Beam carrying machine track optimization control method based on digital twinning and unmanned aerial vehicle cooperation

Abstract

The invention discloses a beam carrying machine track optimization control method based on digital twin and unmanned aerial vehicle cooperation. The method comprises the steps of collecting basic data of a construction site, shooting a construction site scene, establishing a construction site panorama and a construction site digital model, obtaining an optimal track of a beam carrying machine, and controlling the beam carrying machine to walk according to the optimal track of the beam carrying machine. According to the beam moving machine trajectory optimization control method based on digital twin and unmanned aerial vehicle cooperation, the virtual model of the construction site is created in combination with the real-time environment data obtained by the unmanned aerial vehicle, a closed-loop control system is formed, dynamic optimization of the beam moving machine trajectory is achieved, the accuracy and efficiency of trajectory planning can be improved, and the construction efficiency is improved. And the operation risk caused by environment complexity can be obviously reduced, so that the safety and the reliability of the whole construction process are improved.

Description

Technical Field

[0001] The present invention relates to the field of optimization of construction equipment at a construction site, and in particular to a trajectory optimization control method for a beam moving machine based on collaboration between a digital twin and an unmanned aerial vehicle. Background Art

[0002] In large-scale construction projects, beam movers play a vital role and are mainly used for lifting, transporting and installing construction materials, especially large-sized beams. Their efficient operation is a key factor in ensuring construction progress and project quality. However, traditional beam mover trajectory optimization faces many challenges. The environment of construction sites is complex and changeable, including factors such as limited space, complex terrain and dense flow of people, making the accuracy and flexibility of trajectory planning a major problem. In addition, existing technologies are often inefficient in optimizing the trajectory of beam movers, lack real-time response capabilities, and are difficult to adapt to the dynamically changing construction environment. These problems urgently need to be solved through innovative technical means. Summary of the invention

[0003] In order to address the shortcomings of the prior art, the present invention provides a beam moving machine trajectory optimization control method based on digital twins and drones. It creates a virtual model of the construction site by combining real-time environmental data obtained by drones, forms a closed-loop control system, and realizes dynamic optimization of the beam moving machine trajectory. It can not only improve the accuracy and efficiency of trajectory planning, but also significantly reduce the operational risks caused by environmental complexity, thereby improving the safety and reliability of the entire construction process.

[0004] The embodiment of the present invention provides the following solution:

[0005] The embodiment of the present invention provides a trajectory optimization control method for a beam moving machine based on collaboration between digital twins and unmanned aerial vehicles, the method comprising:

[0006] Step 1: Collect basic data of the construction site;

[0007] Step 2: Use a camera to shoot the construction site scene, obtain video data and 3D point cloud data in real time, and process to obtain a panoramic view of the construction site and a digital model of the construction site;

[0008] Step 3: Obtain the optimal trajectory of the beam moving machine;

[0009] Step 4: Use the Internet of Things technology to perform data transmission and interaction between physical construction site equipment and the digital model of the construction site, and control the beam mover to move along the optimal trajectory of the beam mover.

[0010] In an optional embodiment, the basic construction site data described in step 1 includes topography, building structure and equipment information.

[0011] In an optional embodiment, the terrain and building structures are collected by a total station.

[0012] In an optional embodiment, the shooting equipment described in step 2 includes a drone equipped with a camera and a laser radar.

[0013] In an optional embodiment, photographing a construction site scene using a drone includes the following process:

[0014] s2.1. Flight path planning: Set the flight path based on the construction site basic data to ensure coverage of the entire construction site and avoid obstacles;

[0015] s2.2, Real-time data acquisition: The UAV collects image data and 3D point cloud data in real time according to the preset flight path, and transmits the image data and 3D point cloud data to the ground control station;

[0016] s2.3. Data processing and analysis: The ground control station processes the image data and 3D point cloud data to generate a panoramic view of the construction site and a digital model of the construction site.

[0017] In an optional embodiment, step two converts the three-dimensional point cloud data into a digital model of the construction site through BIM technology.

[0018] In an optional embodiment, step two also includes sensor equipment pre-deployed at the construction site to obtain construction site environmental information in real time and synchronize it to the digital model of the construction site.

[0019] In an optional embodiment, the construction site environmental information includes temperature, humidity and equipment status.

[0020] In an optional embodiment, step three obtains the optimal trajectory of the beam moving machine through the following process:

[0021] S3.1, let the trajectory of the beam moving machine be T = {(x1, y1, z1, t1), (x2, y2, z2, t2),…, (x i ,y i ,z i ,t i ), …}, (x i ,y i ,z i ) indicates that the beam moving machine is at t i The spatial coordinate position at the moment;

[0022] S3.2. Establish the objective function:

[0023]

[0024] Among them, E(t i ) indicates that the beam moving machine is at ti Energy consumption at any time, Indicates the preset time weight coefficient;

[0025] S3.3. Establish constraint conditions based on the obstacle positions in the digital model of the construction site. Set the obstacle coordinates as (x obs ,y obs ,z obs ), then it satisfies where d safe The preset safety distance;

[0026] S3.4. Optimize the objective function according to the constraints to obtain the optimal trajectory of the beam moving machine.

[0027] In an optional embodiment, when there is updated data in the digital model of the construction site, the optimal trajectory is recalculated through steps S3.1 to S3.4, and the trajectory of the beam moving machine is adjusted by implementing control input.

[0028] The beneficial effects of the present invention based on its technical solution are:

[0029] (1) The present invention provides a beam moving machine trajectory optimization control method based on digital twin and drone collaboration. Based on digital twin technology, high-precision video data and three-dimensional point cloud data are collected using laser radar, total station, drone and other shooting equipment, and a virtual model that is synchronized with the actual physical system in real time is created through BIM technology conversion. Real-time data transmission and interaction, simulation analysis and optimization are realized by combining sensor data. It can comprehensively monitor various environmental data of the construction site and provide an efficient and accurate trajectory planning solution.

[0030] (2) The present invention provides a beam moving machine trajectory optimization control method based on digital twin and UAV collaboration. By introducing the UAV system, the UAV system is used to monitor the construction site environment in real time by using its efficient and flexible data collection capabilities. The UAV is equipped with a high-resolution camera and a laser radar through a preset flight path to collect the environmental data of the construction site in real time, including terrain features, obstacle locations, and construction dynamics. After processing and analyzing these data, high-definition panoramic images and three-dimensional models are generated, ensuring that the trajectory of the beam moving machine can be dynamically adjusted to adapt to the complex and changeable construction environment, significantly improving construction efficiency and safety.

[0031] (3) The present invention provides a beam moving machine trajectory optimization control method based on digital twin and UAV collaboration, which updates environmental data in real time, identifies potential risks and optimization paths, and automatically adjusts the motion trajectory of the beam moving machine to achieve intelligent construction management and optimization. It continuously optimizes trajectory planning and operating efficiency through a closed-loop control system, providing a fully supported intelligent construction solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 A schematic flow chart of a beam moving machine trajectory optimization control method based on collaboration of digital twins and unmanned aerial vehicles provided by the present invention. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention belong to the scope of protection of the embodiments of the present invention.

[0035] Reference Figure 1 , this embodiment provides a trajectory optimization control method for a beam moving machine based on the collaboration of digital twins and unmanned aerial vehicles, the method comprising:

[0036] Step 1: Collect basic data of the construction site, including terrain, building structure and equipment information. The terrain and building structure can be collected by a total station.

[0037] Step 2: Use a drone equipped with a high-resolution camera and LiDAR to shoot the construction site scene, obtain video data and 3D point cloud data in real time, and process it to obtain a panoramic view of the construction site and a digital model of the construction site. This includes the following processes:

[0038] s2.1. Flight path planning: Set the flight path based on the construction site basic data to ensure coverage of the entire construction site and avoid obstacles;

[0039] s2.2, Real-time data acquisition: The UAV collects image data and 3D point cloud data in real time according to the preset flight path, and transmits the image data and 3D point cloud data to the ground control station;

[0040] s2.3. Data processing and analysis: The ground control station processes the image data and 3D point cloud data, stitches and corrects the image data using image processing software, generates a panoramic view of the construction site, and converts the 3D point cloud data into a digital model of the construction site through BIM (Building Information Modeling) technology.

[0041] During this process, sensor equipment pre-deployed at the construction site can also be used to obtain real-time construction site environmental information, including temperature, humidity, and equipment status, which can be synchronized to the construction site digital model to provide more information for subsequent on-site control.

[0042] Step 3: Obtain the optimal trajectory of the beam moving machine through the following process:

[0043] S3.1, let the trajectory of the beam moving machine be T = {(x1, y1, z1, t1), (x2, y2, z2, t2),…, (x i ,y i ,z i ,t i ), …}, (x i ,y i ,z i ) indicates that the beam moving machine is at t i The spatial coordinate position at the moment;

[0044] S3.2. Establish the objective function:

[0045]

[0046] Among them, E(t i ) indicates that the beam moving machine is at t i The energy consumption at the moment can be calculated by the following formula:

[0047] E(t)=p(t)×t1

[0048] P(t) represents the power consumption of the beam moving machine at time t, which is usually determined by the motor power and other load factors, and t1 represents the time period, which can be regarded as the duration of a short period of time; represents the preset time weight coefficient, which is set to 0.5 in this embodiment, indicating the weight balance between time and energy consumption during trajectory optimization. This balance is a reasonable choice for general construction site scenarios because it takes into account both efficiency (time) and energy consumption;

[0049] S3.3. Establish constraint conditions based on the obstacle positions in the digital model of the construction site. Set the obstacle coordinates as (x obs ,y obs ,z obs ), then it satisfies where d safe The preset safety distance;

[0050] S3.4. Optimize the objective function according to the constraints to obtain the optimal trajectory of the beam moving machine.

[0051] When there is updated data in the digital model of the construction site, the optimal trajectory is recalculated through steps S3.1 to S3.4, and the trajectory of the beam mover is adjusted by implementing control input.

[0052] Step 4: Use the Internet of Things technology to perform data transmission and interaction between physical construction site equipment and the digital model of the construction site, and control the beam mover to move along the optimal trajectory of the beam mover.

[0053] During the control process, a closed-loop control mechanism can be established to monitor and adjust the trajectory of the beam mover in real time, while continuously updating the environmental model to form a feedback loop to continuously optimize trajectory planning and operating efficiency. The design of the intelligent collaborative optimization framework includes data collection, digital modeling, environmental simulation and other processes. For the closed-loop control system in the collaborative optimization framework, real-time monitoring and adjustment of the trajectory of the beam mover can be expressed as:

[0054] u(t)=K(x desired (txt))

[0055] Where u(t) represents the control input, K is the control gain matrix, and x desired (t) is the expected trajectory, and x(t) is the current actual trajectory. By continuously adjusting u(t), the beam moving machine is ensured to move along the optimal trajectory.

[0056] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0057] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (modules, systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0058] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0059] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0060] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0061] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A beam moving machine trajectory optimization control method based on digital twin and UAV collaboration, characterized in that: The method comprises: Step 1: Collect basic data of the construction site; Step 2: Use a camera to shoot the construction site scene, obtain video data and 3D point cloud data in real time, and process to obtain a panoramic view of the construction site and a digital model of the construction site; Step 3: Obtain the optimal trajectory of the beam moving machine; Step 4: Use the Internet of Things technology to perform data transmission and interaction between physical construction site equipment and the digital model of the construction site, and control the beam mover to move along the optimal trajectory of the beam mover.

2. The trajectory optimization control method of a beam moving machine based on digital twin and UAV collaboration according to claim 1 is characterized in that: The basic construction site data described in step 1 includes topography, building structure and equipment information.

3. The trajectory optimization control method of the beam moving machine based on the collaboration of digital twin and unmanned aerial vehicle according to claim 2 is characterized in that: The terrain and building structures were collected using a total station.

4. The trajectory optimization control method of a beam moving machine based on digital twin and UAV collaboration according to claim 1 is characterized in that: The shooting equipment described in step 2 includes a drone equipped with a camera and a laser radar.

5. The trajectory optimization control method of the beam moving machine based on the collaboration of digital twin and unmanned aerial vehicle according to claim 4 is characterized in that: Using drones to shoot construction site scenes includes the following processes: s2.

1. Flight path planning: Set the flight path based on the construction site basic data to ensure coverage of the entire construction site and avoid obstacles; s2.2, Real-time data acquisition: The UAV collects image data and 3D point cloud data in real time according to the preset flight path, and transmits the image data and 3D point cloud data to the ground control station; s2.

3. Data processing and analysis: The ground control station processes the image data and 3D point cloud data to generate a panoramic view of the construction site and a digital model of the construction site.

6. The trajectory optimization control method of a beam moving machine based on digital twin and UAV collaboration according to claim 1 is characterized in that: Step 2: Convert the 3D point cloud data into a digital model of the construction site through BIM technology.

7. The trajectory optimization control method of a beam moving machine based on digital twin and UAV collaboration according to claim 1 is characterized in that: Step 2 also includes pre-deploying sensor equipment at the construction site to obtain real-time construction site environmental information and synchronize it to the digital model of the construction site.

8. The trajectory optimization control method for beam moving machine based on digital twin and UAV collaboration according to claim 7 is characterized in that: The construction site environmental information includes temperature, humidity and equipment status.

9. The beam moving machine trajectory optimization control method based on digital twin and UAV collaboration according to claim 1 is characterized in that: Step 3 Obtain the optimal trajectory of the beam moving machine through the following process: S3.1, let the trajectory of the beam moving machine be T = {(x1, y1, z1, t1), (x2, y2, z2, t2),…, (x i ,y i ,z i ,t i ), …}, (x i ,y i ,z i ) indicates that the beam moving machine is at t i The spatial coordinate position at the moment; S3.

2. Establish the objective function: Among them, E(t i ) indicates that the beam moving machine is at t i Energy consumption at any time, Indicates the preset time weight coefficient; S3.

3. Establish constraint conditions based on the obstacle positions in the digital model of the construction site. Set the obstacle coordinates as (x obs ,y obs ,z obs ), then it satisfies where d safe The preset safety distance; S3.

4. Optimize the objective function according to the constraints to obtain the optimal trajectory of the beam moving machine.

10. The trajectory optimization control method of a beam moving machine based on digital twin and UAV collaboration according to claim 9 is characterized in that: When there is updated data in the digital model of the construction site, the optimal trajectory is recalculated through steps S3.1 to S3.4, and the trajectory of the beam mover is adjusted by implementing control input.

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