An assembled building intelligent hoisting method and system and a readable storage medium

Abstract

A method, system, and readable storage medium for intelligent hoisting of prefabricated buildings relate to the field of on-site processing technology for building materials. The method involves: acquiring current raw data and current environmental data; obtaining the current position coordinates of the hoisted component based on the current raw data; determining the current hoisting scheme based on the current position coordinates; calculating the current reliability of the current raw data based on the current environmental data; adjusting the parameters of the positioning sensors based on the current reliability; acquiring new raw data at the next sampling time; obtaining the new position coordinates of the hoisted component based on the new raw data; determining a compensation scheme based on the difference between the new and current position coordinates; identifying the unfinished portion of the current hoisting scheme; and combining the compensation scheme with the unfinished portion to obtain a new hoisting scheme. By improving adaptability to changing on-site environments, the accuracy of the hoisting scheme is improved, resulting in increased overall work efficiency and reduced construction costs.

Description

Technical Field

[0001] This application relates to the field of on-site processing technology of building materials, and in particular to an intelligent hoisting method, system and readable storage medium for prefabricated buildings. Background Technology

[0002] With the advancement of technology and the development of the construction industry, prefabricated buildings, with their advantages of high construction efficiency, environmental friendliness, and controllable costs, are increasingly becoming an important development direction for the construction industry. Intelligent hoisting technology, as a core component of prefabricated buildings, directly impacts the construction efficiency and quality of the entire project through its level of automation and intelligence.

[0003] Currently, intelligent hoisting methods for prefabricated buildings mainly rely on advanced automatic control systems and mechanical devices. These systems automatically complete the hoisting operations of building components through preset programs and algorithms, combined with data from positioning sensors. These technologies have improved the accuracy and automation level of hoisting operations to a certain extent.

[0004] Currently, intelligent hoisting systems for prefabricated buildings are not yet effectively adapted to the ever-changing site environment. Due to the continuous changes in environmental factors, the fixed parameter settings of sensors may fail to adapt to these changes, leading to errors in the data collected by the sensors. The accumulation of such errors directly affects the accuracy of the hoisting plan. Although workers may make manual adjustments in subsequent processes, frequent or excessive corrections will reduce overall work efficiency and increase construction costs. Summary of the Invention

[0005] This application provides an intelligent hoisting method, system, and readable storage medium for prefabricated buildings, which improves adaptability to changing site environments, thereby improving the accuracy of hoisting schemes, increasing overall work efficiency, and reducing construction costs.

[0006] Firstly, this application provides an intelligent hoisting method for prefabricated buildings, including:

[0007] At the current sampling time, acquire the current raw data obtained by the positioning sensor from the hoisting component and the current environmental data collected by the environmental sensor;

[0008] The current position coordinates of the hoisting component are obtained based on the current raw data;

[0009] The current lifting plan is determined based on the current location coordinates and sent to the lifting assembly, so that the lifting assembly executes the current lifting plan; the current lifting plan includes the lifting trajectory and lifting actions;

[0010] Calculate the current reliability of the original data based on the current environmental data;

[0011] Adjust the parameters of the positioning sensor based on the current level of confidence;

[0012] The adjusted positioning sensor acquires the new raw data of the hoisting component at the next sampling time.

[0013] The new position coordinates of the hoisting component are obtained based on the new original data;

[0014] The compensation scheme is determined based on the difference between the new position coordinates and the current position coordinates;

[0015] Determine the remaining unfinished portion of the hoisting component under the current hoisting plan at the current moment;

[0016] The compensation plan is combined with the remaining unfinished parts to obtain a new hoisting plan;

[0017] Send the new lifting plan to the lifting assembly, so that the lifting assembly executes the new lifting plan.

[0018] In the above embodiments, by acquiring and analyzing positioning and environmental data in real time, the operating parameters of the hoisting components are adaptively adjusted, improving adaptability to changing site environments. This, in turn, enhances the accuracy of the hoisting plan, increases overall work efficiency, and reduces construction costs. The integration of compensation schemes can correct the hoisting trajectory in real time, ensuring the continuity and stability of hoisting operations in dynamic environments.

[0019] In conjunction with some embodiments of the first aspect, in some embodiments, after the step of obtaining the new raw data acquired by the adjusted positioning sensor from the hoisting component at the next sampling time, the method further includes:

[0020] Acquire new environmental data collected by environmental sensors at the next sampling time;

[0021] Calculate the new credibility of the new original data based on the new environmental data;

[0022] If the new confidence level is lower than the confidence level threshold, adjust the parameters of the positioning sensor based on the new confidence level.

[0023] Perform the step of acquiring the new raw data obtained by the adjusted positioning sensor from the hoisting component at the next sampling time.

[0024] In the above embodiments, by acquiring new environmental data from environmental sensors, the reliability of the new raw data can be calculated. If this new reliability is lower than a predetermined threshold, the parameters of the positioning sensor will be adjusted in order to obtain data with higher reliability in the next sampling. This process is repeated to continuously optimize the system and further improve the accuracy of the hoisting scheme.

[0025] In conjunction with some embodiments of the first aspect, in some embodiments, a compensation scheme is determined based on the difference between the new position coordinates and the current position coordinates, specifically including:

[0026] If the difference between the new position coordinates and the current position coordinates is greater than the deviation threshold, a compensation scheme is determined based on the difference between the new position coordinates and the current position coordinates.

[0027] In the above embodiments, a compensation scheme is determined based on the difference between the new and current position coordinates only when the difference between the old and new position coordinates is greater than a certain predetermined deviation threshold, so as to avoid wasting computing resources and time on minor position changes. Compensation measures are only taken when the position change is significant and may affect the operation results.

[0028] In conjunction with some embodiments of the first aspect, in some embodiments, the step of calculating the current confidence level of the current raw data based on the current environmental data and adjusting the parameters of the positioning sensor based on the current confidence level specifically includes:

[0029] Determine whether the current environmental parameter in the current environmental data is greater than the corresponding preset current environmental threshold; the current environmental parameter can be any environmental parameter in the current environmental data;

[0030] If the difference between the current environment parameter and the preset current environment threshold is greater than the corresponding current environment threshold, the difference between the current environment parameter and the preset current environment threshold is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter;

[0031] Statistics of all adjusted parameters;

[0032] Adjust the parameters of the positioning sensor based on all adjustment parameters.

[0033] In the above embodiments, by adjusting the positioning sensor parameters based on the difference between changes in environmental parameters and preset thresholds, the scheme ensures the reliability of positioning data and improves positioning accuracy. Simultaneously, the adjustment of positioning sensor parameters according to environmental changes enhances the ability to maintain positioning accuracy in variable environments.

[0034] In conjunction with some embodiments of the first aspect, in some embodiments, the step of calculating the current confidence level of the current raw data based on the current environmental data and adjusting the parameters of the positioning sensor based on the current confidence level specifically includes:

[0035] Determine whether the current environmental parameter in the current environmental data belongs to the corresponding preset current environmental range; the current environmental parameter is any environmental parameter in the current environmental data;

[0036] If it does not belong to the corresponding preset current environment threshold, then the current environment parameter is determined to be either exceeding the preset current environment range or not reaching the preset current environment range.

[0037] If the current environment parameter exceeds the preset range, the difference between the current environment parameter and the minimum value in the preset range is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter.

[0038] If the current environment range is not reached, the difference between the current environment parameter and the maximum value in the current environment range is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter.

[0039] Statistics of all adjusted parameters;

[0040] Adjust the parameters of the positioning sensor based on all adjustment parameters.

[0041] In the above embodiments, by determining whether the current environmental parameters fall outside the preset environmental range, and whether they exceed or fall below the range, the system can make targeted adjustments to these parameters, thereby optimizing the sensor calibration process and ensuring the continuity and efficiency of the operation.

[0042] In conjunction with some embodiments of the first aspect, in some embodiments, the step of obtaining the current position coordinates of the hoisting component based on the current raw data specifically includes:

[0043] Extract all two-dimensional images from the current raw data;

[0044] The corresponding pixels in different two-dimensional images are found using a stereo matching algorithm;

[0045] The depth information of the pixel is calculated based on the triangulation principle;

[0046] The current position coordinates of the hoisting component are determined based on the depth information of the pixels and their two-dimensional positions in the two-dimensional image.

[0047] In the above embodiment, the process of extracting all two-dimensional images, finding corresponding pixels using a stereo matching algorithm, calculating depth information using the triangulation principle, and finally combining the depth information and two-dimensional position information to calculate the current position coordinates of the hoisting component improves the efficiency of calculating the current position coordinates of the hoisting component.

[0048] In conjunction with some embodiments of the first aspect, in some embodiments, the step of calculating the current credibility of the current original data based on the current environmental data specifically includes:

[0049] After determining the current hoisting scheme based on the current location coordinates, the current reliability of the original data is calculated based on the current environmental data.

[0050] In the above embodiments, the determination of the current hoisting scheme and the calculation of the current credibility of the current raw data are carried out asynchronously to ensure that the critical determination of the current hoisting scheme can be processed in a timely manner, thus ensuring the continuity of the overall work.

[0051] Secondly, embodiments of this application provide an intelligent hoisting system for prefabricated buildings, comprising:

[0052] The first acquisition module is used to acquire the current raw data obtained by the positioning sensor from the hoisting component and the current environmental data collected by the environmental sensor at the current sampling time.

[0053] The first coordinate module is used to obtain the current position coordinates of the hoisting component based on the current raw data;

[0054] The first plan module is used to determine the current hoisting plan based on the current position coordinates and send the current hoisting plan to the hoisting component, so that the hoisting component can execute the current hoisting plan; the current hoisting plan includes the hoisting trajectory and hoisting actions;

[0055] The first credibility module is used to calculate the current credibility of the current original data based on the current environmental data.

[0056] The first adjustment module is used to adjust the parameters of the positioning sensor based on the current confidence level;

[0057] The second acquisition module is used to acquire the new raw data obtained by the adjusted positioning sensor from the hoisting component at the next sampling time.

[0058] The second coordinate module is used to obtain the new position coordinates of the hoisting component based on the new original data;

[0059] The second scheme module is used to determine the compensation scheme based on the difference between the new position coordinates and the current position coordinates;

[0060] The incomplete module is used to determine the remaining unfinished part of the current lifting plan for the lifting component at the current moment;

[0061] The mixing module is used to combine the compensation plan with the unfinished remaining parts to obtain a new hoisting plan;

[0062] The sending module is used to send new hoisting plans to the hoisting components, so that the hoisting components can execute the new hoisting plans.

[0063] In conjunction with some embodiments of the second aspect, in some embodiments, the system further includes:

[0064] The third acquisition module is used to acquire new environmental data collected by the environmental sensor at the next sampling time.

[0065] The second credibility module is used to calculate the new credibility of the new original data based on the new environmental data.

[0066] The second adjustment module is used to adjust the parameters of the positioning sensor based on the new confidence level when the new confidence level is lower than the confidence level threshold.

[0067] The loop module is used to acquire the new raw data obtained by the adjusted positioning sensor from the hoisting component at the next sampling time.

[0068] In conjunction with some embodiments of the second aspect, in some embodiments, the second solution module is specifically used for:

[0069] If the difference between the new position coordinates and the current position coordinates is greater than the deviation threshold, a compensation scheme is determined based on the difference between the new position coordinates and the current position coordinates.

[0070] In conjunction with some embodiments of the second aspect, in some embodiments, the first trust module specifically includes:

[0071] The first judgment submodule is used to determine whether the current environment parameter in the current environment data is greater than the corresponding preset current environment threshold; the current environment parameter is any environment parameter in the current environment data;

[0072] The first adjustment module specifically includes:

[0073] The first input submodule is used to input the difference between the current environment parameter and the preset current environment threshold into the rule corresponding to the current environment parameter if the difference is greater than the corresponding preset current environment threshold, so as to obtain the adjustment parameter.

[0074] The first statistics submodule is used to collect statistics on all adjusted parameters;

[0075] The first adjustment submodule is used to adjust the parameters of the positioning sensor based on all adjustment parameters.

[0076] In conjunction with some embodiments of the second aspect, in some embodiments, the first trust module specifically includes:

[0077] The second judgment submodule is used to determine whether the current environmental parameter in the current environmental data belongs to the corresponding preset current environmental range; the current environmental parameter is any environmental parameter in the current environmental data;

[0078] The third judgment submodule is used to determine whether the current environment parameter exceeds the preset current environment range or does not reach the preset current environment range if it does not belong to the corresponding preset current environment threshold.

[0079] The first adjustment module specifically includes:

[0080] The second input submodule is used to input the difference between the current environment parameter and the minimum value in the preset current environment range into the rule corresponding to the current environment parameter if the current environment parameter exceeds the preset current environment range, so as to obtain the adjustment parameter.

[0081] The second input submodule is used to input the difference between the current environment parameter and the maximum value in the preset current environment range into the rule corresponding to the current environment parameter if the current environment range is not reached, so as to obtain the adjustment parameter.

[0082] The second statistics submodule is used to collect statistics on all adjusted parameters;

[0083] The second adjustment submodule is used to adjust the parameters of the positioning sensor based on all adjustment parameters.

[0084] In conjunction with some embodiments of the second aspect, in some embodiments, the first coordinate module specifically includes:

[0085] The extraction submodule is used to extract all two-dimensional images from the current raw data;

[0086] The matching submodule is used to find corresponding pixels in different two-dimensional images using a stereo matching algorithm.

[0087] The calculation submodule is used to calculate the depth information of pixels based on the triangulation principle;

[0088] The determination submodule is used to determine the current position coordinates of the hoisting component based on the depth information of the pixels and the two-dimensional position of the pixels in the two-dimensional image.

[0089] In conjunction with some embodiments of the second aspect, in some embodiments, the first credibility module is specifically used to: after determining the current hoisting scheme based on the current location coordinates, calculate the current credibility of the current original data based on the current environmental data.

[0090] Thirdly, embodiments of this application provide an intelligent hoisting system for prefabricated buildings, the system comprising: one or more processors and a memory;

[0091] The memory is coupled to the one or more processors and is used to store computer program code, which includes computer instructions that the one or more processors invoke to cause the prefabricated building intelligent hoisting system to perform the methods described in the first aspect and any possible implementation thereof.

[0092] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a server, cause the server to perform the method described in the first aspect and any possible implementation thereof.

[0093] Fifthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a prefabricated building intelligent hoisting system, cause the prefabricated building intelligent hoisting system to perform the method described in the first aspect and any possible implementation thereof.

[0094] Understandably, the intelligent hoisting system for prefabricated buildings provided in the second aspect, the third aspect, the fourth aspect, and the fifth aspect are all used to execute the intelligent hoisting method for prefabricated buildings provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to in the beneficial effects of the corresponding methods, and will not be repeated here.

[0095] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0096] 1. The intelligent hoisting method for prefabricated buildings provided in this application improves adaptability to changing site environments by acquiring and analyzing positioning and environmental data in real time, and adaptively adjusting the operating parameters of hoisting components. This enhances the accuracy of the hoisting plan, improves overall work efficiency, and reduces construction costs. The integrated compensation scheme can correct the hoisting trajectory in real time, ensuring the continuity and stability of hoisting operations in dynamic environments.

[0097] 2. The intelligent hoisting method for prefabricated buildings provided in this application can calculate the reliability of the new original data by acquiring new environmental data from environmental sensors. If the new reliability is lower than a predetermined threshold, the parameters of the positioning sensor will be adjusted in order to obtain data with higher reliability in the next sampling. The repeated execution of this process, through continuous self-optimization, further improves the accuracy of the hoisting scheme. Attached Figure Description

[0098] Figure 1 A flowchart illustrating the intelligent hoisting method for prefabricated buildings provided in this application.

[0099] Figure 2 Another flowchart illustrating the intelligent hoisting method for prefabricated buildings provided in this application.

[0100] Figure 3 A schematic diagram of the modular virtual device of the intelligent hoisting system for prefabricated buildings provided in this application.

[0101] Figure 4 A schematic diagram of the physical device of the prefabricated building intelligent hoisting system provided in this application. Detailed Implementation

[0102] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0103] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0104] The intelligent hoisting method for prefabricated buildings in this embodiment is described below:

[0105] like Figure 1 As shown, Figure 1 A flowchart illustrating the intelligent hoisting method for prefabricated buildings provided in this application.

[0106] S101. Obtain the current raw data collected by the positioning sensor from the hoisting component and the current environmental data collected by the environmental sensor at the current sampling time.

[0107] In some embodiments, the positioning sensor includes a laser scanner, whose main function is to capture fine details of building components and the geometry of the surrounding environment, thereby providing the necessary structural reference for positioning.

[0108] Optical cameras: At least two optical cameras should be configured to obtain high-resolution images. The dual-camera setup is to obtain depth information from the images through parallax, which is especially important for determining 3D coordinates.

[0109] Inertial Measurement Unit (IMU): Used to track the motion state of the device itself in real time, including acceleration and rotation angle. This helps to correct sensor data during movement and ensure positioning accuracy.

[0110] In other embodiments, only an optical camera is required, and this is not a limitation.

[0111] Environmental sensors, such as light sensors, are installed near the positioning sensors to monitor environmental variables, ensuring that the environmental sensors can accurately reflect the environmental conditions in which the positioning sensors are located.

[0112] It should be noted that the current environmental data is used to verify the reliability of the current original data. Therefore, the current original data must match the environmental data captured at the same time. Only when both come from the same point in time can the accuracy of the original data be effectively verified.

[0113] S102. Obtain the current position coordinates of the hoisting component based on the current raw data.

[0114] In some embodiments, step S102 specifically includes:

[0115] S1021. Extract all two-dimensional images from the current raw data;

[0116] As mentioned in the above embodiments, at least two optical cameras are configured, which are triggered synchronously to capture two-dimensional images at the same point in time. The images contain visual features of the hoisting component and position information relative to each camera.

[0117] S1022. Find the corresponding pixels in different two-dimensional images using a stereo matching algorithm;

[0118] Feature points are extracted from each image, and then feature descriptors are used to find corresponding matching points between different images. The matching results of all image pairs will be used for subsequent depth calculations.

[0119] S1023. Calculate the depth information of the pixel based on the triangulation principle;

[0120] For each pair of matched feature points, their positions in 3D space are calculated using triangulation principles. This requires the camera's intrinsic parameters (focal length, optical center coordinates) and extrinsic parameters (camera position and orientation), which can be obtained through the calibration process. During the calculation, the depth value of each point is calculated using the coordinates of the matched points in their respective images, as well as the known distance between the cameras, through trigonometric methods.

[0121] S1024. Determine the current position coordinates of the hoisting component based on the depth information of the pixel and the two-dimensional position of the pixel in the two-dimensional image.

[0122] By combining the depth information of each feature point with its position on the two-dimensional image, the coordinates are transformed into a common three-dimensional coordinate system to determine the current position coordinates of the hoisting component.

[0123] In related technologies, the methods for determining position coordinates are quite mature, and other methods for determining position coordinates can also be adopted, which are not limited here.

[0124] As can be seen, improving the efficiency of calculating the current position coordinates of the hoisting component by extracting all two-dimensional images, using a stereo matching algorithm to find the corresponding pixels, calculating depth information using the triangulation principle, and finally combining the depth information and two-dimensional position information.

[0125] S103. Determine the current hoisting plan based on the current position coordinates and send the current hoisting plan to the hoisting component so that the hoisting component can execute the current hoisting plan; the current hoisting plan includes the hoisting trajectory and hoisting actions.

[0126] In some embodiments, the current position of the crane is used as the starting point and the current position coordinates are used as the ending point to generate the optimal path from the starting point to the ending point using a path planning algorithm.

[0127] Of course, the technology of determining the hoisting scheme based on the location coordinates is already quite mature, so it will not be limited here.

[0128] S104. Calculate the current credibility of the original data based on the current environmental data.

[0129] In some embodiments, it is determined whether the current environmental parameter in the current environmental data is greater than the corresponding preset current environmental threshold; the current environmental parameter is any environmental parameter in the current environmental data.

[0130] If the current environmental parameters are greater than the corresponding preset current environmental threshold, it proves that the current original data is unreliable.

[0131] A specific scenario: At a construction site, an optical camera system is used to acquire raw data for container lifting operations. This data is used to calculate the specific lifting path and ensure that the containers are accurately transported to their designated storage locations. However, on a particular afternoon, the weather suddenly changed, with dense clouds causing a rapid decrease in lighting conditions. The camera system failed to adjust its exposure parameters in time, resulting in overly dark images where the edges and feature points of the lifted components could not be accurately identified. Furthermore, the reflective stickers on the container surfaces produced strong glare under unstable lighting, further interfering with the camera's recognition capabilities. Therefore, in certain specific scenarios, the reliability of the raw data is low.

[0132] S105. Adjust the parameters of the positioning sensor based on the current reliability.

[0133] In some embodiments, S105 specifically includes: S1051, inputting the difference between the current environmental parameter and the preset current environmental threshold into the rule corresponding to the current environmental parameter to obtain the adjustment parameter; the current environmental parameter is any environmental parameter in the current environmental data.

[0134] In practical applications, for each environmental parameter, one or more thresholds are set based on experimental or operational experience. These thresholds define the ideal operating range or limiting conditions of the parameter. For example, for light intensity, the ideal operating range might be set to 5000 lux.

[0135] Acquire current environmental parameter data in real time, such as the current light intensity of 6000 lux. Compare this value with a preset threshold and calculate the difference. For example, the difference between the current light intensity and the minimum threshold is 1000 lux (6000 - 5000 = 1000).

[0136] The difference is input into the rules corresponding to the environmental parameter. These rules are formulated based on the actual situation and are not limited here. For example, for light intensity, the rule may stipulate that for every 1000 lux decrease in light intensity, the exposure time should be increased by 0.5 seconds or the ISO value should be increased by a certain percentage.

[0137] After applying the rules, a set of adjustment parameters is obtained. Taking light intensity as an example, if the current light intensity is lower than the ideal threshold, the adjustment parameters may include increasing the exposure time, opening the aperture, increasing the ISO setting, etc.

[0138] It should be noted that the current environmental data includes multiple parameters, such as light intensity, light direction, color temperature, etc.

[0139] Step S1051 is an example using one parameter. The same processing method should be used for other parameters, and will not be repeated here.

[0140] S1052. Compile all adjusted parameters;

[0141] S1053. Adjust the parameters of the positioning sensor based on all adjustment parameters.

[0142] As can be seen, by adjusting the positioning sensor parameters based on the difference between environmental parameter changes and preset thresholds, the solution ensures the reliability of positioning data and improves positioning accuracy. Simultaneously, the adjustment of positioning sensor parameters according to environmental changes enhances the ability to maintain positioning accuracy in variable environments.

[0143] It should be noted that steps S102 to S103 and steps S104 to S105 are parallel processes, and there is no fixed order requirement between them. However, from a practical perspective, in the workflow of hoisting professionals, even if problems arise in the plan, workers may still manually adjust it in subsequent steps to correct the errors. But if a hoisting plan is not generated in a timely manner, it may disrupt the smooth progress of the hoisting operation, thereby affecting the continuity of the entire operation. Therefore, in some embodiments, the original step S104 can be replaced by the following steps: after determining the current hoisting plan based on the current position coordinates, calculate the current reliability of the current raw data based on the current environmental data.

[0144] As can be seen, the asynchronous processing of determining the current hoisting plan and calculating the current credibility of the original data ensures that the critical determination of the current hoisting plan can be processed in a timely manner, thus guaranteeing the continuity of the overall work.

[0145] S106. Obtain the new raw data of the hoisting component collected by the adjusted positioning sensor at the next sampling time.

[0146] It should be noted that the idea and specific implementation details of this step are similar to those of step S101. Please refer to step S101 for details. No specific limitations are made here.

[0147] S107. Obtain the new position coordinates of the hoisting component based on the new original data.

[0148] It should be noted that the idea and specific implementation details of this step are similar to those of step S102. Please refer to step S102 for details. No specific limitations are made here.

[0149] S108. Determine the compensation scheme based on the difference between the new position coordinates and the current position coordinates.

[0150] It should be noted that the idea and specific implementation details of this step are similar to those of step S103. Please refer to step S103 for details. No specific limitations are made here.

[0151] S109. Determine the remaining unfinished portion of the hoisting component under the current hoisting plan at the current moment.

[0152] In some embodiments, a recording system for the lifting assembly is used to determine the portion of the trajectory already completed by the lifting assembly within the current lifting plan. Assume the current lifting plan describes a precise path for the assembly to reach its destination from its starting position via multiple intermediate points. If adjustments are needed during execution, it is necessary to accurately identify the current location of the assembly and the predetermined trajectory it has not yet traversed.

[0153] S110. Combine the compensation plan with the remaining unfinished parts to obtain a new hoisting plan.

[0154] The combination of the compensation scheme and the incomplete trajectory should generate a new, complete hoisting motion scheme, which details the corrected path from the current position to the new position coordinates.

[0155] S111. Send the new hoisting plan to the hoisting component, so that the hoisting component executes the new hoisting plan.

[0156] It is evident that by acquiring and analyzing positioning and environmental data in real time, and adaptively adjusting the operating parameters of the hoisting components, the adaptability to changing site environments is improved, thereby enhancing the accuracy of the hoisting plan, increasing overall work efficiency, and reducing construction costs. The integration of compensation schemes can correct the hoisting trajectory in real time, ensuring the continuity and stability of hoisting operations in dynamic environments.

[0157] In some other embodiments, after step S111, the method further includes:

[0158] Step S112: Obtain the new environmental data collected by the environmental sensor at the next sampling time;

[0159] It should be noted that the idea and specific implementation details of this step are similar to those of step S102. Please refer to step S102 for details. No specific limitations are made here.

[0160] Step S113: Calculate the new credibility of the new original data based on the new environmental data;

[0161] It should be noted that the idea and specific implementation details of this step are similar to those of step S104. Please refer to step S104 for details. No specific limitations are made here.

[0162] Step S114: If the new confidence level is lower than the confidence level threshold, adjust the parameters of the adjusted positioning sensor based on the new confidence level.

[0163] It should be noted that the idea and specific implementation details of this step are similar to those of step S105. Please refer to step S105 for details. No specific limitations are made here.

[0164] Step S115, jump to step S106.

[0165] It should be noted that, to improve the accuracy of the hoisting scheme, an iterative adjustment method was adopted, rather than a single adjustment. The core of this process is that raw data and environmental data are collected at each sampling moment. The role of environmental data is to verify the accuracy of the raw data at the current sampling moment and to influence subsequent sampling moments, which helps improve the accuracy of the raw data at later sampling moments.

[0166] In the previous embodiment, for simplicity, only the raw and environmental data at one sampling moment were shown, along with an example of how this affected the next sampling moment. However, in this improved embodiment, there is a series of sampling moments, each containing both raw and environmental data. This way, the data from each moment is used to calibrate the next sampling, forming a continuous, self-optimizing data calibration process that ensures the hoisting scheme continuously improves and becomes more accurate over time.

[0167] It is evident that by acquiring new environmental data from environmental sensors, the reliability of the new raw data can be calculated. If this new reliability is lower than a predetermined threshold, the parameters of the positioning sensors will be adjusted in order to obtain data with higher reliability in the next sampling. This process is repeated, and through continuous self-optimization, the accuracy of the hoisting scheme is further improved.

[0168] However, in practical applications, if the difference between the new position coordinates and the current position coordinates is very small, it may not be economical to invest computing resources and time in such a small position change. Therefore, in some embodiments, the original step S108 can be replaced by the following step: if it is determined that the difference between the new position coordinates and the current position coordinates is greater than the deviation threshold, a compensation scheme is determined based on the difference between the new position coordinates and the current position coordinates.

[0169] It is evident that a compensation scheme will only be determined based on the difference between the new and current position coordinates when the difference between the old and new position coordinates is greater than a certain predetermined deviation threshold. This is to avoid wasting computational resources and time on minor position changes. Compensation measures will only be taken when the position change is significant and may affect the operation results.

[0170] The following is combined Figure 2 The diagram shown is another flowchart of the intelligent hoisting method for prefabricated buildings, which provides a detailed description of the intelligent hoisting method for prefabricated buildings in this embodiment of the application:

[0171] like Figure 2 As shown, Figure 2 Another flowchart illustrating the intelligent hoisting method for prefabricated buildings provided in this application.

[0172] In actual use, if a preset threshold for the current environment is set, an overly strict fixed threshold may lead to frequent misjudgments, thereby triggering unnecessary operations.

[0173] Therefore, in some embodiments, step S104 may also be: S201, determining whether the current environmental parameter in the current environmental data belongs to the corresponding preset current environmental range; the current environmental parameter is any environmental parameter in the current environmental data.

[0174] It should be noted that the idea and specific implementation details of this step are similar to those of step S105. Please refer to step S105 for details. No specific limitations are made here.

[0175] S202. If it does not belong to the corresponding preset current environment threshold, then the current environment parameter is determined to be either exceeding the preset current environment range or not reaching the preset current environment range.

[0176] S203. If the current environment parameter exceeds the preset current environment range, the difference between the current environment parameter and the minimum value in the preset current environment range is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter.

[0177] It should be noted that inputting the difference between the current environmental parameter and the minimum value in the preset current environmental range into the rule corresponding to the current environmental parameter is to create a buffer space and prevent the parameter value from exceeding the upper limit again in subsequent changes due to insufficient adjustment.

[0178] S204. If the current environment range is not reached, the difference between the current environment parameter and the maximum value in the current environment range is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter.

[0179] Similarly, inputting the difference between the current environmental parameters and the maximum value in the preset current environmental range into the rule corresponding to the current environmental parameters is to create a buffer space and avoid the parameter value failing to reach the lower limit again in subsequent changes due to insufficient adjustment.

[0180] S205, Statistics of all adjusted parameters.

[0181] S206. Adjust the parameters of the positioning sensor based on all adjustment parameters.

[0182] As can be seen, by determining whether the current environmental parameters fall outside the preset environmental range, and whether they exceed or fall below that range, the system can make targeted adjustments to these parameters, thereby optimizing the sensor calibration process and ensuring the continuity and efficiency of operation.

[0183] The following are device embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the device embodiments of this application, please refer to the method embodiments of this application.

[0184] refer to Figure 3 This application provides an intelligent hoisting system for prefabricated buildings, which includes:

[0185] The first acquisition module 301 is used to acquire the current raw data obtained by the positioning sensor from the hoisting component and the current environmental data collected by the environmental sensor at the current sampling time.

[0186] The first coordinate module 302 is used to obtain the current position coordinates of the hoisting component based on the current raw data;

[0187] The first scheme module 303 is used to determine the current hoisting scheme based on the current position coordinates and send the current hoisting scheme to the hoisting component so that the hoisting component can execute the current hoisting scheme; the current hoisting scheme includes the hoisting trajectory and hoisting actions;

[0188] The first credibility module 304 is used to calculate the current credibility of the current original data based on the current environmental data.

[0189] The first adjustment module 305 is used to adjust the parameters of the positioning sensor based on the current confidence level;

[0190] The second acquisition module 306 is used to acquire the new raw data obtained by the adjusted positioning sensor from the hoisting component at the next sampling time.

[0191] The second coordinate module 307 is used to obtain the new position coordinates of the hoisting component based on the new original data;

[0192] The second scheme module 308 is used to determine the compensation scheme based on the difference between the new position coordinates and the current position coordinates;

[0193] The incomplete module 309 is used to determine the remaining unfinished part of the current lifting plan for the lifting component at the current moment;

[0194] The mixing module 310 is used to combine the compensation scheme with the unfinished remaining parts to obtain a new hoisting scheme.

[0195] The sending module 311 is used to send a new hoisting plan to the hoisting component, so that the hoisting component can execute the new hoisting plan.

[0196] In some embodiments, the system further includes:

[0197] The third acquisition module is used to acquire new environmental data collected by the environmental sensor at the next sampling time.

[0198] The second credibility module is used to calculate the new credibility of the new original data based on the new environmental data.

[0199] The second adjustment module is used to adjust the parameters of the positioning sensor based on the new confidence level when the new confidence level is lower than the confidence level threshold.

[0200] The loop module is used to acquire the new raw data obtained by the adjusted positioning sensor from the hoisting component at the next sampling time.

[0201] In some embodiments, the second scheme module is specifically used for:

[0202] If the difference between the new position coordinates and the current position coordinates is greater than the deviation threshold, a compensation scheme is determined based on the difference between the new position coordinates and the current position coordinates.

[0203] In some embodiments, the first credibility module specifically includes:

[0204] The first judgment submodule is used to determine whether the current environment parameter in the current environment data is greater than the corresponding preset current environment threshold; the current environment parameter is any environment parameter in the current environment data;

[0205] The first adjustment module specifically includes:

[0206] The first input submodule is used to input the difference between the current environment parameter and the preset current environment threshold into the rule corresponding to the current environment parameter if the difference is greater than the corresponding preset current environment threshold, so as to obtain the adjustment parameter.

[0207] The first statistics submodule is used to collect statistics on all adjusted parameters;

[0208] The first adjustment submodule is used to adjust the parameters of the positioning sensor based on all adjustment parameters.

[0209] In some embodiments, the first credibility module specifically includes:

[0210] The second judgment submodule is used to determine whether the current environmental parameter in the current environmental data belongs to the corresponding preset current environmental range; the current environmental parameter is any environmental parameter in the current environmental data;

[0211] The third judgment submodule is used to determine whether the current environment parameter exceeds the preset current environment range or does not reach the preset current environment range if it does not belong to the corresponding preset current environment threshold.

[0212] The first adjustment module specifically includes:

[0213] The second input submodule is used to input the difference between the current environment parameter and the minimum value in the preset current environment range into the rule corresponding to the current environment parameter if the current environment parameter exceeds the preset current environment range, so as to obtain the adjustment parameter.

[0214] The second input submodule is used to input the difference between the current environment parameter and the maximum value in the preset current environment range into the rule corresponding to the current environment parameter if the current environment range is not reached, so as to obtain the adjustment parameter.

[0215] The second statistics submodule is used to collect statistics on all adjusted parameters;

[0216] The second adjustment submodule is used to adjust the parameters of the positioning sensor based on all adjustment parameters.

[0217] In some embodiments, the first coordinate module specifically includes:

[0218] The extraction submodule is used to extract all two-dimensional images from the current raw data;

[0219] The matching submodule is used to find corresponding pixels in different two-dimensional images using a stereo matching algorithm.

[0220] The calculation submodule is used to calculate the depth information of pixels based on the triangulation principle;

[0221] The determination submodule is used to determine the current position coordinates of the hoisting component based on the depth information of the pixels and the two-dimensional position of the pixels in the two-dimensional image.

[0222] In some embodiments, the first credibility module is specifically used to: after determining the current hoisting scheme based on the current location coordinates, calculate the current credibility of the current original data based on the current environmental data.

[0223] This application also discloses an intelligent hoisting system for prefabricated buildings. (See reference...) Figure 4 This is a schematic diagram of the physical device of the intelligent hoisting system for prefabricated buildings provided in this application. The computer 400 may include: at least one processor 401, at least one network interface 404, a user interface 403, a memory 405, and at least one communication bus 402.

[0224] The communication bus 402 is used to enable communication between these components.

[0225] The user interface 403 may include a display screen and a camera. Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0226] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0227] The processor 401 may include one or more processing cores. The processor 401 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 405, and by calling data stored in memory 405. Optionally, the processor 401 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 401 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 401.

[0228] The memory 405 may include random access memory (RAM) or read-only memory. Optionally, the memory 405 may include non-transitory computer-readable storage medium. The memory 405 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 405 may also be at least one storage device located remotely from the aforementioned processor 401. (Refer to...) Figure 4 The memory 405, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for intelligent hoisting of prefabricated buildings.

[0229] exist Figure 4In the computer 400 shown, the user interface 403 is mainly used to provide an input interface for the user and obtain user input data; while the processor 401 can be used to call the application program for intelligent hoisting of prefabricated buildings stored in the memory 405. When executed by one or more processors 401, the computer 400 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0230] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0231] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0232] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0233] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0234] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0235] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0236] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A prefabricated building intelligent hoisting method, characterized in that, include: At the current sampling time, acquire the current raw data obtained by the positioning sensor from the hoisting component and the current environmental data collected by the environmental sensor; The current position coordinates of the hoisting component are obtained based on the current raw data; The current lifting plan is determined based on the current position coordinates, and the current lifting plan is sent to the lifting assembly so that the lifting assembly executes the current lifting plan; the current lifting plan includes the lifting trajectory and lifting actions; Calculate the current credibility of the current raw data based on the current environmental data; Adjust the parameters of the positioning sensor based on the current confidence level; The adjusted positioning sensor acquires the new raw data of the hoisting component at the next sampling time. Acquire the new environmental data collected by the environmental sensor at the next sampling time; Calculate the new credibility of the new original data based on the new environmental data; If the new confidence level is lower than the confidence level threshold, adjust the parameters of the adjusted positioning sensor based on the new confidence level; then perform the step of obtaining the new original data of the hoisting component acquired by the adjusted positioning sensor at the next sampling time. The new position coordinates of the hoisting component are obtained based on the new original data; If the difference between the new position coordinates and the current position coordinates is greater than the deviation threshold, a compensation scheme is determined based on the difference between the new position coordinates and the current position coordinates. Determine the remaining unfinished portion of the current lifting scheme for the lifting assembly at the current moment; The compensation scheme is combined with the remaining unfinished portion to obtain a new hoisting scheme; The new lifting plan is sent to the lifting assembly, causing the lifting assembly to execute the new lifting plan.

2. The prefabricated building intelligent hoisting method according to claim 1, characterized in that, The current credibility of the current original data is calculated based on the current environmental data. The step of adjusting the parameters of the positioning sensor based on the current confidence level specifically includes: Determine whether the current environmental parameter in the current environmental data is greater than the corresponding preset current environmental threshold; the current environmental parameter is any environmental parameter in the current environmental data; If the difference between the current environment parameter and the preset current environment threshold is greater than the corresponding current environment threshold, then the difference between the current environment parameter and the preset current environment threshold is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter; Statistics of all adjusted parameters; Adjust the parameters of the positioning sensor based on all adjustment parameters. 3.The intelligent hoisting method for fabricated buildings according to claim 1, characterized in that, The current credibility of the current original data is calculated based on the current environmental data. The step of adjusting the parameters of the positioning sensor based on the current confidence level specifically includes: Determine whether the current environmental parameter in the current environmental data belongs to the corresponding preset current environmental range; the current environmental parameter is any environmental parameter in the current environmental data; If it does not belong to the corresponding preset current environment threshold, then the current environment parameter is determined to be either exceeding the preset current environment range or not reaching the preset current environment range; If the current environment exceeds the preset current environment range, the difference between the current environment parameter and the minimum value in the preset current environment range is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter; If the preset current environment range is not reached, the difference between the current environment parameter and the maximum value in the preset current environment range is input into the rule corresponding to the current environment parameter to obtain the adjustment parameter; Statistics of all adjusted parameters; Adjust the parameters of the positioning sensor based on all adjustment parameters.

4. The intelligent hoisting method for prefabricated buildings according to claim 1, characterized in that, The step of obtaining the current position coordinates of the hoisting component based on the current raw data specifically includes: Extract all two-dimensional images from the current raw data; The corresponding pixels in different two-dimensional images are found using a stereo matching algorithm; The depth information of the pixel is calculated based on the triangulation principle; The current position coordinates of the hoisting component are determined based on the depth information of the pixels and the two-dimensional position of the pixels in the two-dimensional image.

5. The intelligent hoisting method for prefabricated buildings according to claim 1, characterized in that, The step of calculating the current credibility of the current original data based on the current environmental data specifically includes: After determining the current hoisting scheme based on the current location coordinates, the current reliability of the current raw data is calculated based on the current environmental data.

6. A prefabricated building intelligent hoisting system, characterized in that, Performing the method as described in any one of claims 1-5, comprising: The first acquisition module is used to acquire the current raw data obtained by the positioning sensor from the hoisting component and the current environmental data collected by the environmental sensor at the current sampling time. The first coordinate module is used to obtain the current position coordinates of the hoisting component based on the current raw data; The first scheme module is used to determine the current hoisting scheme based on the current position coordinates, and send the current hoisting scheme to the hoisting component, so that the hoisting component executes the current hoisting scheme; the current hoisting scheme includes a hoisting trajectory and hoisting actions; The first credibility module is used to calculate the current credibility of the current original data based on the current environmental data. The first adjustment module is used to adjust the parameters of the positioning sensor based on the current confidence level; The second acquisition module is used to acquire the new raw data obtained by the adjusted positioning sensor from the hoisting component at the next sampling time. The second coordinate module is used to obtain the new position coordinates of the hoisting component based on the new original data; The second scheme module is used to determine a compensation scheme based on the difference between the new position coordinates and the current position coordinates; The incomplete module is used to determine the remaining unfinished part of the current lifting scheme performed by the lifting component at the current moment; A mixing module is used to combine the compensation scheme with the unfinished remaining parts to obtain a new hoisting scheme; The sending module is used to send the new hoisting plan to the hoisting component, so that the hoisting component executes the new hoisting plan.

7. A prefabricated building intelligent hoisting system, characterized in that, include: One or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the prefabricated building intelligent hoisting system to perform the method as described in any one of claims 1-5.

8. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the prefabricated building intelligent hoisting system, the prefabricated building intelligent hoisting system performs the method as described in any one of claims 1-5.

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