodied in the form of a software product, the computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the embodiments. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0087] It should be understood that the "one embodiment" or "an embodiment" or "some embodiments" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiments are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" or "in some embodiments" appearing throughout the specification does not necessarily mean the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the serial number of each process does not mean the execution order, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The serial number of the above embodiments of the present application is only for description, not representing the advantages and disadvantages of the embodiments. The above description of each embodiment tends to emphasize the differences between each embodiment, and the same or similar parts can be referred to each other. For the sake of brevity, the present application will not be described again.

[0088] The modules described as separate components above can or can not be physically separate, and the components displayed as modules can or can not be physical modules; they can be located in one place or distributed on multiple network units; and part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs.

[0089] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each module can be a separate unit, or two or more modules can be integrated in one unit; the integrated modules can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0090] Those skilled in the art can understand that all or part of the steps of the above method embodiments can be completed by program instruction related hardware, and the foregoing program can be stored in a computer readable storage medium, and the program is executed to perform steps including the above method embodiments; and the foregoing storage medium includes mobile storage devices, read only memory (Read Only Memory, ROM), magnetic discs or optical discs, and various storage medium that can store program codes.

[0091] The methods disclosed in the several method embodiments provided by the embodiments of the present application can be combined arbitrarily without conflict to obtain new method embodiments.

[0092] The features disclosed in the several product embodiments provided by the embodiments of the present application can be combined arbitrarily without conflict to obtain new product embodiments.

[0093] The features disclosed in the several method or device embodiments provided by the embodiments of the present application can be combined arbitrarily without conflict to obtain new method or device embodiments.

[0094] The above is only an implementation manner of the embodiments of the present application, but the protection scope of the embodiments of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the embodiments of the present application. Therefore, the protection scope of the embodiments of the present application should be subject to the protection scope of the claims.

Claims

1. A component precision hoisting method based on heterogeneous sensor collaborative sensing, characterized in that, The method comprises: Obtaining attitude information of the component through an inertial measurement unit arranged at a preset key position of the component; wherein the attitude information comprises original acceleration information and original angular velocity information; Performing data preprocessing and filtering attitude operation on the original acceleration information and the original angular velocity information to obtain component speed information, component position information and attitude angle information; Based on the component speed information, the component position information and the attitude angle information, performing motion trend prediction through a pre-determined motion trend prediction model to determine the inclination trend of the component; Based on the inclination trend of the component and spatial distance information, controlling a hoisting positioning device to adjust the position of the component so that the adjusted component is aligned with a preset installation position, thereby completing component assembly; wherein the spatial distance information is the spatial distance between the component and a target positioning point measured by a laser radar system.

2. The method of claim 1, wherein, The data preprocessing and filtering attitude operation on the original acceleration information and the original angular velocity information to obtain component speed information, component position information and attitude angle information comprises: Performing data preprocessing on the original acceleration information and the original angular velocity information to obtain acceleration information and angular velocity information; Performing filtering attitude operation on the acceleration information and the angular velocity information to obtain the component speed information, the component position information and the attitude angle information.

3. The method of claim 2, wherein, The data preprocessing on the original acceleration information and the original angular velocity information to obtain acceleration information and angular velocity information comprises: Respectively performing data conversion on the original acceleration information and the original angular velocity information to obtain converted original acceleration information and converted original angular velocity information; Respectively performing error correction on the converted original acceleration information and the converted original angular velocity information through a pre-determined error model to obtain corrected original acceleration information and corrected original angular velocity information; Respectively performing denoising, coordinate transformation and gravity correction on the corrected original acceleration information and the corrected original angular velocity information to obtain the acceleration information and the angular velocity information.

4. The method of claim 3, wherein, The data preprocessing on the original acceleration information and the original angular velocity information to obtain acceleration information and angular velocity information comprises: Respectively performing denoising on the corrected original acceleration information and the corrected original angular velocity information to obtain first acceleration information and first angular velocity information; Aligning the inertial measurement device coordinate system corresponding to the first acceleration information and the first angular velocity information with a motion carrier coordinate system determined by the component; and converting the first acceleration information and the first angular velocity information under the inertial measurement device coordinate system into information data under a global coordinate system through Euler angle method; Performing gravity correction on the information data to obtain the acceleration information and the angular velocity information.

5. The method of claim 2, wherein, The filtering attitude operation on the acceleration information and the angular velocity information obtains the component velocity information, the component position information and the attitude angle information, and comprises: Kallman filtering processing is performed on the acceleration information and the angular velocity information to obtain processed acceleration information and processed angular velocity information; Through a preset three-dimensional trajectory window and a quaternion attitude solution model, attitude solution and integral operation are performed on the processed acceleration information and the processed angular velocity information to obtain the component velocity information, the component position information and the attitude angle information.

6. The method of claim 1, wherein, The motion trend prediction model is used to predict the motion trend of the component based on the component velocity information, the component position information and the attitude angle information to determine the inclination trend of the component, and comprises: A tension sensor arranged on each lifting point is used to obtain lifting point load distribution information; The lifting point load distribution information, the component velocity information, the component position information and the attitude angle information are time-aligned to obtain to-be-predicted motion information; The motion trend prediction model is used to predict the motion trend of the component based on the to-be-predicted motion information to determine the inclination trend of the component.

7. The method of claim 1, wherein, Based on the inclination trend of the component and the spatial distance information, the position of the component is adjusted by the hoisting positioning device, the adjusted component is aligned with a preset installation position, and component assembly is completed, and comprises: Based on the inclination trend of the component and the spatial distance information, the position of the component is adjusted by the hoisting positioning device to obtain an adjusted component position; The distance between the adjusted component position and the target positioning point is calculated to obtain a distance error; If the distance error is within a preset distance error range, the component is aligned with a preset installation position based on the adjusted component position, and component assembly is completed; If the distance error is not within the preset distance error range, the component position is adjusted until the distance error between the adjusted component position and the target positioning point is within the preset distance error range, and the component is aligned with a preset installation position based on the adjusted component position, and component assembly is completed.

8. A component precision hoisting system based on heterogeneous sensor collaborative perception, characterized in that, The component precision hoisting system based on heterogeneous sensor cooperative perception comprises an acquisition module, an operation module, a determination module and a control module, wherein The acquisition module is configured to acquire attitude information of a component by an inertial measurement unit arranged at a preset key position of the component, wherein the attitude information comprises original acceleration information and original angular velocity information; The operation module is configured to perform data preprocessing and filtering attitude operation on the original acceleration information and the original angular velocity information to obtain component velocity information, component position information and attitude angle information; The determination module is configured to determine the inclination trend of the component by a pre-determined motion trend prediction model based on the component velocity information, the component position information and the attitude angle information. The control module is configured to control a hoisting positioning device to adjust the position of the component based on the inclination trend and the spatial distance information of the component, so that the adjusted component is aligned with a preset installation position, and component assembly is completed; the spatial distance information is a spatial distance between the component and a target positioning point measured by a laser radar system.

9. A component precision hoisting equipment based on heterogeneous sensor collaborative perception, characterized in that, Comprising: a processor and a memory, the memory is configured to store a computer program; the processor is configured to call and run the computer program from the memory to execute the method in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, executable instructions are stored for causing the processor to execute when the method of any one of claims 1 to 7 is implemented.

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