Intelligent Beidou pile foundation positioning control, algorithm and system

Abstract

The invention discloses an intelligent Beidou pile foundation positioning control method, algorithm and system, and the method comprises the steps: obtaining real-time Beidou positioning data corresponding to the real-time position of a task pile machine and target position data corresponding to a target task to be executed by the task pile machine, and then carrying out the real-time positioning of the task pile machine based on the real-time Beidou positioning data and the target position data; the method comprises the steps of determining information of a construction environment where a task pile machine executes a target task, determining an optimal path of the task pile machine moving from a real-time position to a target position based on the information of the construction environment, and controlling the task pile machine to move from the real-time position to the target position according to the optimal path, so that path planning of the task pile machine based on intelligent Beidou positioning is effectively realized; and high-precision, high-efficiency and low-cost automatic displacement of the task pile machine in a complex environment is realized, so that the reliability and the construction generalization ability of intelligent Beidou pile foundation positioning control are further improved.

Description

Technical Field

[0001] The present disclosure generally relates to the field of Beidou positioning technology, and specifically to an intelligent Beidou pile foundation positioning control, algorithm and system. Background Art

[0002] In solar energy, wind power plants, reservoir dam fences, highway and railway roadbeds and other projects, piles are the lower load-bearing structure and an important part of the project. With the rapid development of the national economy, my country is undergoing large-scale urbanization, the number of various types of construction and engineering construction has increased sharply, the difficulty of the project has increased, and the quality requirements have become higher and higher. While greatly promoting the development of various foundation treatment construction technologies, it has also put forward higher requirements for engineering equipment. As the main construction equipment, pile driving machinery has also ushered in opportunities and challenges.

[0003] Related technologies propose to install the Beidou high-precision positioning terminal on the pile driver, import the designed pile point coordinates into the receiver, and guide the pile driver to accurately position the pile foundation at the point, so as to improve the positioning speed and accuracy of the pile driver. However, the current pile driver can only perform pile foundation tasks in an open environment, which has high restrictions on automated pile foundation construction. Summary of the invention

[0004] In view of the above-mentioned defects or shortcomings in the prior art, it is hoped to provide an intelligent Beidou pile foundation positioning control, algorithm and system that can plan the optimal execution path according to the complexity of the construction environment and ensure that the piling construction can be implemented efficiently and accurately.

[0005] In a first aspect, an embodiment of the present application provides an intelligent Beidou pile foundation positioning control algorithm, including:

[0006] Acquire real-time Beidou positioning data corresponding to the real-time position of the task pile driver and target position data corresponding to the target task to be performed by the task pile driver;

[0007] Based on the real-time Beidou positioning data and the target position data, determining the construction environment information in which the task pile driver performs the target task;

[0008] Based on the construction environment information, determining an optimal path for the task pile driver to move from a real-time position to a target position;

[0009] According to the optimal path, the task pile driver is controlled to move from the real-time position to the target position.

[0010] In some embodiments, the step of obtaining the real-time Beidou positioning data corresponding to the real-time position of the task pile driver includes:

[0011] Acquire initial Beidou positioning data corresponding to the real-time position of the task pile driver, and inertial sensor data and angle sensor data corresponding to the real-time posture of the task pile driver;

[0012] The initial Beidou positioning data is corrected by using the inertial sensing data and the angle sensing data to obtain the real-time Beidou positioning data.

[0013] In some embodiments, the using the inertial sensing data and the angle sensing data to correct the initial Beidou positioning data to obtain the real-time Beidou positioning data includes:

[0014] For any sensor data, obtain the correction weight of the task pile driver at the last moment;

[0015] Determining a correction weight of the sensor data at a current moment based on the correction weight at the previous moment;

[0016] The initial Beidou positioning data, the inertial sensing data, the angle sensing data and their corresponding correction weights at the current moment are used for correction to obtain the real-time Beidou positioning data.

[0017] In some embodiments, determining the optimal path for the task pile driver to move from the real-time position to the target position based on the construction environment information includes:

[0018] Acquire the position data of each obstacle that the task pile driver needs to avoid when moving from the real-time position to the target position;

[0019] Based on the position data of each obstacle, determining the obstacle penalty item corresponding to each obstacle and the construction environment complexity weight corresponding to the task pile driver;

[0020] Based on the obstacle penalty term and the construction environment complexity weight, calculating the action cost of the task pile driver moving from the real-time position to the target position;

[0021] The path with the lowest action cost is used as the optimal path for the task pile driver to move from the real-time position to the target position.

[0022] In some embodiments, it also includes:

[0023] Obtaining the number of task pile drivers corresponding to the tasks to be performed and the task information and construction environment complexity corresponding to each of the tasks to be performed;

[0024] Building a task progress prediction model based on the number of task pile drivers, the task information and the complexity of the construction environment;

[0025] The task progress prediction model is used to predict the completion time of the current task to be executed.

[0026] In some embodiments, it also includes:

[0027] Based on the task progress change of the current task to be executed, updating the task progress prediction model;

[0028] The updated task progress prediction model is used to predict the completion time of the current task to be executed.

[0029] In a second aspect, the embodiment of the present application provides an intelligent Beidou pile foundation positioning control system, including:

[0030] An acquisition module, used to acquire real-time Beidou positioning data corresponding to the real-time position of the task pile driver and target position data corresponding to the target task to be performed by the task pile driver;

[0031] A determination module, used to determine the construction environment information in which the task pile driver performs the target task based on the real-time Beidou positioning data and the target position data;

[0032] A screening module, used to determine the optimal path for the task pile driver to move from the real-time position to the target position based on the construction environment information;

[0033] The execution module is used to control the task pile driver to move from the real-time position to the target position according to the optimal path.

[0034] In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the embodiment of the present application when executing the program.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the embodiment of the present application.

[0036] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, characterized in that when the computer program is executed by a processor, it implements the method described in the embodiment of the present application.

[0037] The intelligent Beidou pile foundation positioning control algorithm proposed in the embodiment of the present application obtains the real-time Beidou positioning data corresponding to the real-time position of the task pile driver and the target position data corresponding to the target task to be executed by the task pile driver, and then determines the construction environment information in which the task pile driver executes the target task based on the real-time Beidou positioning data and the target position data, and determines the optimal path for the task pile driver to move from the real-time position to the target position based on the construction environment information. According to the optimal path, the task pile driver is controlled to move from the real-time position to the target position, effectively realizing the path planning of the task pile driver based on intelligent Beidou positioning, and realizing high-precision, high-efficiency and low-cost automatic displacement of the task pile driver in a complex environment, thereby further improving the reliability and construction generalization capability of the intelligent Beidou pile foundation positioning control.

[0038] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

[0040] Figure 1 The implementation environment architecture diagram of the intelligent Beidou pile foundation positioning control algorithm provided in the embodiment of the present application is shown;

[0041] Figure 2 A schematic diagram of the process of intelligent Beidou pile foundation positioning construction provided by an embodiment of the present application is shown;

[0042] Figure 3 The schematic diagram of the state monitoring of the intelligent Beidou pile foundation positioning construction provided by an embodiment of the present application is shown;

[0043] Figure 4 A schematic diagram of pile position status of intelligent Beidou pile foundation positioning construction provided by an embodiment of the present application is shown;

[0044] Figure 5 A flow chart of an intelligent Beidou pile foundation positioning control algorithm provided by an embodiment of the present application is shown;

[0045] Figure 6 A flow chart of an intelligent Beidou pile foundation positioning control algorithm provided by another embodiment of the present application is shown;

[0046] Figure 7 An exemplary structural block diagram of an intelligent Beidou pile foundation positioning control system provided by an embodiment of the present application is shown;

[0047] Figure 8 An exemplary structural block diagram of an intelligent Beidou pile foundation positioning control system provided in the first embodiment of the present application is shown;

[0048] Fig. 9 A schematic diagram of the structure of a computer system of an electronic device or server suitable for implementing an embodiment of the present application is shown. DETAILED DESCRIPTION

[0049] The present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the relevant invention, rather than to limit the invention. It is also necessary to explain that, for ease of description, only the parts related to the invention are shown in the accompanying drawings.

[0050] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0051] For the specific implementation environment of the intelligent Beidou pile foundation positioning control algorithm proposed in this application, see Figure 1 . Figure 1 The implementation environment architecture diagram of the intelligent Beidou pile foundation positioning control algorithm provided in the embodiment of the present application is shown.

[0052] like Figure 1 As shown in the figure, the implementation environment architecture includes: base station, pile driver, Beidou positioning terminal, Beidou antenna, driver terminal, user management terminal and intelligent Beidou pile driving cloud platform. Among them, the self-end and user management terminal are user login ports of the intelligent Beidou pile driving cloud platform, which can be implemented using independent terminal devices, that is, setting up driver terminal and management user terminal, or using the same terminal device to log in to different account ports to achieve the operation purpose of the driver terminal and user management terminal.

[0053] The intelligent Beidou piling cloud platform uses global navigation system positioning technology and software technology to achieve precise control of the pile driver's operating plane position and pile top elevation. Among them, the Beidou positioning terminal (i.e. Beidou positioning and directional integrated terminal) and the Beidou antenna are installed in the operating room of the static press (i.e. pile driver). The static press body is a construction machinery for constructing prestressed pipe piles. This application incorporates the pile base into the intelligent Beidou piling system by installing relevant equipment on the pile base, such as the Beidou positioning terminal and Beidou antenna.

[0054] Beidou antenna and Beidou positioning terminal are used to obtain the position data and operation angle data of the pile driver in real time, and synchronize the data to the intelligent Beidou piling cloud platform. The intelligent Beidou piling cloud platform is an Internet platform for receiving, processing and managing data. The driver side logs in through the intelligent Beidou piling cloud platform, obtains the pile driver user information, obtains the task pile driver information and other data, and at the same time, the driver side uploads the location information, task completion status and other data to the intelligent Beidou piling cloud platform. The user management side can monitor the operation of the pile driver in real time, including the number of completed pile drivers and the real-time location of the pile driver, and can also count the construction progress. The content that the user management side can count and display includes but is not limited to the number of currently operating pile drivers, the number of currently completed pile foundations, the number of currently operating construction units, the proportion of pile foundation completion of the project, the progress of the construction unit, the historical completion progress of the pile foundation, etc.

[0055] In a possible embodiment, if Figure 2 As shown, log in to the Intelligent Beidou Piling Cloud Platform through the user management port to create a task on the Intelligent Beidou Piling Cloud Platform, including but not limited to uploading pile foundation files, setting task parameters, selecting the planned completion time, etc. Optionally, after logging in to the user management port, the user can download the pile foundation file template from the Intelligent Beidou Piling Cloud Platform, and then obtain the pile foundation file corresponding to the task by filling in the pile foundation information corresponding to the task. After the task is created, select the target pile driver to execute the task and dispatch the task.

[0056] The driver terminal can be a fixed terminal device installed in the pile driver operation room. After the construction personnel start the pile driver, the driver terminal communicates and interacts with the Beidou positioning terminal and angle sensor on the pile driver. After the construction personnel log in to the corresponding driver terminal account, the driver terminal communicates with the intelligent Beidou piling cloud platform, receives the tasks to be performed by the pile driver from the task list, and selects the pile foundation and performs the task under the operation of the construction personnel. After performing the pile foundation task, submit the task to the intelligent Beidou piling cloud platform.

[0057] After assigning a task, the management user can log in to the intelligent Beidou piling cloud platform at any time to monitor the status of the piling machine executing the task, check the project progress, etc., and download the pile foundation report after the piling machine task is completed. Figure 3 and Figure 4 shown.

[0058] Compared with traditional construction methods, traditional construction methods require full-time surveyors to locate and stake out pile positions, and are greatly affected by the environment, and instrument positioning can only be performed during the day. Traditional construction methods require a large amount of calculations in the early stage, and frequent construction and stakeout in the later stage, with low work efficiency and high work intensity. After using the intelligent Beidou piling cloud platform to manage the construction, static pressure pipe pile construction has high construction accuracy and efficiency, and can operate 24 hours a day, freeing surveyors from a large amount of measurement and stakeout work, which can reduce a large number of personnel input and shorten the construction period.

[0059] Moreover, after the construction is managed through the intelligent Beidou piling cloud platform, in addition to the high construction accuracy, the construction data is synchronously stored on the intelligent Beidou piling cloud platform, which greatly facilitates the construction statistics and construction data inspection work, provides reliable data support for project acceptance, and improves acceptance efficiency.

[0060] Optionally, the intelligent Beidou pile driver cloud platform can be set up on a server. The server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, as well as big data and artificial intelligence platforms.

[0061] The terminal devices (user management end and driver end) are directly or indirectly connected to the server through wired or wireless communication. Optionally, the above-mentioned wireless network or wired network uses standard communication technology and / or protocol. The network is usually the Internet, and can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or any combination of a virtual private network.

[0062] The intelligent Beidou pile foundation positioning control algorithm proposed in this application can be implemented by an intelligent Beidou pile foundation positioning control system, and the intelligent Beidou pile foundation positioning control system can be installed on a server.

[0063] In order to further illustrate the technical solution provided by the embodiment of the present application, this is described in detail below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiment of the present application provides the method operation instruction steps shown in the following embodiments or drawings, more or less operation instruction steps may be included in the method based on routine or no creative labor. In the steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided by the embodiment of the present application. The method may be executed in the order of the method shown in the embodiment or drawings or in parallel during the actual processing process or when the device is executed.

[0064] Please refer to Figure 5 , Figure 5 FIG. 1 is a flow chart of an intelligent Beidou pile foundation positioning control algorithm provided by an embodiment of the present application. Figure 5 As shown, the method includes:

[0065] Step 101, obtaining real-time Beidou positioning data corresponding to the real-time position of the task pile driver and target position data corresponding to the target task to be performed by the task pile driver.

[0066] Among them, the task pile driver is a static press to perform the target task. The task pile driver operation room is equipped with a Beidou positioning terminal and Beidou antenna, and the pile driver boom is equipped with an inertial measurement unit IMU (inertial measurement unit) and an angle sensor. Among them, the Beidou positioning terminal and Beidou antenna are used to perform real-time positioning of the task pile driver and obtain the initial Beidou positioning data corresponding to the real-time position of the task pile driver. The inertial measurement unit IMU and the angle sensor are used to determine the real-time posture of the pile driver boom, and then determine the actual position of the pile foundation task execution end, that is, the real-time Beidou positioning data.

[0067] In a feasible embodiment, the initial Beidou positioning data corresponding to the real-time position of the task pile driver, the inertial sensor data and the angle sensor data corresponding to the real-time posture of the task pile driver are obtained, and the initial Beidou positioning data is corrected using the inertial sensor data and the angle sensor data to obtain the real-time Beidou positioning data.

[0068] Specifically, the Beidou positioning terminal and Beidou antenna are used to obtain the initial Beidou positioning data pGPS = (xGPS, yGPS, zGPS) of the task pile driver, as well as the inertial sensor data IMU = (xIMU, yIMU, zIMU) collected by the inertial measurement unit IMU set on the pile driver's arm and the angle sensor data θ = (θx, θy, θz) collected by the angle sensor. Then, the initial Beidou positioning data is corrected using the inertial sensor data and the angle sensor data, for example, using the following formula:

[0069] pfused=W GPS pGPS+WIMU IMU+W θ ·θ

[0070] Among them, W GPS , W IMU and W θ They are the real-time correction weights of the initial Beidou positioning data, inertial sensor data and angle sensor data respectively.

[0071] Optionally, for any sensor data, the correction weight of the task pile driver at the previous moment is obtained, and based on the correction weight of the previous moment, the correction weight of the sensor data at the current moment is determined, so as to use the initial Beidou positioning data, inertial sensor data and angle sensor data and their corresponding correction weights at the current moment to perform corrections and obtain real-time Beidou positioning data.

[0072] Specifically, the following formula can be used to update the correction weight corresponding to the sensor data at the current moment:

[0073] W ( =W (-1 +K ( ·(Z ( -H ( ·W (-1 )

[0074] Among them, W (-1 is the correction weight of the sensor data at the last moment, K ( is the Kalman gain, Z ( is the detection value of the sensor data at the current moment, H ( is the observation matrix.

[0075] Among them, the initial Beidou positioning data, inertial sensor data and angle sensor data are all sensor data. That is to say, the correction weights of the initial Beidou positioning data, inertial sensor data and angle sensor data at the current moment can be calculated according to the correction weights of the initial Beidou positioning data, inertial sensor data and angle sensor data at the previous moment, and W can be obtained. (·GPS , W (·ImU and W (·θ , and then we get:

[0076] pfused=W (·GPS pGPS+W (·ImU IMU+W (·θ ·θ

[0077] Therefore, the embodiment of the present application can not only accurately locate the real-time position of the task pile driver by using the Beidou positioning terminal and the Beidou antenna, but also can correct the initial Beidou positioning data obtained by the task pile driver through the intelligent Beidou positioning system through the inertial sensor measurement unit and the angle sensor set on the pile driver arm, and obtain the real-time Beidou positioning data of the task execution end, which effectively ensures the reliability of the pile foundation position positioning. In addition, the present application can also correct the real-time weight according to the change of the initial Beidou positioning data, inertial sensor data and angle sensor data over time, so that the sensor weight used for positioning information fusion can fully consider the movement trend of the pile driver and the pile driver arm, and further improve the accuracy and reliability of the pile foundation position positioning.

[0078] Step 102, based on the real-time Beidou positioning data and the real-time target position data, determine the construction environment information in which the task pile driver performs the target task.

[0079] It should be noted that in the embodiments of the present application, the construction environment information may include but is not limited to weather, geology, obstacles, etc., wherein the obstacle information includes but is not limited to the number of obstacles, the location data of each obstacle, etc.

[0080] Specifically, the weather of the construction environment can be obtained through the interface API query with the weather management platform, for example, using real-time Beidou positioning data to query real-time weather information from the weather management platform. For example, the complexity of the construction environment corresponding to sunny weather is relatively low, and the complexity of the construction environment corresponding to rainy and snowy weather is relatively high.

[0081] The geology of the construction environment can be obtained based on prior environmental information, for example, it can be obtained through parameter information in the pile foundation file. For example, the construction environment complexity corresponding to soft geology is relatively low, and the construction environment complexity of hard geology is relatively high.

[0082] The number and location of obstacles in the construction environment can be obtained based on the construction environment map, such as recorded in the pile foundation file uploaded by the management user. For example, the more obstacles there are, the more complex the construction environment is, and the larger the space occupied by the obstacles, the more complex the construction environment is.

[0083] Step 103: Based on the construction environment information, determine the optimal path for the task pile driver to move from the real-time position to the target position.

[0084] It should be noted that the optimal path for the task pile foundation to move from the real-time position to the target position is determined to minimize the movement cost paid by the task pile foundation to move from the real-time position to the target position, including but not limited to the shortest distance.

[0085] In a feasible embodiment, the position data of each obstacle that needs to be avoided when the task pile driver moves from the real-time position to the target position is obtained, and based on the position data of each obstacle, the obstacle penalty item corresponding to each obstacle and the construction environment complexity weight corresponding to the task pile driver are determined; based on the obstacle penalty item and the construction environment complexity weight, the action cost of the task pile driver moving from the real-time position to the target position is calculated, and the path with the lowest action cost is used as the optimal path for the task pile driver to move from the real-time position to the target position.

[0086] Specifically, the obstacle, geology and other information are obtained by using the uploaded pile foundation file, and then the obstacle penalty item corresponding to each obstacle is determined according to the position data of each obstacle. For example, the penalty item of each obstacle can be calculated using the following formula:

[0087]

[0088] Among them, dist(R,obstacle i ) is the distance from the task pile driver R to the i-th obstacle.

[0089] Preferably, for the task pile foundation, multiple positions such as the task execution end, the pile driver arm, and the pile driver base may collide with obstacles during the movement process. Therefore, they all need to be used as judgment nodes r to calculate the penalty terms between the obstacles. That is:

[0090]

[0091] On the other hand, the complexity weight of the construction environment is determined according to the number of obstacles, weather and geology, and the action cost of the task pile driver R on any path is calculated using the following formula:

[0092] f(R)=g(R)+α·h(R)+β·Penalty(R)

[0093] Among them, f(R) is the action cost of the current path, g(R) is the estimated cost of moving from the real-time position to the intermediate position, h(R) is the estimated cost of moving from the intermediate state to the target position, Penalty(R) is the obstacle penalty term for executing the path, α is the construction environment complexity weight, and β is the obstacle penalty coefficient.

[0094] After obtaining the action cost estimates of multiple routes, the path with the lowest action cost is used as the optimal path for the task pile driver to move from the real-time position to the target position.

[0095] Step 104, controlling the task pile driver to move from the real-time position to the real-time target position according to the optimal path.

[0096] That is to say, after obtaining the optimal path, the task pile driver can be controlled to execute the optimal path so as to move the task pile driver from the real-time position to the target position. Preferably, the task execution end is moved from the real-time position to the target position.

[0097] Specifically, it includes but is not limited to controlling the moving mechanism of the task pile driver to travel along the optimal route, controlling the pile driver arm of the task pile driver to move along the optimal route, and controlling the task execution end of the task pile driver to move along the optimal route.

[0098] Therefore, the intelligent Beidou pile foundation positioning control algorithm proposed in the embodiment of the present application obtains the real-time Beidou positioning data corresponding to the real-time position of the task pile driver and the target position data corresponding to the target task to be executed by the task pile driver, and then determines the construction environment information in which the task pile driver performs the target task based on the real-time Beidou positioning data and the target position data, and determines the optimal path for the task pile driver to move from the real-time position to the target position based on the construction environment information, and controls the task pile driver to move from the real-time position to the target position according to the optimal path, effectively realizing the path planning of the task pile driver based on intelligent Beidou positioning, and realizing high-precision, high-efficiency and low-cost automatic displacement of the task pile driver in a complex environment, thereby further improving the reliability and construction generalization capability of intelligent Beidou pile foundation positioning control.

[0099] In addition, the present application can further correct the position of the task execution end according to the inertial sensor data and angle sensor data, realize the precise positioning of the task execution end, further improve the positioning accuracy of task execution, and improve the reliability of pile foundation positioning. In addition, according to the information of obstacles and the complexity of the construction environment, the optimal path planning can ensure that the task pile driver completes the path selection to the target position with the shortest distance and the lowest cost, further saving construction costs.

[0100] In a feasible embodiment, there are multiple task pile drivers that can execute tasks in the construction environment, and each construction machine is configured with multiple tasks to be executed to improve the overall project completion efficiency through simultaneous construction. Based on this, the present application further proposes to construct a task progress prediction model to predict the completion of multiple tasks to be executed in the construction environment, so as to monitor and correct the implementation of the tasks.

[0101] Specifically, if Figure 6 As shown, including:

[0102] Step 201, obtaining the number of task pile drivers corresponding to the tasks to be executed and the task information and construction environment complexity corresponding to each task to be executed.

[0103] It should be noted that the task information includes but is not limited to pile foundation task information such as target location, pile foundation length, etc. The complexity of the construction environment can be determined by the aforementioned weather, geology and obstacles.

[0104] Step 202: construct a task progress prediction model based on the number of task pile drivers, task information and construction environment complexity.

[0105] Preferably, in the embodiment of the present application, a dynamic construction progress prediction model is established. Specifically, based on the task progress change of the currently executed task, the task progress prediction model is updated, and the completion time of the currently executed task is predicted using the updated task progress prediction model.

[0106] In a specific embodiment, the task progress prediction model is constructed using the following formula:

[0107] y(t)=β0+β1P(t)+β2N(t)+β3L(t)+β4C(t)+∈(t)

[0108] Among them, β0, β1, β2, β3 and β4 are model parameters, which can be dynamically adjusted according to the modified parameter items, P(t) is the real-time position of the pile foundation of the task, N(t) is the number of pile drivers performing the task, L(t) is the length of the pile foundation in the task, C(t) is the complexity of the construction environment, and ∈(t) is the error term.

[0109] Furthermore, the following formula is used to dynamically adjust the model parameters:

[0110] βk=β k-1 +K k ·(y k -x k β k-1 ))

[0111] Among them, β k-1 is the model parameter of the previous moment, x k =[1,P(t),N(k),L(k),C(k)] T is the input feature vector at the kth time point, K k is the gain matrix.

[0112] Step 203: Use the task progress prediction model to predict the completion time of the current task to be executed.

[0113] That is to say, the task progress prediction model proposed in the embodiment of the present application can update the model parameters according to the progress of the implementation of the actual task, and then generate a task progress prediction model that is consistent with the actual task progress. The task progress prediction model is then used to predict the completion of the task to be executed, which can fully consider the actual construction progress and improve the reliability and accuracy of the prediction.

[0114] It should be noted that although the operations of the method of the present invention are described in a particular order in the drawings, this does not require or imply that the operations must be performed in this particular order or that all illustrated operations must be performed to achieve desired results.

[0115] Figure 7 An exemplary structural block diagram of an intelligent Beidou pile foundation positioning control system provided in an embodiment of the present application is shown.

[0116] like Figure 7 As shown, the intelligent Beidou pile foundation positioning control system 10 includes:

[0117] An acquisition module 11 is used to acquire real-time Beidou positioning data corresponding to the real-time position of the task pile driver and target position data corresponding to the target task to be performed by the task pile driver;

[0118] A determination module 12, for determining the construction environment information in which the task pile driver performs the target task based on the real-time Beidou positioning data and the target position data;

[0119] A screening module 13 is used to determine the optimal path for the task pile driver to move from the real-time position to the target position based on the construction environment information;

[0120] The execution module 14 is used to control the task pile driver to move from the real-time position to the target position according to the optimal path.

[0121] In some embodiments, the acquisition module 11 is further used to:

[0122] Acquire initial Beidou positioning data corresponding to the real-time position of the task pile driver, and inertial sensor data and angle sensor data corresponding to the real-time posture of the task pile driver;

[0123] The initial Beidou positioning data is corrected by using the inertial sensing data and the angle sensing data to obtain the real-time Beidou positioning data.

[0124] In some embodiments, the acquisition module 11 is further used to:

[0125] For any sensor data, obtain the correction weight of the task pile driver at the last moment;

[0126] Determining a correction weight of the sensor data at a current moment based on the correction weight at the previous moment;

[0127] The initial Beidou positioning data, the inertial sensing data, the angle sensing data and their corresponding correction weights at the current moment are used for correction to obtain the real-time Beidou positioning data.

[0128] In some embodiments, the screening module 13 is further configured to:

[0129] Acquire the position data of each obstacle that the task pile driver needs to avoid when moving from the real-time position to the target position;

[0130] Based on the position data of each obstacle, determining the obstacle penalty item corresponding to each obstacle and the construction environment complexity weight corresponding to the task pile driver;

[0131] Based on the obstacle penalty term and the construction environment complexity weight, calculating the action cost of the task pile driver moving from the real-time position to the target position;

[0132] The path with the lowest action cost is used as the optimal path for the task pile driver to move from the real-time position to the target position.

[0133] In some embodiments, Figure 8 As shown, the intelligent Beidou pile foundation positioning control system 10 includes a prediction module 15:

[0134] The prediction module 15 is used to obtain the number of task pile drivers corresponding to the tasks to be performed and the task information and construction environment complexity corresponding to each of the tasks to be performed;

[0135] Building a task progress prediction model based on the number of task pile drivers, the task information and the complexity of the construction environment;

[0136] The task progress prediction model is used to predict the completion time of the current task to be executed.

[0137] In some embodiments, the prediction module 15 is further configured to:

[0138] Based on the task progress change of the current task to be executed, updating the task progress prediction model;

[0139] The updated task progress prediction model is used to predict the completion time of the current task to be executed.

[0140] It should be understood that the modules or modules recorded in the intelligent Beidou pile foundation positioning control system 10 are the same as those in the reference Figure 5The various steps in the described method correspond to each other. Therefore, the operations and features described above for the method are also applicable to the intelligent Beidou pile foundation positioning control system 10 and the modules contained therein, and will not be repeated here. The intelligent Beidou pile foundation positioning control system 10 can be pre-implemented in a browser or other security application of an electronic device, or can be loaded into a browser or its security application of an electronic device by downloading or the like. The corresponding modules in the intelligent Beidou pile foundation positioning control system 10 can cooperate with the modules in the electronic device to implement the solution of the embodiment of the present application.

[0141] For the several modules or units mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0142] Reference below Fig. 9 , Fig. 9 A schematic diagram of the structure of a computer system of an electronic device or server suitable for implementing an embodiment of the present application is shown.

[0143] like Fig. 9 As shown, the computer system includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 902 or the program loaded from the storage part 908 into the random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation instructions of the system are also stored. The CPU 901, the ROM 902 and the RAM 903 are connected to each other through a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0144] The following components are connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed so that a computer program read therefrom is installed into the storage section 908 as needed.

[0145] In particular, according to an embodiment of the present application, the above reference flow chart Figure 2The described process can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flow chart. In such an embodiment, the computer program includes a program code for executing the method shown in the flow chart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 909, and / or installed from the removable medium 911. When the computer program is executed by the central processing unit (CPU) 901, the above-mentioned functions defined in the system of the present application are executed.

[0146] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium such as a computer-readable storage medium that can send, propagate or transmit a program for use by or in conjunction with an instruction execution system, device or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0147] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operating instructions of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the aforementioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, the boxes represented by two connections can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operating instruction, or can be implemented with a combination of dedicated hardware and computer instructions.

[0148] The units or modules involved in the embodiments described in the present application may be implemented by software or hardware. The units or modules described may also be arranged in a processor, for example, may be described as: a processor includes an acquisition module, a determination module, a screening module and an execution module. Wherein, the names of these units or modules do not constitute a limitation on the units or modules themselves under certain circumstances, for example, the acquisition module may also be described as "acquiring the real-time Beidou positioning data corresponding to the real-time position of the task pile driver and the target position data corresponding to the target task to be executed by the task pile driver".

[0149] As another aspect, the present application further provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device. The above computer-readable storage medium stores one or more programs, and when the above programs are used by one or more processors to execute the intelligent Beidou pile foundation positioning control algorithm described in the present application.

[0150] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. An intelligent Beidou pile foundation positioning control algorithm, characterized in that: include: Acquire real-time Beidou positioning data corresponding to the real-time position of the task pile driver and target position data corresponding to the target task to be performed by the task pile driver; Based on the real-time Beidou positioning data and the target position data, determining the construction environment information in which the task pile driver performs the target task; Based on the construction environment information, determining an optimal path for the task pile driver to move from a real-time position to a target position; According to the optimal path, the task pile driver is controlled to move from the real-time position to the target position.

2. The intelligent Beidou pile foundation positioning control algorithm according to claim 1 is characterized in that: The real-time Beidou positioning data corresponding to the real-time position of the task pile driver is obtained, including: Acquire initial Beidou positioning data corresponding to the real-time position of the task pile driver, and inertial sensor data and angle sensor data corresponding to the real-time posture of the task pile driver; The initial Beidou positioning data is corrected by using the inertial sensing data and the angle sensing data to obtain the real-time Beidou positioning data.

3. The intelligent Beidou pile foundation positioning control algorithm according to claim 2 is characterized in that: The method of using the inertial sensor data and the angle sensor data to correct the initial Beidou positioning data to obtain the real-time Beidou positioning data includes: For any sensor data, obtain the correction weight of the task pile driver at the last moment; Determining a correction weight of the sensor data at a current moment based on the correction weight at the previous moment; The initial Beidou positioning data, the inertial sensing data, the angle sensing data and their corresponding correction weights at the current moment are used for correction to obtain the real-time Beidou positioning data.

4. The intelligent Beidou pile foundation positioning control algorithm according to claim 1 is characterized in that: The step of determining the optimal path for the task pile driver to move from the real-time position to the target position based on the construction environment information includes: Acquire the position data of each obstacle that the task pile driver needs to avoid when moving from the real-time position to the target position; Based on the position data of each obstacle, determining the obstacle penalty item corresponding to each obstacle and the construction environment complexity weight corresponding to the task pile driver; Based on the obstacle penalty term and the construction environment complexity weight, calculating the action cost of the task pile driver moving from the real-time position to the target position; The path with the lowest action cost is used as the optimal path for the task pile driver to move from the real-time position to the target position.

5. The intelligent Beidou pile foundation positioning control algorithm according to claim 1 is characterized in that: Also includes: Obtaining the number of task pile drivers corresponding to the tasks to be performed and the task information and construction environment complexity corresponding to each of the tasks to be performed; Building a task progress prediction model based on the number of task pile drivers, the task information and the complexity of the construction environment; The task progress prediction model is used to predict the completion time of the current task to be executed.

6. The intelligent Beidou pile foundation positioning control algorithm according to claim 5 is characterized in that: Also includes: Based on the task progress change of the current task to be executed, updating the task progress prediction model; The updated task progress prediction model is used to predict the completion time of the current task to be executed.

7. An intelligent Beidou pile foundation positioning control system, characterized in that: include: An acquisition module, used to acquire real-time Beidou positioning data corresponding to the real-time position of the task pile driver and target position data corresponding to the target task to be performed by the task pile driver; A determination module, used to determine the construction environment information in which the task pile driver performs the target task based on the real-time Beidou positioning data and the target position data; A screening module, used to determine the optimal path for the task pile driver to move from the real-time position to the target position based on the construction environment information; The execution module is used to control the task pile driver to move from the real-time position to the target position according to the optimal path.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the intelligent Beidou pile foundation positioning control algorithm as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the intelligent Beidou pile foundation positioning control algorithm as described in any one of claims 1-6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the intelligent Beidou pile foundation positioning control algorithm described in any one of claims 1 to 6 is implemented.

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