Construction site robot scheduling method and device

Abstract

The application discloses a scheduling method and device for a construction site robot, wherein three-dimensional point cloud data of a construction site environment is acquired; the three-dimensional point cloud data is divided into first point cloud data and second point cloud data, wherein the first point cloud data belongs to a ground type; a first plane is generated based on the first point cloud data; the second point cloud data is projected on the first plane to obtain a two-dimensional grid map; and the robot is scheduled based on the two-dimensional grid map. The application can improve the accuracy of scheduling of the construction site robot.

Description

Technical Field

[0001] This application relates to the field of point cloud processing technology, specifically to a scheduling method and device for robots at construction sites. Background Technology

[0002] Construction sites are often chaotic, and maps cannot accurately represent the actual environment. For example, they cannot depict temporary items stored on-site (roadblocks, block stacks, storage yard gates, temporary warning tapes, and restricted areas), which can easily lead to issuing incorrect commands and causing robots to collide with obstacles. In other words, the accuracy of robot scheduling at construction sites is low. Summary of the Invention

[0003] This application provides a method and apparatus for scheduling robots at construction sites, which can improve the accuracy of robot scheduling at construction sites.

[0004] Firstly, the scheduling method for construction site robots provided in this application includes:

[0005] Acquire 3D point cloud data of the construction site environment;

[0006] The 3D point cloud data is divided into first point cloud data and second point cloud data, where the first point cloud data belongs to the ground type;

[0007] Generate the first plane based on the first point cloud data;

[0008] The second point cloud data is projected onto the first plane to obtain a two-dimensional raster map;

[0009] The robot is scheduled based on the two-dimensional grid map.

[0010] Optionally, acquiring the three-dimensional point cloud data of the construction site environment includes:

[0011] The mobile lidar is controlled to scan the construction site environment to obtain the three-dimensional point cloud data of the construction site environment.

[0012] Optionally, generating the first plane based on the first point cloud data includes:

[0013] The first point cloud data is filtered to obtain the third point cloud data;

[0014] The first plane is generated based on the third point cloud data.

[0015] Optionally, the robot scheduling based on the two-dimensional grid map includes:

[0016] Get the task type input by the user;

[0017] The robot is controlled based on the task type.

[0018] Optionally, controlling the robot based on the task type includes:

[0019] When the task type is a material handling task, a first scheduling pop-up window appears on the two-dimensional grid map;

[0020] Detect the coordinates of the first and second clicked images on the two-dimensional grid map by the user.

[0021] Transform the coordinates of the first and second click images to the world coordinate system to obtain the material picking position corresponding to the first click image coordinates and the material unloading position corresponding to the second click image coordinates;

[0022] Enter the material pick-up and unloading locations into the first scheduling pop-up window;

[0023] When the system detects that the user has clicked the confirmation button on the first scheduling pop-up window, it controls the robot to pick up the material from the picking position and move to the unloading position to unload the material.

[0024] Optionally, the scheduling method for the construction site robot includes:

[0025] When the task type is a robot summoning task, a second scheduling pop-up window appears on the two-dimensional grid map;

[0026] Detect the coordinates of the third click image clicked by the user on the two-dimensional grid map;

[0027] Transform the third click image coordinates to the world coordinate system to obtain the target position;

[0028] Enter the target location in the second scheduling pop-up window;

[0029] When the system detects that the user has clicked the confirmation button on the second scheduling pop-up window, it controls the robot to move to the target location.

[0030] Optionally, the scheduling method for the construction site robot includes:

[0031] When the task type is a collection task, a third scheduling pop-up window will appear on the two-dimensional grid map.

[0032] Detect the coordinates of the fourth click image clicked by the user on the two-dimensional grid map;

[0033] Transform the coordinates of the fourth click image to the world coordinate system to obtain the world x-coordinate and world y-coordinate of the collection point corresponding to the coordinates of the fourth click image;

[0034] Input the world x-coordinate and world y-coordinate of the collection point into the third scheduling pop-up window;

[0035] When a user clicks the confirmation button on the third scheduling pop-up, the favorite point is stored.

[0036] Secondly, the scheduling device for construction site robots provided in this application includes:

[0037] The acquisition module is used to acquire three-dimensional point cloud data of the construction site environment;

[0038] The partitioning module is used to divide the 3D point cloud data into first point cloud data and second point cloud data, wherein the first point cloud data belongs to the ground type;

[0039] The generation module is used to generate the first plane based on the first point cloud data;

[0040] The projection module is used to project the second point cloud data onto the first plane to obtain a two-dimensional raster map.

[0041] The scheduling module is used to schedule robots based on the two-dimensional grid map.

[0042] Optionally, acquiring the three-dimensional point cloud data of the construction site environment includes:

[0043] The mobile lidar is controlled to scan the construction site environment to obtain the three-dimensional point cloud data of the construction site environment.

[0044] Optionally, the generation module is used for:

[0045] The first point cloud data is filtered to obtain the third point cloud data;

[0046] The first plane is generated based on the third point cloud data.

[0047] Optionally, the scheduling module is used to:

[0048] Get the task type input by the user;

[0049] The robot is controlled based on the task type.

[0050] Optionally, the scheduling module is used to:

[0051] When the task type is a material handling task, a first scheduling pop-up window appears on the two-dimensional grid map;

[0052] Detect the coordinates of the first and second clicked images on the two-dimensional grid map by the user.

[0053] Transform the coordinates of the first and second click images to the world coordinate system to obtain the material picking position corresponding to the first click image coordinates and the material unloading position corresponding to the second click image coordinates;

[0054] Enter the material pick-up and unloading locations into the first scheduling pop-up window;

[0055] When the system detects that the user has clicked the confirmation button on the first scheduling pop-up window, it controls the robot to pick up the material from the picking position and move to the unloading position to unload the material.

[0056] Optionally, the scheduling module is used for:

[0057] When the task type is a robot summoning task, a second scheduling pop-up window appears on the two-dimensional grid map;

[0058] Detect the coordinates of the third click image clicked by the user on the two-dimensional grid map;

[0059] Transform the third click image coordinates to the world coordinate system to obtain the target position;

[0060] Enter the target location in the second scheduling pop-up window;

[0061] When the system detects that the user has clicked the confirmation button on the second scheduling pop-up window, it controls the robot to move to the target location.

[0062] Optionally, the scheduling module is used for:

[0063] When the task type is a collection task, a third scheduling pop-up window will appear on the two-dimensional grid map.

[0064] Detect the coordinates of the fourth click image clicked by the user on the two-dimensional grid map;

[0065] Transform the coordinates of the fourth click image to the world coordinate system to obtain the world x-coordinate and world y-coordinate of the collection point corresponding to the coordinates of the fourth click image;

[0066] Input the world x-coordinate and world y-coordinate of the collection point into the third scheduling pop-up window;

[0067] When a user clicks the confirmation button on the third scheduling pop-up, the favorite point is stored.

[0068] Thirdly, the electronic device provided in this application includes a memory and a processor. The memory stores a computer program, and the processor is used to run the computer program in the memory to implement the steps in the scheduling method for construction site robots provided in this application.

[0069] Fourthly, the computer-readable storage medium provided in this application stores multiple instructions that are adapted for loading by a processor to implement the steps in the scheduling method for construction site robots provided in this application.

[0070] Fifthly, the computer program product provided in this application includes a computer program or instructions that, when executed by a processor, implement the steps in the scheduling method for construction site robots provided in this application.

[0071] In this application, compared to related technologies, the scheduling method for robots at construction sites includes: acquiring three-dimensional point cloud data of the construction site environment; dividing the three-dimensional point cloud data into first point cloud data and second point cloud data, wherein the first point cloud data belongs to the ground type; generating a first plane based on the first point cloud data; projecting the second point cloud data onto the first plane to obtain a two-dimensional grid map; and scheduling the robot based on the two-dimensional grid map. This application can improve the accuracy of robot scheduling at construction sites. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0073] Figure 1 This is a schematic diagram of a scenario for a scheduling system for construction site robots provided in an embodiment of this application;

[0074] Figure 2 This is a flowchart illustrating one embodiment of the scheduling method for construction site robots provided in this application.

[0075] Figure 3 This is a schematic diagram of a first scheduling pop-up window appearing on a two-dimensional grid map in one embodiment of the scheduling method for construction site robots provided in this application.

[0076] Figure 4 This is a schematic diagram of a second scheduling pop-up window appearing on a two-dimensional grid map in one embodiment of the scheduling method for construction site robots provided in this application.

[0077] Figure 5 This is a schematic diagram of a third scheduling pop-up window appearing on a two-dimensional grid map in one embodiment of the scheduling method for construction site robots provided in this application.

[0078] Figure 6This is a schematic diagram of the structure of the scheduling device for a construction site robot provided in the embodiments of this application;

[0079] Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0080] It should be noted that the principles of this application are illustrated by example in a suitable computing environment. The following description is based on the specific embodiments of this application that are illustrated, and should not be regarded as limiting other specific embodiments not detailed herein.

[0081] In the following description of this application, "some embodiments" are referred to, which describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subset of all possible embodiments, and may be combined with each other without conflict.

[0082] In the following description of this application, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0083] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0084] To improve the scheduling efficiency of robots at construction sites, this application provides a scheduling method, a scheduling device, an electronic device, a computer-readable storage medium, and a computer program product for robots at construction sites. The scheduling method can be executed by the scheduling device or by an electronic device integrating the scheduling device.

[0085] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0086] Please refer to Figure 1 This application also provides a scheduling system for robots at construction sites, such as... Figure 1 As shown, the electronic device 100 is a scheduling system for a construction site robot, and the electronic device 100 integrates the scheduling device for the construction site robot provided in this application.

[0087] Among them, electronic device 100 can be any device equipped with a processor and having processing capabilities, such as mobile electronic devices with processors such as smartphones, tablets, PDAs, laptops, and smart speakers, or fixed electronic devices with processors such as desktop computers, televisions, servers, and industrial equipment.

[0088] In addition, such as Figure 1 As shown, the scheduling system for the construction site robot can also include a memory 200 for storing raw data, intermediate data, and result data.

[0089] In this embodiment of the application, the memory 200 can be a cloud memory. Cloud storage is a new concept that is extended and developed from the concept of cloud computing. A distributed cloud storage system (hereinafter referred to as a storage system) refers to a storage system that uses cluster applications, grid technology and distributed storage file system functions to bring together a large number of storage devices of various types in the network (storage devices are also called storage nodes) through application software or application interfaces to work together to provide data storage and business access functions to the outside world.

[0090] Currently, the storage method of storage systems is as follows: Logical volumes are created. During the creation of a logical volume, physical storage space is allocated to each logical volume. This physical storage space may consist of a single storage device or the disks of several storage devices. Clients store data on a logical volume, which means storing the data on the file system. The file system divides the data into many parts, each part being an object. Each object contains not only the data but also additional information such as a data identifier (ID, ID entity). The file system writes each object to the physical storage space of that logical volume and records the storage location information of each object. Therefore, when a client requests access to data, the file system can allow the client to access the data based on the storage location information of each object.

[0091] The process by which a storage system allocates physical storage space to a logical volume is as follows: the physical storage space is pre-divided into strips according to the capacity estimate of the objects stored in the logical volume (this estimate often has a large margin relative to the actual capacity of the objects to be stored) and the grouping of Redundant Array of Independent Disks (RAID). A logical volume can be understood as a strip, thus allocating physical storage space to the logical volume.

[0092] It should be noted that, Figure 1 The schematic diagram of the scheduling system for construction site robots shown is merely an example. The scheduling system and scenarios for construction site robots described in this application are intended to more clearly illustrate the technical solutions of this application and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of the scheduling system for construction site robots and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0093] The following sections provide detailed descriptions of each example. It should be noted that the sequence numbers of the following embodiments are not intended to limit the preferred order of the embodiments.

[0094] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating one embodiment of the scheduling method for construction site robots provided in this application. Figure 2 As shown, the flowchart of the scheduling method for construction site robots provided in this application is as follows:

[0095] 201. Obtain three-dimensional point cloud data of the construction site environment.

[0096] In this embodiment of the application, acquiring three-dimensional point cloud data of the construction site environment includes: controlling a mobile lidar to scan the construction site environment to obtain three-dimensional point cloud data of the construction site environment. For example, the mobile lidar is installed on a data acquisition vehicle, and the mobile lidar acquires point cloud data as the vehicle moves.

[0097] Specifically, a mobile lidar is used to scan the construction site environment from all directions. This lidar is preferably a mobile backpack-type lidar, which can collect multiple frames of point cloud data during its movement. These frames are then stitched together to form a 3D point cloud dataset of the construction site environment. It should be noted that, in addition to mobile lidar, depth cameras or 3D scanners can also be used to acquire multiple frames of point clouds. Depth cameras include, but are not limited to, those based on optical time-of-flight (TOF) methods such as indirect time-of-flight (iToF) or direct time-of-flight (dToF), binocular vision, or structured light; no specific limitations are imposed here.

[0098] 202. Divide the 3D point cloud data into first point cloud data and second point cloud data, where the first point cloud data belongs to the ground type.

[0099] In one specific embodiment, dividing the three-dimensional point cloud data into first point cloud data and second point cloud data includes: extracting first point cloud data within a preset vertical range on the ground from the three-dimensional point cloud data based on the height of the mobile lidar, and determining the point cloud data of the three-dimensional point cloud data excluding the first point cloud data as the second point cloud data.

[0100] Specifically, when the mobile lidar is set on the top of the data acquisition vehicle, the height of the mobile lidar can be understood as the height of the data acquisition vehicle. For example, if the height of the data acquisition vehicle is 1.6 meters, then when capturing the first point cloud data within the preset longitudinal range of the ground, point cloud data between 1.4 meters and 1.8 meters away from the mobile lidar can be captured.

[0101] In another specific embodiment, 2D images captured by a camera on the vehicle are acquired. A single frame of the 2D image captured by the camera and a single frame of point cloud data captured by a mobile LiDAR on the vehicle are captured from the same viewpoint. Ground region segmentation is performed on the 2D image to obtain segmented ground regions. The 2D image and the corresponding single frame point cloud data are aligned, and point cloud data located within the segmented ground regions are extracted and fused to obtain fourth point cloud data. Based on the height of the mobile LiDAR, fifth point cloud data within a preset longitudinal range on the ground is extracted from the 3D point cloud data. The 3D model formed by multiple 3D point clouds in the fourth point cloud data is determined as the first 3D model, and the 3D model formed by multiple 3D point clouds in the fifth point cloud data is determined as the second 3D model. An overlapping model between the first and second 3D models is obtained. The 3D point clouds in the overlapping model are determined as the first point cloud data, and the point cloud data excluding the first point cloud data is determined as the second point cloud data.

[0102] 203. Generate the first plane based on the first point cloud data.

[0103] In one specific embodiment, generating a first plane based on first point cloud data includes: performing plane fitting on the first point cloud data to obtain the first plane.

[0104] In another specific embodiment, the first point cloud data is filtered to obtain third point cloud data. A first plane is then generated based on the third point cloud data.

[0105] Specifically, the first point cloud data is subjected to pass-through filtering, voxel filtering, statistical filtering, Gaussian filtering, bilateral filtering, and radius filtering to obtain the third point cloud data. The first plane is then generated based on the third point cloud data.

[0106] Pass-through filters retain or remove certain points in point cloud data by setting specific attribute ranges. For example, the range of point cloud data in a certain dimension can be restricted to a specified interval to remove unwanted point cloud data. Voxel filters divide the point cloud into small voxels (cubes) and select a representative point in each voxel, thus achieving downsampling without destroying the geometry of the point cloud. This method reduces the number of points by randomly sampling the point cloud while preserving its overall distribution and shape characteristics. Statistical filters identify and remove outliers by calculating the average and standard deviation of the distances between each point and its nearest neighbors. Specifically, for each point in the point cloud, its K nearest neighbors are found, and the average distance between these neighbors is calculated. Then, a threshold is calculated based on this average and the corresponding standard deviation; all points exceeding this threshold are considered outliers and removed. Gaussian filtering is a smoothing filtering method based on a Gaussian function, suitable for removing random noise and preserving edge information. It achieves denoising by applying Gaussian weights to a weighted average of points within the neighborhood. Bilateral filtering combines spatial distance and pixel similarity, effectively removing noise while preserving edge information. It is particularly suitable for ordered point cloud data. Radius filtering removes all points whose distance exceeds a set radius threshold. This method is simple and effective, and is often used for initial noise reduction.

[0107] In a specific embodiment, generating a first plane based on third point cloud data includes: using the RANSAC (Random Sample Consensus) algorithm to fit the third point cloud data to a plane to obtain the first plane. The RANSAC algorithm estimates the parameters of a mathematical model iteratively from a set of observation datasets containing "outsiders." It is an uncertain algorithm, with a certain probability of yielding a reasonable result; to increase the probability, the number of iterations must be increased. This algorithm was first proposed by Fischler and Bolles in 1981. The basic assumptions of RANSAC are: data consists of "insiders," for example, the distribution of the data can be explained by some model parameters; "outsiders" are data that cannot fit the model; and other data are noise. Outsiders can be caused by: noise extrema; incorrect measurement methods; and incorrect assumptions about the data.

[0108] In another specific embodiment, the RANSAC algorithm is used to perform planar fitting on the third point cloud data to obtain a second plane. The second plane is rotated around a first straight line a preset number of times, each time by a preset angle, to obtain a third plane a preset number of times. The second plane is then rotated around a second straight line a preset number of times, each time by a preset angle, to obtain a fourth plane a preset number of times. The preset angle can be 1 degree or other angles, and the preset number of times can be 5 times or other numbers. Both the first and second straight lines lie on the second plane and are perpendicular to each other. The second plane, the third plane (preset number of times), and the fourth plane (preset number of times) are then defined as multiple fifth planes, from which a first plane is selected.

[0109] Specifically, the first point cloud data is projected onto different fifth planes to obtain different projection areas, resulting in multiple projection areas of the fifth plane. The fifth plane with the largest projection area is then determined as the first plane.

[0110] 204. Project the second point cloud data onto the first plane to obtain a two-dimensional raster map.

[0111] Specifically, each 3D point in the second point cloud data is projected onto the first plane to obtain each 2D point on the 2D raster map, and the mapping relationship between each 3D point in the second point cloud data and each 2D point on the 2D raster map is saved. The 2D raster map is saved as a PGM format image, and the coordinates of each 2D point on the 2D raster map and the coordinates of the corresponding 3D point are stored in YAML format files.

[0112] 205. Robot scheduling based on two-dimensional grid map.

[0113] In this embodiment of the application, scheduling a robot based on a two-dimensional grid map includes: obtaining the task type input by the user; and controlling the robot based on the task type.

[0114] like Figure 3 As shown in the embodiments of this application, controlling the robot based on task type includes:

[0115] (1) When the task type is material handling task, the first scheduling pop-up window will pop up on the two-dimensional grid map.

[0116] like Figure 3 As shown, the first scheduling pop-up window allows users to input the material pickup location, unloading location, AGV number, handling type, and quantity. The AGV number is the robot's identification number.

[0117] (2) Detect the coordinates of the first and second clicked images on the two-dimensional grid map.

[0118] (3) Transform the coordinates of the first click image and the second click image to the world coordinate system to obtain the material picking position corresponding to the first click image coordinate and the material unloading position corresponding to the second click image coordinate.

[0119] Specifically, based on the mapping relationship between the coordinates of the first click image and the 3D points in the second point cloud data and the 2D points on the 2D grid map, the coordinates of the first click image are transformed into the world coordinate system to obtain the material picking position corresponding to the first click image coordinates. Similarly, based on the mapping relationship between the coordinates of the second click image and the 3D points in the second point cloud data and the 2D points on the 2D grid map, the coordinates of the second click image are transformed into the world coordinate system to obtain the material picking position corresponding to the second click image coordinates.

[0120] (4) Input the material pick-up location and unloading location into the first scheduling pop-up window.

[0121] Specifically, the material pick-up and unloading positions are automatically entered into the corresponding positions in the first scheduling pop-up window.

[0122] (5) When the user clicks the confirmation button on the first scheduling pop-up, control the robot to pick up the material from the picking position and move to the unloading position to unload the material.

[0123] like Figure 3 As shown, when the user clicks "Confirm Add", the system detects that the user has clicked the confirmation button on the first scheduling pop-up window.

[0124] In one specific embodiment, different construction floors in the construction site environment correspond to different two-dimensional grid maps. This can be achieved by generating maps for each construction floor separately, resulting in two-dimensional grid maps corresponding to different construction floors. Each construction floor's two-dimensional grid map corresponds to a different floor number. When a user clicks the confirmation button on the first scheduling pop-up window, it is determined whether the user has entered an AGV number in the first scheduling pop-up window. If the user has entered an AGV number, the robot corresponding to that AGV number is controlled to pick up materials from the material-picking position and move to the unloading position to unload. If the user has not entered an AGV number in the first scheduling pop-up window, the floor number corresponding to the two-dimensional grid map is obtained, and the positions of multiple robots on the floor corresponding to that floor are obtained. The robot on the floor corresponding to that floor is controlled to pick up materials from the material-picking position and move to the unloading position to unload.

[0125] like Figure 4 As shown in the embodiments of this application, the scheduling method for robots at construction sites includes:

[0126] (1) When the task type is robot summoning task, a second scheduling pop-up window will appear on the two-dimensional grid map.

[0127] (2) Detect the coordinates of the third click image when the user clicks on the two-dimensional grid map.

[0128] (3) Convert the coordinates of the third click image to the world coordinate system to obtain the target position.

[0129] (4) Input the target location into the second scheduling pop-up window.

[0130] (5) When the user clicks the confirmation button on the second scheduling pop-up, control the robot to move to the target position.

[0131] like Figure 5 As shown in the embodiments of this application, the scheduling method for robots at construction sites includes:

[0132] (1) When the task type is a collection task, a third scheduling pop-up window will appear on the two-dimensional grid map.

[0133] (2) Detect the coordinates of the fourth click image that the user clicks on the two-dimensional grid map.

[0134] (3) Transform the coordinates of the fourth click image to the world coordinate system to obtain the world horizontal and world vertical coordinates of the collection point corresponding to the coordinates of the fourth click image.

[0135] (4) Input the world horizontal and vertical coordinates of the collection point into the third scheduling pop-up window.

[0136] (5) When the user clicks the confirmation button on the third scheduling pop-up, save the favorite point.

[0137] In this application, compared to related technologies, the scheduling method for robots at construction sites includes: acquiring three-dimensional point cloud data of the construction site environment; dividing the three-dimensional point cloud data into first point cloud data and second point cloud data, wherein the first point cloud data belongs to the ground type; generating a first plane based on the first point cloud data; projecting the second point cloud data onto the first plane to obtain a two-dimensional grid map; and scheduling the robot based on the two-dimensional grid map. This application can improve the accuracy of robot scheduling at construction sites.

[0138] This application improves mapping efficiency and avoids repetitive manual coordinate collection. It can realistically display all details of the construction site environment, making it more suitable for scheduling in highly dynamic and complex construction environments. It allows for the rapid acquisition of any world coordinate point within the site environment, accessible directly by clicking on the image.

[0139] To facilitate better implementation of the scheduling method for construction site robots provided in this application, this application also provides a scheduling device for construction site robots based on the aforementioned scheduling method. The meanings of the terms used are the same as in the aforementioned scheduling method for construction site robots; for specific implementation details, please refer to the descriptions in the above method embodiments.

[0140] Please refer to Figure 6 , Figure 6 This is a schematic diagram of the structure of a scheduling device for a construction site robot provided in an embodiment of this application. The scheduling device for the construction site robot may include:

[0141] The acquisition module 701 is used to acquire three-dimensional point cloud data of the construction site environment;

[0142] The partitioning module 702 is used to partition the 3D point cloud data into first point cloud data and second point cloud data, wherein the first point cloud data belongs to the ground type;

[0143] Generation module 703 is used to generate a first plane based on the first point cloud data;

[0144] Projection module 704 is used to project the second point cloud data onto the first plane to obtain a two-dimensional raster map.

[0145] The scheduling module 705 is used to schedule robots based on a two-dimensional grid map.

[0146] Optionally, acquire three-dimensional point cloud data of the construction site environment, including:

[0147] The mobile lidar is controlled to scan the construction site environment and obtain three-dimensional point cloud data of the construction site environment.

[0148] Optionally, a generation module is used for:

[0149] The first point cloud data is filtered to obtain the third point cloud data;

[0150] The first plane is generated based on the third point cloud data.

[0151] Optionally, the scheduling module is used for:

[0152] Get the task type input by the user;

[0153] Controlling robots based on task type.

[0154] Optionally, the scheduling module is used for:

[0155] When the task type is material handling task, the first scheduling pop-up window will appear on the two-dimensional grid map;

[0156] Detect the coordinates of the first and second clicks on the 2D grid map.

[0157] Transform the coordinates of the first and second click images to the world coordinate system to obtain the material picking position corresponding to the first click image coordinates and the material unloading position corresponding to the second click image coordinates;

[0158] Enter the material pick-up and unloading locations into the first scheduling pop-up window;

[0159] When the system detects that the user has clicked the confirmation button on the first scheduling pop-up window, it controls the robot to pick up the material from the picking position and move to the unloading position to unload the material.

[0160] Optionally, the scheduling module is used for:

[0161] When the task type is robot summoning task, a second scheduling pop-up window will appear on the two-dimensional grid map;

[0162] Detect the coordinates of the third click image when the user clicks on a 2D raster map;

[0163] Transform the third click image coordinates to the world coordinate system to obtain the target position;

[0164] Enter the target location in the second dispatch pop-up window;

[0165] When the system detects that the user has clicked the confirmation button on the second scheduling pop-up window, it controls the robot to move to the target location.

[0166] Optionally, the scheduling module is used for:

[0167] When the task type is a favorite task, a third scheduling pop-up window will appear on the two-dimensional grid map;

[0168] Detect the coordinates of the fourth click image on the 2D raster map by the user;

[0169] Transform the coordinates of the fourth click image to the world coordinate system to obtain the world x-coordinate and world y-coordinate of the collection point corresponding to the coordinates of the fourth click image;

[0170] Input the world x-coordinate and world y-coordinate of the collection point into the third scheduling pop-up window;

[0171] When a user clicks the confirmation button on the third scheduling pop-up, the favorite point is saved.

[0172] For details on the implementation of each of the above modules, please refer to the previous examples, which will not be repeated here.

[0173] This application also provides an electronic device, including a memory and a processor, wherein the processor executes the steps in the scheduling method for a construction site robot provided in this embodiment by calling a computer program stored in the memory.

[0174] Please refer to Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0175] The electronic device may include components such as a processor 101 with one or more processing cores, a memory 102 with one or more computer-readable storage media, a power supply 103, and an input unit 104. Those skilled in the art will understand that the electronic device structure shown in the figures does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0176] The processor 101 is the control center of the electronic device, connecting various parts of the device via various interfaces and lines. It executes software programs and / or modules stored in the memory 102, and calls data stored in the memory 102, to perform various functions and process data. Optionally, the processor 101 may include one or more processing cores; alternatively, the processor 101 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 101.

[0177] The memory 102 can be used to store software programs and modules. The processor 101 executes various functional applications and data processing by running the software programs and modules stored in the memory 102. The memory 102 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 102 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 102 may also include a memory controller to provide the processor 101 with access to the memory 102.

[0178] The electronic device also includes a power supply 103 that supplies power to the various components. Optionally, the power supply 103 can be logically connected to the processor 101 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 103 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0179] The electronic device may also include an input unit 104, which can be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0180] Although not shown, the electronic device may also include a display unit 105, an image acquisition component, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 101 in the electronic device will load one or more executable codes corresponding to computer programs into the memory 102 according to the following instructions, and the processor 101 will execute the steps in the scheduling method for construction site robots provided in this application, such as:

[0181] Acquire 3D point cloud data of the construction site environment; divide the 3D point cloud data into first point cloud data and second point cloud data, wherein the first point cloud data belongs to the ground type; generate a first plane based on the first point cloud data; project the second point cloud data onto the first plane to obtain a 2D grid map; schedule robots based on the 2D grid map.

[0182] It should be noted that the electronic device provided in this application embodiment and the scheduling method of the construction site robot in the above embodiment belong to the same concept. The specific implementation process can be found in the above related embodiments, and will not be repeated here.

[0183] This application also provides a computer-readable storage medium storing a computer program thereon. When the computer program stored thereon is executed on the processor of the electronic device provided in the embodiments of this application, the processor of the electronic device executes the steps in the scheduling method for construction site robots provided in this application. The storage medium may be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0184] This application also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform various optional implementations of the above-described scheduling method for construction site robots.

[0185] The above provides a detailed description of the scheduling method and device for construction site robots provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

[0186] It should be noted that when the above embodiments of this application are applied to specific products or technologies, and user-related data is involved, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

Claims

1. A method for scheduling robots at a construction site, characterized in that, include: Acquire 3D point cloud data of the construction site environment; The 3D point cloud data is divided into first point cloud data and second point cloud data, where the first point cloud data belongs to the ground type; A first plane is generated based on the first point cloud data. The first point cloud data is filtered to obtain third point cloud data. The RANSAC algorithm is used to fit the third point cloud data to a plane to obtain a second plane. The second plane is rotated around a first straight line a preset number of times, each time by a preset angle, to obtain a third plane a preset number of times. The second plane is then rotated around a second straight line a preset number of times, each time by a preset angle, to obtain a fourth plane a preset number of times. Both the first and second straight lines lie on the second plane and are perpendicular to each other. The second plane, the third plane a preset number of times, and the fourth plane a preset number of times are defined as multiple fifth planes. The first point cloud data is projected onto different fifth planes to obtain different projection areas, resulting in multiple projection areas of the fifth planes. The fifth plane with the largest projection area is defined as the first plane. The second point cloud data is projected onto the first plane to obtain a two-dimensional raster map; The robot is scheduled based on the two-dimensional grid map.

2. The scheduling method for robots at construction sites according to claim 1, characterized in that, The acquisition of 3D point cloud data of the construction site environment includes: The mobile lidar is controlled to scan the construction site environment to obtain the three-dimensional point cloud data of the construction site environment.

3. The scheduling method for robots at construction sites according to claim 1, characterized in that, The robot scheduling based on the two-dimensional grid map includes: Get the task type input by the user; The robot is controlled based on the task type.

4. The scheduling method for robots at construction sites according to claim 3, characterized in that, Controlling the robot based on the task type includes: When the task type is a material handling task, a first scheduling pop-up window appears on the two-dimensional grid map; Detect the coordinates of the first and second clicked images on the two-dimensional grid map by the user. Transform the coordinates of the first and second click images to the world coordinate system to obtain the material picking position corresponding to the first click image coordinates and the material unloading position corresponding to the second click image coordinates; Enter the material pick-up and unloading locations into the first scheduling pop-up window; When the system detects that the user has clicked the confirmation button on the first scheduling pop-up window, it controls the robot to pick up the material from the picking position and move to the unloading position to unload the material.

5. The scheduling method for robots at construction sites according to claim 3, characterized in that, The scheduling method for robots at construction sites includes: When the task type is a robot summoning task, a second scheduling pop-up window appears on the two-dimensional grid map; Detect the coordinates of the third click image clicked by the user on the two-dimensional grid map; Transform the third click image coordinates to the world coordinate system to obtain the target position; Enter the target location in the second dispatch pop-up window; When the system detects that the user has clicked the confirmation button on the second scheduling pop-up window, it controls the robot to move to the target location.

6. The scheduling method for robots at construction sites according to claim 3, characterized in that, The scheduling method for robots at construction sites includes: When the task type is a collection task, a third scheduling pop-up window will appear on the two-dimensional grid map. Detect the coordinates of the fourth click image clicked by the user on the two-dimensional grid map; Transform the coordinates of the fourth click image to the world coordinate system to obtain the world x-coordinate and world y-coordinate of the collection point corresponding to the coordinates of the fourth click image; Input the world x-coordinate and world y-coordinate of the collection point into the third scheduling pop-up window; When a user clicks the confirmation button on the third scheduling pop-up, the favorite point is stored.

7. A scheduling device for robots at a construction site, characterized in that, include: The acquisition module is used to acquire three-dimensional point cloud data of the construction site environment; The partitioning module is used to divide the 3D point cloud data into first point cloud data and second point cloud data, wherein the first point cloud data belongs to the ground type; A generation module is used to generate a first plane based on first point cloud data. The first point cloud data is filtered to obtain third point cloud data. The RANSAC algorithm is used to perform plane fitting on the third point cloud data to obtain a second plane. The second plane is rotated around a first straight line a preset number of times, each time by a preset angle, to obtain a third plane a preset number of times. The second plane is then rotated around a second straight line a preset number of times, each time by a preset angle, to obtain a fourth plane a preset number of times. Both the first and second straight lines lie on the second plane and are perpendicular to each other. The second plane, the third plane a preset number of times, and the fourth plane a preset number of times are determined as multiple fifth planes, and the first plane is selected from these fifth planes. The projection module is used to project the second point cloud data onto the first plane to obtain a two-dimensional raster map. The scheduling module is used to schedule robots based on the two-dimensional grid map.

8. An electronic device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor running the computer program in the memory to perform the steps in the scheduling method for a construction site robot according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions adapted for loading by a processor to execute the steps of the scheduling method for a construction site robot according to any one of claims 1 to 6.

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