Intelligent beidou pile foundation positioning control, algorithm and system

Abstract

The application discloses an intelligent Beidou pile foundation positioning control, algorithm and system, acquires real-time Beidou positioning data corresponding to a 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, then determines construction environment information in which the task pile machine executes the target task based on the real-time Beidou positioning data and the target position data, determines an optimal path for the task pile machine to move from the real-time position to the target position based on the construction environment information, controls the task pile machine to move from the real-time position to the target position according to the optimal path, effectively realizes path planning of the task pile machine based on intelligent Beidou positioning, realizes automatic displacement of the task pile machine in a complex environment with high precision, high efficiency and low cost, and further improves reliability and construction generalization capability of intelligent Beidou pile foundation positioning control.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of Beidou positioning technology, in particular to an intelligent Beidou pile foundation positioning control, algorithm and system. BACKGROUND

[0002] In solar, wind power plants, reservoir dam fences and highway, railway subgrade engineering, piles as the lower bearing structure are an important part of the engineering. With the rapid development of the national economy, China is carrying out large-scale urbanization construction, the number of various types of buildings and engineering construction is increasing, the engineering difficulty is increasing, and the quality requirement is higher and higher, which greatly promotes the development of various foundation treatment construction technology, and also puts forward higher requirements for engineering equipment. As the main construction equipment, pile driving machinery also faces opportunities and challenges.

[0003] In the related art, a Beidou high-precision positioning terminal is installed on a pile driver, and a designed pile point coordinate is imported into the receiver to guide the pile driver to accurately position the pile foundation to 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, and the automation of pile foundation construction is limited. SUMMARY

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

[0005] In a first aspect, the embodiments of the present application provide an intelligent Beidou pile foundation positioning control algorithm, comprising:

[0006] Obtain 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 executed by the task pile driver;

[0007] Determine 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;

[0008] 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;

[0009] Control the task pile driver to move from the real-time position to the target position according to the optimal path.

[0010] In some embodiments, the real-time Beidou positioning data corresponding to the real-time position of the task pile driver is obtained, comprising:

[0011] acquire initial Beidou positioning data corresponding to the real-time position of the task stake machine, inertial sensing data and angle sensing data corresponding to the real-time attitude of the task stake machine;

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

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

[0014] for any sensing data, acquire the correction weight of the task stake machine at the previous time;

[0015] determine the correction weight of the sensing data at the current time based on the correction weight at the previous time;

[0016] correct the initial Beidou positioning data, the inertial sensing data and the angle sensing data by using the correction weight at the current time corresponding to the sensing data to obtain the real-time Beidou positioning data.

[0017] In some embodiments, the determining the optimal path of the task stake machine from the real-time position to the target position based on the construction environment information comprises:

[0018] acquire the position data of each obstacle to be avoided when the task stake machine moves from the real-time position to the target position;

[0019] determine the obstacle penalty term corresponding to each obstacle and the construction environment complexity weight corresponding to the task stake machine based on the position data of each obstacle;

[0020] calculate the action cost of the task stake machine from the real-time position to the target position based on the obstacle penalty term and the construction environment complexity weight;

[0021] take the path with the lowest action cost as the optimal path of the task stake machine from the real-time position to the target position.

[0022] In some embodiments, it further comprises:

[0023] acquire the number of task stake machines corresponding to the to-be-executed tasks and the task information and construction environment complexity corresponding to each to-be-executed task;

[0024] construct a task progress prediction model based on the number of task stake machines, the task information and the construction environment complexity;

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

[0026] In some embodiments, further comprising:

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

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

[0029] In a second aspect, the embodiments of the present application provide an intelligent Beidou pile foundation positioning control system, comprising:

[0030] An acquisition module is configured to acquire real-time Beidou positioning data corresponding to a 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;

[0031] A determination module is configured to determine construction environment information in which the task pile machine executes the target task based on the real-time Beidou positioning data and the target position data;

[0032] A screening module is configured to determine an optimal path for the task pile machine to move from the real-time position to the target position based on the construction environment information;

[0033] An execution module is configured to control the task pile machine to move from the real-time position to the target position according to the optimal path.

[0034] In a third aspect, the embodiments of the present application provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in the embodiments of the present application.

[0035] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, which stores a computer program, wherein the program is executed by a processor to implement the method described in the embodiments of the present application.

[0036] In a fifth aspect, the embodiments of the present application provide a computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the method described in the embodiments of the present application.

[0037] The intelligent Beidou pile foundation positioning control algorithm provided by the embodiment of the application obtains real-time Beidou positioning data corresponding to a 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, then determines construction environment information in which the task pile machine executes the target task based on the real-time Beidou positioning data and the target position data, determines an optimal path for the task pile machine to move from the real-time position to the target position based on the construction environment information, controls the task pile machine to move from the real-time position to the target position according to the optimal path, effectively realizes path planning of the task pile machine based on intelligent Beidou positioning, and realizes automatic displacement of the task pile machine in a complex environment with high precision, high efficiency and low cost, thereby further improving reliability and construction generalization capability of intelligent Beidou pile foundation positioning control.

[0038] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and / or can be learned by practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0039] Other features, objects, and advantages of the application will become more apparent from the following detailed description when read in connection with the following drawings:

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

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

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

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

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

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

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

[0048] Figure 9 A structural diagram of a computer system of an electronic device or a server suitable for implementing embodiments of the present application is shown. DETAILED DESCRIPTION

[0049] The present application will be further described below in conjunction with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the related application, and not to limit the application. In addition, it should be noted that only the parts related to the application are shown in the drawings for ease of description.

[0050] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0051] The specific implementation environment of the intelligent Beidou pile foundation positioning control algorithm proposed in the present application is described in Figure 1 . Figure 1 A structural diagram of an implementation environment of the intelligent Beidou pile foundation positioning control algorithm provided by the embodiments of the present application is shown.

[0052] As Figure 1 shown, the implementation environment architecture includes a base station, a pile driver, a Beidou positioning terminal, a Beidou antenna, a driver terminal, a user management terminal, and an intelligent Beidou pile driving cloud platform. Among them, the driver terminal and the user management terminal are user login ports of the intelligent Beidou pile driving cloud platform, which can be realized by using independent terminal devices, i.e., setting the driver terminal and the management user terminal, or by using the same terminal device through logging into different account ports to achieve the operation purposes of the driver terminal and the user management terminal.

[0053] The intelligent Beidou pile driving cloud platform uses global navigation system positioning technology and software technology to realize accurate control of the planar position and pile top elevation of the pile driver. Among them, the Beidou positioning terminal (i.e., a Beidou positioning and orientation integrated terminal) and the Beidou antenna are installed in the operating room of the static pressure machine (i.e., the pile driver). The static pressure machine body is a construction machinery for construction of prestressed pipe piles. The present application integrates the pile foundation body into the intelligent Beidou pile driving system by installing relevant equipment such as the Beidou positioning terminal and the Beidou antenna on the pile foundation body.

[0054] The Beidou antenna and the Beidou positioning terminal are used to obtain the position data and the operation angle data of the pile driver in real time, and synchronize the data to the intelligent Beidou pile driving cloud platform. The intelligent Beidou pile driving cloud platform is an Internet platform for receiving, processing and managing data. The driver end performs login operation through the intelligent Beidou pile driving cloud platform, obtains pile driver user information, obtains task pile driver information and the like, and at the same time, the driver end uploads position information, task completion condition and the like to the intelligent Beidou pile driving cloud platform. The user management end can monitor the pile driving operation in real time, including the number of completed pile drivers and the real-time position of the pile driver, and can also count the construction progress. The user management end can count and display the contents including but not limited to the number of current operation pile drivers, the number of current completed pile foundations, the number of current operation construction units, the pile foundation completion ratio of the project, the construction unit progress, the historical completion progress of the pile foundation and the like.

[0055] In a feasible embodiment, as shown in Figure 2 , the user management end is logged in the intelligent Beidou pile driving cloud platform to create a task in the intelligent Beidou pile driving cloud platform, specifically including but not limited to uploading a pile foundation file, setting a task parameter, selecting a planned completion time and the like. Optionally, after the user logs in the user management end, the user can download a pile foundation file template from the intelligent Beidou pile driving cloud platform, and then obtain a pile foundation file corresponding to the task by filling in the pile foundation information corresponding to the task. After the task is created, the target pile driver for executing the task is selected, and the task is assigned.

[0056] The driver end can be a fixed terminal device arranged in the operation room of the pile driver. After the pile driver is started by the construction personnel, the driver end communicates with the Beidou positioning terminal and the angle sensor and the like on the pile driver. After the construction personnel logs in the corresponding driver end account, the driver end communicates with the intelligent Beidou pile driving cloud platform, receives the task to be executed by the pile driver from the task list, and selects the pile foundation and executes the task under the operation of the construction personnel. After the pile foundation task is executed, the task is submitted to the intelligent Beidou pile driving cloud platform.

[0057] After the task is assigned by the management user, the management user can log in the intelligent Beidou pile driving cloud platform at any time to monitor the state of the pile driver executing the task, view the project progress and the like, and download the pile foundation report after the pile driver task is executed, as shown in Figure 3 and Figure 4 .

[0058] Compared with the traditional construction method, the traditional construction method needs to set a full-time measurement personnel to position and loft the pile position, and is greatly affected by the environment. The instrument positioning can only be carried out in the daytime. The traditional construction method has large calculation amount in the early stage, frequent construction lofting in the later stage, low work efficiency and large work intensity. After the intelligent Beidou piling cloud platform is used to manage the construction, the static pressure pipe pile construction has high construction precision and high efficiency, can work for 24 hours without interruption, liberates the measurement personnel from a large amount of measurement and lofting work, can reduce a large number of personnel investment and shorten the construction period.

[0059] Moreover, after the intelligent Beidou piling cloud platform is used to manage the construction, in addition to high construction precision, because the construction data is synchronously stored on the intelligent Beidou piling cloud platform, the construction statistics and the inspection work of the construction data are greatly facilitated, reliable data support is provided for the project acceptance, and the acceptance efficiency is improved.

[0060] Optionally, the intelligent Beidou piling machine cloud platform can be set 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 providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and basic cloud computing services such as big data and artificial intelligence platforms.

[0061] The terminal device (user management end and driver end) and the server are directly or indirectly connected through wired or wireless communication mode. Optionally, the 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 local area network (LAN), metropolitan area network (MAN), wide area network (WAN), mobile, wired or wireless network, private network or any combination of virtual private network.

[0062] The intelligent Beidou pile foundation positioning control algorithm proposed in the present 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] To further illustrate the technical solutions provided by the embodiments of the present application, the following will describe in detail in combination with the drawings and specific embodiments. Although the embodiments of the present application provide the method operation instruction steps as shown in the following embodiments or drawings, more or less operation instruction steps can be included in the method based on conventional or non-creative labor. The execution order of the steps is not limited to the execution order provided by the embodiments of the present application in the logical sense. The method can be executed in sequence or in parallel during actual processing or when the device is executed according to the method sequence shown in the embodiments or drawings.

[0064] Reference is made to Figure 5 , Figure 5 The flowchart of the intelligent Beidou pile foundation positioning control algorithm provided by an embodiment of the present application is shown. As shown in Figure 5 , the method comprises:

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

[0066] Among them, the task pile machine is a static pressure machine to be executed for the target task, the Beidou positioning terminal and the Beidou antenna are arranged in the task pile machine operating room, and the inertial measurement unit IMU (lnertial Measurement Unit) and the angle sensor are arranged on the pile machine arm. Among them, the Beidou positioning terminal and the Beidou antenna are used for real-time positioning of the task pile machine, obtaining the initial Beidou positioning data corresponding to the real-time position of the task pile machine, the inertial measurement unit IMU and the angle sensor are used for determining the real-time attitude of the pile machine arm, and then determining the actual position of the pile foundation task execution end, i.e. 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 machine, the inertial sensing data and the angle sensing data corresponding to the real-time attitude of the task pile machine are obtained, and 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.

[0068] Specifically, the initial Beidou positioning data pGPS=(xGPS,yGPS,zGPS) of the task pile machine is obtained by using the Beidou positioning terminal and the Beidou antenna, and the inertial sensing data IMU=(xIMU,yIMU,zIMU) collected by the inertial measurement unit IMU arranged on the pile machine arm and the angle sensing data θ=(θx,θy,θz) collected by the angle sensor. Then, the initial Beidou positioning data is corrected by using the inertial sensing data and the angle sensing data, for example, using the following formula:

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

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

[0071] Optionally, for any sensor data, the correction weight of the task stake machine at the previous time is obtained, and the correction weight of the sensor data at the current time is determined based on the correction weight at the previous time, so as to correct the initial Beidou positioning data, inertial sensor data and angle sensor data and the corresponding correction weight at the current time to obtain real-time Beidou positioning data.

[0072] Specifically, the correction weight of the sensor data at the current time can be updated by the following formula:

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

[0074] Wherein, W (-1 is the correction weight of the sensor data at the previous time, K ( is the Kalman gain, Z ( is the detection value of the sensor data at the current time, and H ( is the observation matrix.

[0075] Wherein, the initial Beidou positioning data, inertial sensor data and angle sensor data are all sensor data. That is, the correction weights of the initial Beidou positioning data, inertial sensor data and angle sensor data at the current time can be calculated according to the correction weights of the initial Beidou positioning data, inertial sensor data and angle sensor data at the previous time respectively, to obtain W (·GPS , W (·ImU and W (·θ , and then obtain:

[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 machine by using the Beidou positioning terminal and the Beidou antenna, but also correct the initial Beidou positioning data obtained by the intelligent Beidou positioning system of the task pile machine by the inertial sensor measurement unit and the angle sensor arranged on the pile arm to obtain the real-time Beidou positioning data of the task execution end, effectively ensuring the reliability of the pile foundation position positioning. In addition, the present application can correct the real-time weight according to the change of the initial Beidou positioning data, the inertial sensing data and the angle sensing data with time, so that the sensor weight used for positioning information fusion can fully consider the motion trend of the pile machine and the pile arm, further improving 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, determining the construction environment information of the task pile machine executing the target task.

[0079] It should be noted that in the embodiment of the present application, the construction environment information can include but is not limited to weather, geology, obstacles and the like, wherein the obstacle information includes but is not limited to the number of obstacles, the position data of each obstacle and the like.

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

[0081] The geology of the construction environment can be obtained according to the prior environment information, for example, can be obtained by the 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 corresponding to hard geology is relatively high.

[0082] The number and position of the obstacles of the construction environment can be obtained according to the construction environment map, for example, recorded in the pile foundation file uploaded by the management user. For example, the more the number of obstacles, the higher the construction environment complexity, and the larger the space occupied by the obstacles, the higher the construction environment complexity.

[0083] Step 103, based on the construction environment information, determining the optimal path of the task pile machine moving from the real-time position to the target position.

[0084] It should be noted that determining the optimal path of the task pile foundation moving from the real-time position to the target position is the lowest moving cost of the task pile foundation moving from the real-time position to the target position, including but not limited to the shortest distance.

[0085] In one possible embodiment, the position data of each obstacle required to avoid when the task pile machine moves from the real-time position to the target position is acquired, the obstacle penalty term corresponding to each obstacle is determined based on the position data of each obstacle, the construction environment complexity weight corresponding to the task pile machine is determined based on the position data of each obstacle, the action cost of the task pile machine moving from the real-time position to the target position is calculated based on the obstacle penalty term and the construction environment complexity weight, and the path with the lowest action cost is taken as the optimal path of the task pile machine moving from the real-time position to the target position.

[0086] Specifically, the information of obstacles, geology, etc. is acquired according to the aforementioned uploaded pile file, and then the obstacle penalty term corresponding to each obstacle is determined according to the position data of each obstacle. Exemplarily, the penalty term of each obstacle can be calculated by the following formula:

[0087]

[0088] wherein dist(R,obstacle i ) is the distance from the task pile machine R to the ith obstacle.

[0089] Preferably, for the task pile machine, the task execution end, the pile machine boom, the pile machine base, etc. may collide with obstacles during movement, and therefore, the penalty term between each of them and the obstacle needs to be calculated as the judgment node r. That is:

[0090]

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

[0092] f(R)=g(R)+α·h(R)+β·Penalty(R)

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

[0094] After the action cost estimates of multiple routes are acquired, the path with the lowest action cost is taken as the optimal path of the task pile machine moving from the real-time position to the target position.

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

[0096] That is, after the optimal path is obtained, the task pile machine can be controlled to execute the optimal path so that the task pile machine moves 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 movement mechanism of the task pile machine to travel according to the optimal route, controlling the pile arm of the task pile machine to move according to the optimal route, and controlling the task execution end of the task pile machine to move according to the optimal route.

[0098] Therefore, the intelligent Beidou pile foundation positioning control algorithm proposed in the embodiments of the present application obtains real-time Beidou positioning data corresponding to the real-time position of the task pile machine and target position data corresponding to the target task to be executed by the task pile machine, and then determines the construction environment information in which the task pile machine executes the target task based on the real-time Beidou positioning data and the target position data, determines the optimal path for the task pile machine to move from the real-time position to the target position based on the construction environment information, controls the task pile machine to move from the real-time position to the target position according to the optimal path, effectively realizes path planning of the task pile machine based on intelligent Beidou positioning, and realizes high-precision, high-efficiency and low-cost automatic displacement of the task pile machine in a complex environment, thereby further improving the reliability and construction generalization ability 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 sensing data and the angle sensing data, realize accurate 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 the obstacles and the complexity of the construction environment, the optimal path is planned, which can ensure the shortest distance and the lowest cost of the task pile machine to reach the target position, and further save the construction cost.

[0100] In a feasible embodiment, there are multiple task pile machines that can execute tasks in the construction environment, and each construction machine is configured with multiple tasks to be executed to improve the overall completion efficiency of the project by 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 task implementation.

[0101] Specifically, as shown in Figure 6 , it includes:

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

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

[0104] Step 202, constructing a task progress prediction model based on the number of task piles, task information and construction environment complexity.

[0105] Preferably, in the embodiments of the present application, a construction progress dynamic prediction model is established. Specifically, the task progress prediction model is updated based on the task progress change of the current execution task, and the updated task progress prediction model is used to predict the completion time of the current execution task.

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

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

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

[0109] Further, the model parameters are dynamically adjusted by using the following formula:

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

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

[0112] Step 203, using the task progress prediction model to predict the completion time of the current to-be-executed task.

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

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

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

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

[0117] An acquisition module 11 is configured to acquire real-time Beidou positioning data corresponding to a 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;

[0118] A determination module 12 is configured to determine construction environment information in which the task pile machine executes the target task based on the real-time Beidou positioning data and the target position data;

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

[0120] An execution module 14 is configured to control the task pile machine 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 configured to:

[0122] acquire initial Beidou positioning data corresponding to the real-time position of the task pile machine, inertial sensing data corresponding to a real-time attitude of the task pile machine, and angle sensing data;

[0123] correct the initial Beidou positioning data 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 configured to:

[0125] for any sensing data, acquire a correction weight of the task pile machine at a previous time;

[0126] determine a correction weight of the sensing data at a current time based on the correction weight at the previous time;

[0127] correct the initial Beidou positioning data, the inertial sensing data, and the angle sensing data by using the correction weights at the current time corresponding to the initial Beidou positioning data, the inertial sensing data, and the angle sensing data to obtain the real-time Beidou positioning data.

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

[0129] obtain position data of each obstacle that needs to be avoided when the task stake machine moves from the real-time position to the target position;

[0130] determine, based on the position data of each obstacle, an obstacle penalty term corresponding to each obstacle and a construction environment complexity weight corresponding to the task stake machine;

[0131] calculate, based on the obstacle penalty term and the construction environment complexity weight, an action cost of the task stake machine moving from the real-time position to the target position;

[0132] determine, as the optimal path of the task stake machine moving from the real-time position to the target position, the path with the lowest action cost.

[0133] In some embodiments, as shown in FIG. 1, the intelligent Beidou stake foundation positioning control system 10 comprises a prediction module 15. Figure 8

[0134] The prediction module 15 is configured to obtain the number of task stake machines 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] construct a task progress prediction model based on the number of task stake machines, the task information, and the construction environment complexity;

[0136] predict the completion time of the current task to be performed using the task progress prediction model.

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

[0138] update the task progress prediction model based on the task progress change of the current task to be performed;

[0139] predict the completion time of the current task to be performed using the updated task progress prediction model.

[0140] It should be understood that the modules or modules described in the intelligent Beidou stake foundation positioning control system 10 are described with reference to the accompanying drawings and the description of the embodiments. Figure 5 ​The various steps in the described method correspond. Thus, the operations and features described above in relation to the method also apply to the intelligent Beidou pile foundation positioning control system 10 and the modules contained therein, which will not be described again here. The intelligent Beidou pile foundation positioning control system 10 can be pre- implemented in the browser or other security application of the electronic device, or can be loaded into the browser or security application thereof of the electronic device through 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 realize the scheme of the embodiments of the present application.

[0141] In the foregoing detailed description, several modules or units mentioned are 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. Conversely, a module or unit described above can be further divided into a plurality of modules or units to perform the features and functions described above.

[0142] Reference will now be made to the following Figure 9 , Figure 9 A structural schematic diagram of a computer system of an electronic device or server suitable for implementing the embodiments of the present application is shown,

[0143] As Figure 9 shown, the computer system includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 902 or programs loaded from a storage portion 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for 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 portion 906 including a keyboard, a mouse, and the like; an output portion 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a speaker, and the like; a storage portion 908 including a hard disk, and the like; and a communication portion 909 including a network interface card such as a LAN card, a modem, and the like. The communication portion 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as necessary. A removable recording medium 911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 910 as necessary, so that a computer program read therefrom is installed in the storage portion 908 as necessary.

[0145] In particular, according to the embodiments of the present application, the operations described above with reference to the flowcharts Figure 2The described processes can be implemented as computer software programs. For example, embodiments of the present application include a computer program product which includes a computer program tangibly embodied on a computer readable medium, the computer program including program code for executing the methods illustrated in the flowcharts. In such embodiments, the computer program includes program code for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 909 and / or installed from the removable media 911. When the computer program is executed by the central processing unit (CPU) 901, the above-described 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 can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, 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, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as a carrier wave in a propagated data signal, which carries the computer readable program code. Such a propagated data signal can take many forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium that can send, propagate or transfer a program for use by or in connection with an instruction execution system, device or apparatus. The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical cable, RF or the like, or any suitable combination of the above.

[0147] The computer program product of the present application can be a computer program including a plurality of instructions executable by one or more processors of a computer. The computer program product can be stored in the memory 130 of the electronic device 100 or in a memory of a different electronic device. The computer program product can be distributed over network coupled (through a hard-wired or wireless connection) devices, which it causes to perform the instructions. Alternatively, the computer program product can be a dedicated device or memory (e.g., a ROM) including the instructions that are specifically designed for the implementation of the present application, and it does not involve other devices.

[0148] The units or modules described in the embodiments of the present application can be implemented by software, or can be implemented by hardware. The described units or modules can also be arranged in a processor, for example, can be described as: a processor includes an acquisition module, a determination module, a screening module, and an execution module. Among them, the name of these units or modules does not constitute a limitation to the units or modules themselves in some cases, for example, the acquisition module can also be described as "acquiring real-time Beidou positioning data corresponding to the real-time position of the task pile machine and target position data corresponding to the target task to be executed by the task pile machine".

[0149] As another aspect, the present application also provides a computer readable storage medium, which can be included in the electronic device described in the above embodiments, or can exist separately without being assembled into the electronic device. The above computer readable storage medium stores one or more programs, when the 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 merely preferred embodiments of the present application and a description of the principles of the technology used. Those skilled in the art should understand that the disclosed range of the present application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features disclosed in the present application (but not limited to) having similar functions to form technical solutions.

Claims

1. An intelligent Beidou pile foundation positioning control algorithm, characterized in that, The method comprises the following steps: Obtaining real-time Beidou positioning data corresponding to the real-time position of the task stake machine and target position data corresponding to the target task to be executed by the task stake machine; Based on the real-time Beidou positioning data and the target position data, the construction environment information in which the task stake machine executes the target task is determined; Based on the construction environment information, the optimal path for the task stake machine to move from the real-time position to the target position is determined; According to the optimal path, the task stake machine is controlled to move from the real-time position to the target position, Obtaining initial Beidou positioning data corresponding to the real-time position of the task stake machine, inertial sensing data and angle sensing data corresponding to the real-time attitude of the task stake machine; Using the inertial sensing data and the angle sensing data, the initial Beidou positioning data is corrected to obtain the real-time Beidou positioning data, Based on the construction environment information, the optimal path for the task stake machine to move from the real-time position to the target position is determined, comprising: Obtaining the position data of each obstacle that needs to be avoided when the task stake machine moves from the real-time position to the target position; Using the Beidou positioning terminal and the Beidou antenna to obtain the initial Beidou positioning data pGPS=(xGPS,yGPS,zGPS) of the task stake machine, and the inertial sensing data IMU=(xIMU,yIMU,zIMU) collected by the inertial measurement unit IMU arranged on the large arm of the stake machine and the angle sensing data θ=(θx,θy,θz) collected by the angle sensor; then, using the inertial sensing data and the angle sensing data, the initial Beidou positioning data is corrected, Based on the position data of each obstacle, the obstacle penalty term corresponding to each obstacle and the construction environment complexity weight corresponding to the task stake machine are determined; Based on the obstacle penalty term and the construction environment complexity weight, the action cost of the task stake machine moving from the real-time position to the target position is calculated; The path with the lowest action cost is taken as the optimal path for the task stake machine to move from the real-time position to the target position. According to the foregoing, the obstacle and geological information are obtained by uploading the stake file, then the obstacle penalty term corresponding to each obstacle is determined according to the position data of each obstacle, and the following formula is used to calculate the penalty term of each obstacle: ， For the task stake, the task execution end, the stake arm and the stake base are all in the moving process and collide with the obstacles, so the penalty term between them and the obstacles needs to be calculated as a judgment node r, that is, ， On the other hand, according to the number of obstacles, weather and geology, the construction environment complexity weight is determined, and the following formula is used to calculate the action cost of the task stake R to any path: ， Further comprising: Based on the task progress change of the current task to be executed, the task progress prediction model is updated; The completion time of the current task to be executed is predicted by using the updated task progress prediction model, and the task progress prediction model is constructed by using the following formula: Further, the model parameters are dynamically adjusted by using the following formula: ， 。 2. The intelligent Beidou pile foundation positioning control algorithm according to claim 1, characterized in that, The method for correcting the initial Beidou positioning data by using the inertial sensing data and the angle sensing data to obtain the real-time Beidou positioning data comprises: For any sensing data, the modified weight of the task stake machine at the last time is obtained; Based on the modified weight at the last time, the modified weight of the sensing data at the current time is determined; The initial Beidou positioning data, the inertial sensing data and the angle sensing data are corrected by using the corresponding modified weight at the current time, and the real-time Beidou positioning data is obtained.

3. The intelligent Beidou pile foundation positioning control algorithm according to claim 1, characterized in that, The optimal path of the task stake machine from the real-time position to the target position is determined based on the construction environment information, which includes: Obtain the position data of each obstacle that needs to be avoided when the task stake machine moves from the real-time position to the target position; Based on the position data of each obstacle, determine the corresponding obstacle penalty term of each obstacle and the corresponding construction environment complexity weight of the task stake machine; Based on the obstacle penalty term and the construction environment complexity weight, calculate the action cost of the task stake machine from the real-time position to the target position; The path with the lowest action cost is taken as the optimal path of the task stake machine from the real-time position to the target position.

4. The intelligent Beidou pile foundation positioning control algorithm according to claim 1, characterized in that, It also includes: Obtain the number of task stake machines corresponding to the to-be-executed tasks and the task information and construction environment complexity corresponding to each to-be-executed task; Based on the number of task stake machines, the task information and the construction environment complexity, a task progress prediction model is constructed; The completion time of the current to-be-executed task is predicted by using the task progress prediction model.

5. An intelligent Beidou pile foundation positioning control system, characterized in that, It includes: An acquisition module is configured to acquire real-time Beidou positioning data corresponding to a real-time position of a task stake machine and target position data corresponding to a target task to be executed by the task stake machine; A determination module is configured to determine construction environment information based on the real-time Beidou positioning data and the target position data, wherein the task stake machine executes the target task in the construction environment information; A screening module is configured to determine an optimal path of the task stake machine from the real-time position to the target position based on the construction environment information; An execution module is configured to control the task stake machine to move from the real-time position to the target position according to the optimal path, and the control system adopts an intelligent Beidou pile foundation positioning control algorithm as claimed in any one of claims 1-4.

6. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the program to implement the intelligent Beidou pile foundation positioning control algorithm as claimed in any one of claims 1-4.

7. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the intelligent Beidou pile foundation positioning control algorithm as claimed in any one of claims 1-4.

8. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the intelligent Beidou pile foundation positioning control algorithm as claimed in any one of claims 1-4.

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