Ship loader material loading scheduling planning method based on three-dimensional point cloud

Abstract

The invention discloses a ship loader material loading scheduling planning method based on a three-dimensional point cloud, and the method comprises the steps: obtaining the total volume of a to-be-loaded material pile, and the single-time material grabbing volume and unloading stacking area of a ship loader; according to the capacity of the ship warehouse, the total volume of the to-be-loaded material pile and the single-time material grabbing volume and unloading stacking area of the ship loader are combined, a loading planning scheme of the first layer of materials is calculated and generated, and then loading of the first layer of materials in the ship warehouse is completed; the loadable position is determined through the three-dimensional point cloud data of the loaded materials in the ship warehouse, the loading planning scheme of the next layer of materials is calculated in combination with the residual volume of the to-be-loaded material pile and the volume of the materials grabbed by the ship loader at a time, and then loading of the next layer of materials in the ship warehouse is completed. And the material loading dispatching work of the ship loader is repeated until the to-be-loaded material pile is loaded or the ship warehouse capacity reaches the upper limit. The material loading uniformity and loading efficiency of the ship loader can be improved.

Description

Technical Field

[0001] The invention relates to the technical field of intelligent control and ship loaders, and in particular to a material loading scheduling planning method for a ship loader based on three-dimensional point clouds. Background Art

[0002] Ship loader is a large bulk material machine used for loading at bulk material terminals. It is usually composed of multiple parts, including arm belt conveyor, transition belt conveyor, telescopic chute, tail car, running device, gantry, tower, pitch device, slewing device, etc. These parts work together to achieve efficient loading of bulk materials.

[0003] During the material loading process, the ship loader grabs the material through its boom or grab bucket and transports it to the cargo hold of the cargo ship. Specifically, the workflow of the ship loader is as follows: 1) Bulk materials are transported from the storage area to the working area of ​​the ship loader through a conveyor belt system. 2) The grabbing device of the ship loader (such as a grab bucket or a telescopic chute) grabs the material from the conveyor belt. 3) The grabbing device transports the material to the top of the cargo hold of the cargo ship through a rotating device or a moving device. 4) The material is accurately placed in the ship's cargo hold, completing the loading process.

[0004] However, there are still some problems when grabbing and unloading materials into the ship's cargo hold by the ship loader, mainly including uneven loading and no reasonable planning of the loading position of the ship loader each time. On the one hand, the ship loader does not perform precise distribution and control when loading materials, which will lead to uneven distribution of materials on the cargo ship. The uneven distribution will not only affect the navigation stability of the cargo ship, but may also cause long-term damage to the hull structure. Especially when loading heavy materials, uneven loading may cause excessive stress on the local hull, resulting in structural deformation or damage. On the other hand, due to the lack of reasonable planning of the loading position of the ship loader each time, the ship loader will be frequently moved and adjusted during the loading process, thereby reducing the loading efficiency. Summary of the invention

[0005] In view of the above-mentioned deficiencies of the prior art, the technical problem to be solved by the present invention is: how to provide a material loading scheduling planning method for a ship loader based on a three-dimensional point cloud, by generating a scheduling planning scheme for each layer of materials in the ship cargo hold to realize the material grabbing and unloading of the ship loader, thereby improving the uniformity and loading efficiency of the ship loader material loading.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] The material loading scheduling planning method for ship loader based on three-dimensional point cloud includes:

[0008] S1: Obtain the total volume of the material pile to be loaded, as well as the volume of materials grabbed by the ship loader in a single time and the unloading stacking area;

[0009] S2: Calculate and generate a loading plan for the first layer of materials based on the capacity of the ship's cargo hold, the total volume of the material pile to be loaded, the volume of materials grabbed by the ship loader at a time, and the unloading stacking area; the loading plan for the first layer of materials includes the unloading position of the ship loader each time when loading the first layer of materials in the ship's cargo hold;

[0010] S3: Scheduling the ship loader to complete the loading of the first layer of materials in the ship's cargo hold through the loading planning scheme of the first layer of materials;

[0011] S4: Determine the loading position through the three-dimensional point cloud data of the loaded materials in the ship cargo hold, and calculate the loading plan for the next layer of materials in combination with the remaining volume of the material pile to be loaded and the volume of materials grabbed by the ship loader at a time; wherein the loading plan for the next layer of materials includes the unloading position of the ship loader each time when loading the next layer of materials in the ship cargo hold;

[0012] S5: Scheduling the loader to complete the loading of the next layer of materials in the ship's cargo hold through the loading planning scheme of the next layer of materials;

[0013] S6: Repeat steps S4 to S5 until the material pile to be loaded is loaded or the ship's cargo hold capacity reaches an upper limit.

[0014] Preferably, in step S1, the total volume of the material pile to be loaded is determined by using the three-dimensional point cloud data;

[0015] The specific steps are as follows:

[0016] S101: Acquire three-dimensional point cloud data of a material pile to be loaded at different viewing angles or different positions;

[0017] S102: Preprocessing the three-dimensional point cloud data;

[0018] S103: converting the pre-processed three-dimensional point cloud data at different viewing angles or different positions into a unified coordinate system;

[0019] S104: Using a point cloud stitching algorithm to stitch together the three-dimensional point cloud data at different viewing angles or different positions to generate an overall point cloud model of the material;

[0020] S105: based on the difference between the material pile to be loaded and the environment, the material pile to be loaded is segmented from the background of the overall point cloud model of the material in combination with a segmentation algorithm to obtain point cloud data of the material pile;

[0021] S107: reconstructing the segmented point cloud data of the material pile to obtain a three-dimensional model of the material pile;

[0022] S108: Calculate the total volume of the material pile to be loaded based on the reconstructed three-dimensional model of the material pile and in combination with a volume calculation method.

[0023] Preferably, in step S1, the ship loader is subjected to multiple material grabbing and unloading experiments; the volume of material grabbed by the ship loader and the material stacking area after unloading in each experiment are measured; and the average value of the multiple measured material volumes and material stacking areas is taken as the single grabbing material volume and unloading stacking area of ​​the ship loader.

[0024] Preferably, in step S2, a loading plan for the first layer of materials is generated by the following steps:

[0025] S201: dividing the bottom surface of the ship cargo hold into grids according to the unloading and stacking area of ​​the ship loader; wherein the area size of each grid unit in the grid corresponds to the unloading and stacking area of ​​the ship loader at a time;

[0026] S202: Calculate the theoretical volume of the first layer of materials in the ship cargo hold by combining the number of grid units with the volume of materials grabbed by the ship loader at a time; determine whether the theoretical volume of the first layer of materials is greater than the total volume of the material pile to be loaded: if so, execute step S203; otherwise, execute step S204;

[0027] S203: Calculate the required grabbing times of the first layer by combining the total volume of the material pile to be loaded with the volume of the material grabbed by the ship loader at a time; select a corresponding number of grid cells from the grid of the ship cargo hold according to the required grabbing times of the ship loader; generate a loading plan for the first layer of materials using all the selected grid cells as the unloading position of the ship loader when loading the first layer of materials in the ship cargo hold;

[0028] S204: Generate a loading planning scheme for the first layer of materials using all grid cells in the grid as the unloading position of the loading machine when loading the first layer of materials in the ship's cargo hold.

[0029] Preferably, in step S202, the theoretical volume of the first layer of material is calculated by the following formula:

[0030] V1=N×v;

[0031] Where: V m represents the theoretical volume of the first layer of materials; N represents the number of grid units; v represents the volume of materials grabbed by the loader.

[0032] Preferably, in step S203, the required number of grabs of the first layer is calculated by the following formula:

[0033]

[0034] Where: C represents the number of grabs required for the first layer; V allIt represents the total volume of the material pile to be loaded; v represents the volume of the material grabbed by the loader.

[0035] Preferably, in step S203, if the theoretical volume of the first layer of material is greater than the capacity of the ship's cargo hold, the maximum number of grabbing times for the first layer is calculated by combining the capacity of the ship's cargo hold with the volume of material that the loader grabs at a single time; a corresponding number of grid units are selected from the grid of the ship's cargo hold according to the maximum number of grabbing times for the first layer; and a loading planning scheme for the first layer of material is generated using all the selected grid units as the unloading position of the loader when loading the first layer of material in the ship's cargo hold.

[0036] Preferably, in step S4, a loading plan for the next layer of materials is generated through the following steps:

[0037] S401: Acquire the three-dimensional point cloud data of the materials loaded in the ship's cargo hold;

[0038] S402: Identifying the loading position of the next layer of materials in the ship's cargo hold according to the three-dimensional point cloud data of the materials already loaded in the ship's cargo hold;

[0039] S403: Calculate the theoretical volume of the next layer of materials in the ship cargo hold by combining the number of available loading positions with the volume of materials grabbed by the ship loader; determine whether the theoretical volume of the next layer of materials is greater than the remaining volume of the material pile to be loaded: if so, execute step S404; otherwise, execute step S405;

[0040] S404: Calculate the number of times the ship loader needs to grab the next layer of materials by combining the remaining volume of the material pile to be loaded and the volume of materials grabbed by the ship loader at a time; select a corresponding number of loadable positions according to the number of times the next layer of materials needs to be grabbed; generate a loading plan for the next layer of materials with the selected loadable positions as the unloading positions of the ship loader when loading the next layer of materials in the ship's cargo hold;

[0041] S405: Generate a loading planning scheme for the next layer of materials using all available loading positions as the unloading positions of the loading machine when loading the next layer of materials in the ship's cargo hold.

[0042] Preferably, in step S402, the low-lying areas of the loaded materials in the ship's cargo hold as well as the position coordinates and area are identified through the three-dimensional point cloud data of the loaded materials in the ship's cargo hold; the low-lying areas with an area greater than a set area threshold are used as the loading positions for the next layer of materials.

[0043] Preferably, in step S402, the low-lying area of ​​the material in the ship's cargo hold is identified by the following steps:

[0044] S4021: Preprocessing the three-dimensional point cloud data of the materials loaded in the ship's cargo hold;

[0045] S4022: Modeling the preprocessed 3D point cloud data to generate a 3D model of the material surface;

[0046] Generate a 3D model of the material surface using the Delaunay triangulation algorithm. The specific steps are as follows:

[0047] S40221: Select a super triangle containing all point cloud data and add it to the mesh;

[0048] S40222: traverse each data point in the three-dimensional point cloud data and insert it into the current grid in turn;

[0049] S40223: For each newly inserted data point, find the triangle or super triangle where the data point is located, and connect the data point to the three vertices of the triangle to form three new edges;

[0050] S40224: Check whether the new edge meets the Delaunay condition. If there is an edge that does not meet the Delaunay condition, perform an edge flip operation, that is, replace the current triangle with two adjacent triangles until all edges meet the Delaunay condition.

[0051] S40225: Repeat steps S40222 to S40224 until all data points are inserted into the grid and all edges satisfy the Delaunay condition;

[0052] S40226: Remove the initially added super triangle and its associated triangles to generate the final Delaunay triangulated mesh;

[0053] S40227: Perform mesh smoothing and hole filling on the Delaunay triangulated mesh to generate a three-dimensional model of the material surface;

[0054] S4023: Perform morphological analysis on the three-dimensional model of the material surface to identify low-lying areas on the material surface;

[0055] The specific steps for identifying low-lying areas are as follows:

[0056] S40231: Select a projection plane, traverse each vertex in the three-dimensional model of the material surface, calculate its coordinates on the projection plane, and record the height information of each vertex;

[0057] S40232: Fill the blank areas between vertices through interpolation algorithm to generate height map;

[0058] S40233: Preprocessing and morphological operations are performed on the height map; the morphological operations include corrosion operations, dilation operations, opening operations, and closing operations;

[0059] S40234: Apply threshold segmentation technique to divide the height map after preprocessing and morphological operation into low-lying areas and non-low-lying areas;

[0060] S4024: Calculate the location coordinates and area of ​​the low-lying area;

[0061] The specific steps for calculating the location coordinates and area of ​​the low-lying area are as follows:

[0062] S40241: Mark the pixel points in the low-lying area; calculate the coordinates of the centroid of each low-lying area as its position coordinates;

[0063] S40242: Count the number of pixels in the low-lying area, and calculate the area of ​​the low-lying area based on the actual area represented by each pixel.

[0064] Compared with the prior art, the material loading scheduling planning method for ship loader based on three-dimensional point cloud in the present invention has the following beneficial effects:

[0065] The present invention calculates and generates a loading plan for the first layer of materials based on the capacity of the ship's cargo hold combined with the total volume of the material pile to be loaded and the volume of materials grabbed by the loader at a time and the unloading stacking area, thereby realizing the loading of the first layer of materials in the ship's cargo hold. First, by accurately calculating the loading plan for the first layer of materials, it is possible to ensure that the first layer of materials is evenly distributed in the ship's cargo hold. This uniform distribution can effectively avoid the center of gravity shift caused by the concentration of materials in the cargo hold, thereby ensuring the stability of the ship during navigation and reducing the risk of ship tilting due to uneven cargo. Secondly, according to the capacity of the ship's cargo hold and the grabbing capacity of the loader, the unloading position of the loader is accurately planned each time, so that the first layer of materials can achieve a high degree of uniformity in both the horizontal and vertical directions, which is not only beneficial to the stability of the ship, but also improves the effective utilization of the loading space. Finally, through the pre-calculated loading plan, the loader can directly load according to the established path and position, reducing the adjustment and waiting time during the loading process, thereby improving the overall loading efficiency.

[0066] On the basis of realizing the loading of the first layer of materials in the ship cargo hold, the present invention further determines the loading position through the three-dimensional point cloud data of the loaded materials in the ship cargo hold, combines the remaining volume of the material pile to be loaded and the volume of the material grabbed by the loader at a time to calculate the loading planning scheme of the next layer of materials, and finally realizes the loading of each layer of materials. First, as the loading proceeds, the distribution of materials in the ship cargo hold will change. The material status in the cargo hold is monitored in real time through the three-dimensional point cloud data, and the loading planning scheme of the subsequent layers is dynamically adjusted to ensure that each layer of materials can be evenly distributed in the ship cargo hold, and the materials in each layer are evenly distributed, so as to continuously ensure the uniformity and stability of the loading of ship materials. Secondly, based on the three-dimensional point cloud data of the loaded materials, the matching degree of the remaining loading space and the materials to be loaded can be accurately calculated, so as to plan a loading scheme that is more in line with the shape and capacity of the cargo hold, and further improve the uniformity of material loading. Finally, by accurately controlling the loading position and shape of each layer of materials, the gaps between materials can be effectively reduced, and the space utilization rate and loading density of the cargo hold can be improved. At the same time, for material piles with irregular shapes or large volume changes, 3D point cloud data can provide more accurate material shape information, help planning solutions better adapt to complex situations, and avoid stability problems during loading. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to make the purpose, technical solution and advantages of the invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings, in which:

[0068] Figure 1 This is the logical block diagram of the material loading scheduling planning method for ship loader based on three-dimensional point cloud. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but only represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0070] It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. In the description of the present invention, it should be noted that the orientation or position relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. is based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the invention product is usually placed when used, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. In addition, the terms "horizontal", "vertical", etc. do not mean that the components are required to be absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted. In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0071] The following is a further detailed description through specific implementation methods:

[0072] Example:

[0073] This embodiment discloses a material loading scheduling planning method for a ship loader based on three-dimensional point cloud.

[0074] like Figure 1 As shown, the material loading scheduling planning method for a ship loader based on three-dimensional point cloud includes:

[0075] S1: Obtain the total volume of the material pile to be loaded, as well as the volume of materials grabbed by the ship loader in a single time and the unloading stacking area;

[0076] S2: Calculate and generate a loading plan for the first layer of materials based on the capacity of the ship's cargo hold, the total volume of the material pile to be loaded, the volume of materials grabbed by the ship loader at a time, and the unloading stacking area; the loading plan for the first layer of materials includes the unloading position of the ship loader each time when loading the first layer of materials in the ship's cargo hold;

[0077] S3: Scheduling the ship loader to complete the loading of the first layer of materials in the ship's cargo hold through the loading planning scheme of the first layer of materials;

[0078] S4: Determine the loading position through the three-dimensional point cloud data of the loaded materials in the ship cargo hold, and calculate the loading plan for the next layer of materials in combination with the remaining volume of the material pile to be loaded and the volume of materials grabbed by the ship loader at a time; wherein the loading plan for the next layer of materials includes the unloading position of the ship loader each time when loading the next layer of materials in the ship cargo hold;

[0079] S5: Scheduling the loader to complete the loading of the next layer of materials in the ship's cargo hold through the loading planning scheme of the next layer of materials;

[0080] S6: Repeat steps S4 to S5 until the material pile to be loaded is loaded or the ship's cargo hold capacity reaches an upper limit.

[0081] The present invention calculates and generates a loading plan for the first layer of materials based on the capacity of the ship's cargo hold combined with the total volume of the material pile to be loaded and the volume of materials grabbed by the loader at a time and the unloading stacking area, thereby realizing the loading of the first layer of materials in the ship's cargo hold. First, by accurately calculating the loading plan for the first layer of materials, it is possible to ensure that the first layer of materials is evenly distributed in the ship's cargo hold. This uniform distribution can effectively avoid the center of gravity shift caused by the concentration of materials in the cargo hold, thereby ensuring the stability of the ship during navigation and reducing the risk of ship tilting due to uneven cargo. Secondly, according to the capacity of the ship's cargo hold and the grabbing capacity of the loader, the unloading position of the loader is accurately planned each time, so that the first layer of materials can achieve a high degree of uniformity in both the horizontal and vertical directions, which is not only beneficial to the stability of the ship, but also improves the effective utilization of the loading space. Finally, through the pre-calculated loading plan, the loader can directly load according to the established path and position, reducing the adjustment and waiting time during the loading process, thereby improving the overall loading efficiency.

[0082] On the basis of realizing the loading of the first layer of materials in the ship cargo hold, the present invention further determines the loading position through the three-dimensional point cloud data of the loaded materials in the ship cargo hold, combines the remaining volume of the material pile to be loaded and the volume of the material grabbed by the loader at a time to calculate the loading planning scheme of the next layer of materials, and finally realizes the loading of each layer of materials. First, as the loading proceeds, the distribution of materials in the ship cargo hold will change. The material status in the cargo hold is monitored in real time through the three-dimensional point cloud data, and the loading planning scheme of the subsequent layers is dynamically adjusted to ensure that each layer of materials can be evenly distributed in the ship cargo hold, and the materials in each layer are evenly distributed, so as to continuously ensure the uniformity and stability of the loading of ship materials. Secondly, based on the three-dimensional point cloud data of the loaded materials, the matching degree of the remaining loading space and the materials to be loaded can be accurately calculated, so as to plan a loading scheme that is more in line with the shape and capacity of the cargo hold, and further improve the uniformity of material loading. Finally, by accurately controlling the loading position and shape of each layer of materials, the gaps between materials can be effectively reduced, and the space utilization rate and loading density of the cargo hold can be improved. At the same time, for material piles with irregular shapes or large volume changes, 3D point cloud data can provide more accurate material shape information, help planning solutions better adapt to complex situations, and avoid stability problems during loading.

[0083] In the specific implementation process, in step S1, the total volume of the material pile to be loaded is determined through the three-dimensional point cloud data;

[0084] The specific steps are as follows:

[0085] S101: Acquire three-dimensional point cloud data of a material pile to be loaded at different viewing angles or different positions;

[0086] In this embodiment, a high-precision laser radar device is used to perform an all-round scan of the irregular material pile. The laser radar calculates the three-dimensional coordinates of each point on the surface of the material pile by emitting a laser beam and receiving the reflected signal, thereby generating point cloud data.

[0087] S102: performing data preprocessing on the three-dimensional point cloud data; the data preprocessing includes denoising and / or smoothing;

[0088] In this embodiment, the noise points generated by equipment errors, environmental interference and other factors are eliminated by denoising, which can be achieved through filtering algorithms (such as Gaussian filtering, median filtering, etc.) to improve the accuracy of subsequent processing. At the same time, the filtering algorithm is applied to smooth the three-dimensional point cloud data to reduce random errors and noise in the point cloud, making the point cloud data smoother and more continuous.

[0089] S103: converting the pre-processed three-dimensional point cloud data at different viewing angles or different positions into a unified coordinate system to ensure the consistency and comparability of the point cloud data;

[0090] S104: Using a point cloud stitching algorithm to stitch together the three-dimensional point cloud data at different viewing angles or different positions to generate an overall point cloud model of the material;

[0091] In this embodiment, adjacent point cloud data can be automatically matched and fused through point cloud stitching algorithms such as ICP algorithm and NDT algorithm to generate a seamless three-dimensional model.

[0092] S105: based on the difference between the material pile to be loaded and the environment, the material pile to be loaded is segmented from the background of the overall point cloud model of the material in combination with a segmentation algorithm to obtain point cloud data of the material pile;

[0093] In this embodiment, the material pile to be loaded can be separated from the environment by combining environmental differences such as color, texture, height, etc., with algorithms such as clustering-based segmentation and edge detection-based segmentation. The segmentation algorithm needs to accurately identify the boundaries of the material pile and distinguish it from the surrounding environment.

[0094] S107: reconstructing the segmented point cloud data of the material pile to obtain a three-dimensional model of the material pile;

[0095] In this embodiment, cloud data reconstruction can be achieved through various methods such as Delaunay triangulation and meshing. During the reconstruction process, the geometric features and shape details of the material pile need to be retained to facilitate subsequent volume calculation.

[0096] S108: Calculate the total volume of the material pile to be loaded based on the reconstructed three-dimensional model of the material pile and in combination with a volume calculation method.

[0097] In this embodiment, the total volume of the material pile to be loaded can be calculated by volume calculation methods such as convex hull algorithm, model reconstruction method, slicing method and projection algorithm. Convex hull algorithm: first use the convex hull model to approximate the irregular body, and then decompose the convex hull model into multiple simple shapes (such as triangular mesh surfaces), and calculate the volume of these simple shapes and sum them to get the total volume. Model reconstruction method: After obtaining the point cloud data, construct a triangular patch model to approximate the shape of the material pile and calculate the volume of the model. Slicing method: Slice the point cloud data along a certain coordinate axis, calculate the area of ​​each slice, and get the total volume by accumulating the slice volume. Projection method: First project the point cloud data, and then calculate the volume based on the projection result.

[0098] The present invention can accurately calculate the volume of materials through the three-dimensional point cloud data of materials, so as to plan a loading plan that is more in line with the shape and capacity of the warehouse, and further improve the uniformity of material loading. At the same time, for material piles with irregular shapes or large volume changes, the three-dimensional point cloud data can provide more accurate material morphology information, help the scheduling planning plan better adapt to complex situations, and avoid stability problems during loading.

[0099] During the specific implementation process, for (each or each) ship loader, multiple material grabbing and unloading experiments are carried out using the materials to be loaded; the volume of materials grabbed by the ship loader in each experiment and the material stacking area after unloading are measured; the average value of the material volume and material stacking area measured multiple times is taken as the single grabbing material volume and unloading stacking area of ​​the ship loader.

[0100] In this embodiment, the volume of materials grabbed by the ship loader can be obtained by loading and measuring the container. For the material stacking area: the material stacking shape after the ship loader unloads is approximated as a cone, and then the bottom area of ​​the cone is calculated as the material stacking area. Therefore, when calculating the bottom area, it is necessary to regard the bottom of the material pile as a perfect circle, and only the diameter of the bottom of the material pile needs to be measured.

[0101] In the actual material loading process, for granular or fixed-volume (such as box) materials, the volume of materials grabbed by the loader each time and the stacking area of ​​the unloaded materials, that is, the occupied area, are close or the same. Based on this feature, the volume and area of ​​materials grabbed and unloaded by the loader in a single time can be effectively quantified, and then the volume of materials grabbed by the loader in a single time and the stacking area of ​​unloaded materials can be used as a benchmark to conduct quantitative analysis of the entire material loading process. In this way, each action of the loader can be accurately planned, thereby better and more accurately realizing the scheduling plan of material loading and improving the effective utilization rate of loading space and loading efficiency.

[0102] In the specific implementation process, in step S2, the loading plan for the first layer of materials is generated through the following steps:

[0103] S201: dividing the bottom surface of the ship cargo hold into grids according to the unloading and stacking area of ​​the ship loader; wherein the area size of each grid unit in the grid corresponds to the unloading and stacking area of ​​the ship loader at a time;

[0104] S202: Calculate the theoretical volume of the first layer of materials in the ship cargo hold by combining the number of grid units with the volume of materials grabbed by the ship loader at a time; determine whether the theoretical volume of the first layer of materials is greater than the total volume of the material pile to be loaded: if so (indicating that under the loading of the ship loader, only loading the first layer can complete the loading of the material pile to be loaded), execute step S203; otherwise (indicating that under the loading of the ship loader, multiple layers need to be loaded to complete the loading of the material pile to be loaded), execute step S204;

[0105] S203: Calculate the required grabbing times of the first layer by combining the total volume of the material pile to be loaded with the volume of the material grabbed by the ship loader at a time; select a corresponding number of grid cells from the grid of the ship cargo hold according to the required grabbing times of the ship loader; generate a loading plan for the first layer of materials using all the selected grid cells as the unloading position of the ship loader when loading the first layer of materials in the ship cargo hold;

[0106] In this embodiment, when selecting grid units, grid units are selected in sequence in a manner of spreading from the center position of the ship cargo hold grid to the surrounding areas as the position of each unloading of the ship loader. The purpose of this is to ensure that the material is loaded in the middle position of the ship cargo hold as much as possible, and to avoid the problem of unbalanced and uneven material loading caused by all the materials being loaded on one side of the ship cargo hold.

[0107] S204: Generate a loading planning scheme for the first layer of materials using all grid cells in the grid as the unloading position of the loading machine when loading the first layer of materials in the ship's cargo hold.

[0108] In the specific implementation process, in step S202, the theoretical volume of the first layer of material is calculated by the following formula:

[0109] V1=N×v;

[0110] Where: V m represents the theoretical volume of the first layer of materials; N represents the number of grid units; v represents the volume of materials grabbed by the loader.

[0111] In the specific implementation process, in step S203, the required number of grabs of the first layer is calculated by the following formula:

[0112]

[0113] Where: C represents the number of grabs required for the first layer; V all It represents the total volume of the material pile to be loaded; v represents the volume of the material grabbed by the loader.

[0114] The present invention uses the volume of materials grabbed by the ship loader at a time and the unloading stacking area as a benchmark to perform quantitative analysis on the entire material loading process, and takes into account the total volume of the material pile to be loaded during the planning process, so that the scheduling planning of material loading can be better and more accurately realized, thereby improving the effective utilization rate of the loading space and the loading efficiency.

[0115] During the specific implementation process, in step S203, if the theoretical volume of the first layer of materials is greater than the capacity of the ship's cargo hold, the maximum number of grabbing times for the first layer is calculated by combining the capacity of the ship's cargo hold with the volume of materials that the loader grabs at a single time; a corresponding number of grid cells are selected from the grid of the ship's cargo hold according to the maximum number of grabbing times for the first layer; and a loading planning scheme for the first layer of materials is generated using all the selected grid cells as the unloading position of the loader when loading the first layer of materials in the ship's cargo hold.

[0116] In this embodiment, the maximum grabbing times of the first layer is calculated by dividing the capacity of the ship's cargo hold by the volume of materials grabbed by the ship loader in a single time.

[0117] The present invention further considers the capacity of the ship's cargo hold during the planning process, so that the scheduling planning of material loading can be better and more accurately realized, thereby improving the effective utilization rate of the loading space and the loading efficiency.

[0118] In the specific implementation process, in step S4, the loading plan for the next layer of materials is generated through the following steps:

[0119] S401: Acquire the three-dimensional point cloud data of the materials loaded in the ship's cargo hold;

[0120] In this embodiment, a laser scanner or other high-precision 3D scanning equipment is used to perform a full-scale scan of the material pile in the ship's cargo hold to obtain detailed 3D point cloud data. Such data should include the 3D coordinate information of the material pile, as well as possible auxiliary information such as surface texture and color.

[0121] S402: Identifying the loading position of the next layer of materials in the ship's cargo hold according to the three-dimensional point cloud data of the materials already loaded in the ship's cargo hold;

[0122] S403: Calculate the theoretical material volume of the next layer of materials in the ship cargo hold by combining the number of loadable positions with the volume of materials grabbed by the ship loader; determine whether the theoretical material volume of the next layer of materials is greater than the remaining volume of the material pile to be loaded: if so (indicating that the material pile to be loaded can be loaded by loading the next layer under the loading of the ship loader), execute step S404; otherwise (indicating that the material pile to be loaded cannot be loaded by loading the next layer under the loading of the ship loader), execute step S405;

[0123] S404: Calculate the number of times the loader needs to grab the next layer of materials by combining the remaining volume of the material pile to be loaded and the volume of materials grabbed by the loader at a time; select a corresponding number of loadable positions according to the number of times the loader needs to grab the next layer of materials; generate a loading plan for the next layer of materials with the selected loadable positions as the unloading positions of the loader when loading the next layer of materials in the cargo hold of the ship;

[0124] In this embodiment, the number of times required to grab the next layer of material is calculated by dividing the remaining volume of the material pile to be loaded by the volume of the material grabbed by the ship loader in a single time. When selecting the loadable position, the loadable positions are selected in sequence in a manner of spreading from the center position of the ship cargo hold grid to the surrounding areas as the position for each unloading of the ship loader. The purpose of this is to ensure that the material is loaded in the middle position of the ship cargo hold as much as possible, and to avoid the problem of unbalanced and uneven material loading caused by all the materials being loaded on one side of the ship cargo hold.

[0125] S405: Generate a loading planning scheme for the next layer of materials using all available loading positions as the unloading positions of the loading machine when loading the next layer of materials in the ship's cargo hold.

[0126] The present invention uses the volume of materials grabbed by the ship loader at a time and the unloading stacking area as a benchmark to perform quantitative analysis on the entire material loading process, and takes into account the remaining volume of the material pile to be loaded during the planning process, so that the scheduling planning of material loading can be better and more accurately realized, thereby improving the effective utilization rate of the loading space and the loading efficiency.

[0127] In the specific implementation process, in step S402, the low-lying areas of the loaded materials in the ship's cargo hold, as well as the position coordinates and area are identified through the three-dimensional point cloud data of the loaded materials in the ship's cargo hold; the low-lying areas with an area greater than the set area threshold are used as the loading positions for the next layer of materials.

[0128] Specifically, the low-lying areas of materials in the ship's cargo hold are identified through the following steps:

[0129] S4021: Preprocessing the three-dimensional point cloud data of the materials loaded in the ship's cargo hold;

[0130] In this embodiment, preprocessing includes denoising and filtering, data simplification and data registration processing. Denoising and filtering refer to denoising the original point cloud data to remove noise points and outliers to reduce the impact on subsequent grid generation, which can be achieved through statistical filtering, median filtering and other methods. Applying a filtering algorithm to smooth the point cloud data further reduces noise and improves data quality. Data simplification refers to streamlining point cloud data, such as reducing the amount of data through downsampling, improving processing efficiency, and ensuring that the streamlined data still maintains the key features of the material surface. Data registration refers to data registration of point cloud data from multiple perspectives or different time periods, aligning different point cloud data to the same coordinate system to ensure data integrity and consistency.

[0131] S4022: Modeling the preprocessed 3D point cloud data to generate a 3D model of the material surface;

[0132] Generate a 3D model of the material surface using the Delaunay triangulation algorithm. The specific steps are as follows:

[0133] S40221: Select a super triangle containing all point cloud data and add it to the mesh;

[0134] S40222: traverse each data point in the three-dimensional point cloud data and insert it into the current grid in turn;

[0135] S40223: For each newly inserted data point, find the triangle or super triangle where the data point is located, and connect the data point to the three vertices of the triangle to form three new edges;

[0136] S40224: Check whether the new edges meet the Delaunay condition (check whether there are other points in the circumcircle of these edges). If there are edges that do not meet the Delaunay condition, perform edge flipping, that is, replace the current triangle with two adjacent triangles until all edges meet the Delaunay condition (the flipping operation will update adjacent triangles and edges to ensure that the local shape of the mesh is good);

[0137] S40225: Repeat steps S40222 to S40224 until all data points are inserted into the grid and all edges satisfy the Delaunay condition;

[0138] S40226: Remove the initially added super triangle and its associated triangles to generate the final Delaunay triangulated mesh;

[0139] S40227: Perform mesh smoothing and hole filling on the Delaunay triangulated mesh to generate a three-dimensional model of the material surface;

[0140] In this embodiment, mesh smoothing refers to smoothing the generated Delaunay triangulated mesh to reduce the jagged edges caused by discretization and make the mesh surface smoother and more natural, which can be achieved by moving the vertex positions, adjusting the triangle shapes, etc. Hole filling refers to filling the holes in the mesh caused by occlusion or data loss, which can be achieved by interpolation, shape-based repair, etc.

[0141] S4023: Perform morphological analysis on the three-dimensional model of the material surface to identify low-lying areas on the material surface;

[0142] The specific steps for identifying low-lying areas are as follows:

[0143] S40231: Select a projection plane, traverse each vertex in the three-dimensional model of the material surface, calculate its coordinates on the projection plane, and record the height information of each vertex;

[0144] In this embodiment, a horizontal plane (such as an XY plane) is selected as the projection plane, so that the height map obtained can intuitively reflect the undulation of the material surface. For each vertex, its X and Y coordinates are the coordinates on the projection plane, and its Z coordinate is used as the height information.

[0145] S40232: Fill the blank areas between vertices by interpolation algorithms (such as bilinear interpolation, nearest neighbor interpolation, etc.) to generate a height map;

[0146] In this embodiment, the interpolation algorithm can select bilinear interpolation and nearest neighbor interpolation algorithms. The height information obtained by interpolation is stored in a two-dimensional array, each element corresponds to a pixel point on the height map, and its value represents the height of the point. The height map can also be further converted into an image format (such as PNG, JPEG, etc.).

[0147] S40233: Preprocessing and morphological operations are performed on the height map; the morphological operations include corrosion operations, dilation operations, opening operations, and closing operations;

[0148] In this embodiment, the preprocessing of the height map includes filtering, denoising and contrast enhancement, etc., so as to improve the image quality and enhance the accuracy of subsequent processing.

[0149] Among them, the erosion operation refers to the application of the erosion operation to reduce the bright area (i.e., the area with higher height) in the image; the erosion operation is achieved by replacing the local minimum of the image with the structural element, which helps to remove small protrusions and noise. The dilation operation refers to the application of the dilation operation to expand the dark area (i.e., the low-lying area) in the image; the dilation operation is achieved by replacing the local maximum of the image with the structural element, which helps to connect adjacent low-lying areas and fill small holes. The opening operation and the closing operation refer to the fact that on the basis of the erosion operation and the dilation operation, the opening operation (first erosion and then dilation) can be used to remove small protrusions and noise without significantly changing the size of the low-lying area; the closing operation (first dilation and then erosion) helps to fill small holes and cracks in the low-lying area.

[0150] S40234: Apply threshold segmentation technology to divide the height map after preprocessing and morphological operation into low-lying areas and non-low-lying areas (i.e., select a suitable threshold and regard the pixels below the threshold as part of the low-lying area. The selection of the threshold needs to be determined according to the actual application scenario and the characteristics of the height map, and it may be necessary to find the best value through experiments and adjustments);

[0151] S4024: Calculate the location coordinates and area of ​​the low-lying area;

[0152] The specific steps for calculating the location coordinates and area of ​​the low-lying area are as follows:

[0153] S40241: Mark the pixels in the low-lying area (usually by setting a specific pixel value (such as 0 or 255) or marking in a separate mask image); calculate the coordinates of the centroid (or center) of each low-lying area as its position coordinates;

[0154] In this embodiment, the centroid coordinates of the low-lying area can be obtained by weighted averaging the coordinates of all pixels in the area, and the weight can be the brightness value or other relevant attributes of the pixel.

[0155] S40242: Count the number of pixels in the low-lying area, and calculate the area of ​​the low-lying area by combining (multiplying) the actual area represented by each pixel (which depends on the resolution and scale of the height map).

[0156] The present invention uses the three-dimensional point cloud data of the loaded material to construct a three-dimensional model of the material surface, and then identifies the low-lying area and its position coordinates and area based on the model, and finally determines the loading position of the next layer of material. First, the high-precision three-dimensional model of the material surface constructed by the three-dimensional point cloud data can accurately reflect the actual situation of the material surface, including the shape, size and position of the low-lying area, provide a reliable basis for subsequent material loading, and reduce loading errors caused by human misjudgment, thereby improving the accuracy and reliability of subsequent material loading. Secondly, based on the three-dimensional model of the material surface, the low-lying area is identified, which can ensure that the material is more evenly distributed during the loading process, reduce material damage or stability problems caused by excessive or insufficient local pressure, and help to achieve layered loading of materials, and improve the overall stability and safety of loading. Finally, by accurately identifying the low-lying area as the loading position of the material, the invalid space occupation during the material loading process can be reduced, making the overall material loading more compact and uniform, thereby improving the effectiveness of the single loading of the ship loader, and at the same time, it can reduce the loading gap caused by the unreasonable material unloading position, thereby further improving the uniformity of material loading.

[0157] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the technical solution. Those skilled in the art should understand that those modifications or equivalent substitutions of the technical solution of the present invention that do not depart from the purpose and scope of the technical solution should be included in the scope of the claims of the present invention.

Claims

1. A material loading scheduling planning method for a ship loader based on three-dimensional point cloud, characterized in that: include: S1: Obtain the total volume of the material pile to be loaded, as well as the volume of materials grabbed by the ship loader in a single time and the unloading stacking area; S2: Calculate and generate a loading plan for the first layer of materials based on the capacity of the ship's cargo hold, the total volume of the material pile to be loaded, the volume of materials grabbed by the ship loader at a time, and the unloading stacking area; the loading plan for the first layer of materials includes the unloading position of the ship loader each time when loading the first layer of materials in the ship's cargo hold; S3: Scheduling the ship loader to complete the loading of the first layer of materials in the ship's cargo hold through the loading planning scheme of the first layer of materials; S4: Determine the loading position through the three-dimensional point cloud data of the loaded materials in the ship cargo hold, and calculate the loading plan for the next layer of materials in combination with the remaining volume of the material pile to be loaded and the volume of materials grabbed by the ship loader at a time; wherein the loading plan for the next layer of materials includes the unloading position of the ship loader each time when loading the next layer of materials in the ship cargo hold; S5: Scheduling the loader to complete the loading of the next layer of materials in the ship's cargo hold through the loading planning scheme of the next layer of materials; S6: Repeat steps S4 to S5 until the material pile to be loaded is loaded or the ship's cargo hold capacity reaches an upper limit.

2. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 1, characterized in that: In step S1, the total volume of the material pile to be loaded is determined by using the three-dimensional point cloud data; The specific steps are as follows: S101: Acquire three-dimensional point cloud data of a material pile to be loaded at different viewing angles or different positions; S102: Preprocessing the three-dimensional point cloud data; S103: converting the pre-processed three-dimensional point cloud data at different viewing angles or different positions into a unified coordinate system; S104: Using a point cloud stitching algorithm to stitch together the three-dimensional point cloud data at different viewing angles or different positions to generate an overall point cloud model of the material; S105: based on the difference between the material pile to be loaded and the environment, the material pile to be loaded is segmented from the background of the overall point cloud model of the material in combination with a segmentation algorithm to obtain point cloud data of the material pile; S107: reconstructing the segmented point cloud data of the material pile to obtain a three-dimensional model of the material pile; S108: Calculate the total volume of the material pile to be loaded based on the reconstructed three-dimensional model of the material pile and in combination with a volume calculation method.

3. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 1, characterized in that: In step S1, the ship loader is subjected to multiple material grabbing and unloading experiments; the volume of materials grabbed by the ship loader and the material stacking area after unloading in each experiment are measured; and the average value of the multiple measured material volumes and material stacking areas is taken as the single grabbing material volume and unloading stacking area of ​​the ship loader.

4. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 1, characterized in that: In step S2, a loading plan for the first layer of materials is generated through the following steps: S201: dividing the bottom surface of the ship cargo hold into grids according to the unloading and stacking area of ​​the ship loader; wherein the area size of each grid unit in the grid corresponds to the unloading and stacking area of ​​the ship loader at a time; S202: Calculate the theoretical volume of the first layer of materials in the ship cargo hold by combining the number of grid units with the volume of materials grabbed by the ship loader at a time; determine whether the theoretical volume of the first layer of materials is greater than the total volume of the material pile to be loaded: if so, execute step S203; otherwise, execute step S204; S203: Calculate the required grabbing times of the first layer by combining the total volume of the material pile to be loaded with the volume of the material grabbed by the ship loader at a time; select a corresponding number of grid cells from the grid of the ship cargo hold according to the required grabbing times of the ship loader; generate a loading plan for the first layer of materials using all the selected grid cells as the unloading position of the ship loader when loading the first layer of materials in the ship cargo hold; S204: Generate a loading planning scheme for the first layer of materials using all grid cells in the grid as the unloading position of the loading machine when loading the first layer of materials in the ship's cargo hold.

5. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 4, characterized in that: In step S202, the theoretical volume of the first layer of material is calculated by the following formula: V1 = N × v; Where: V m represents the theoretical volume of the first layer of materials; N represents the number of grid units; v represents the volume of materials grabbed by the loader.

6. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 4, characterized in that: In step S203, the required number of grabs for the first layer is calculated using the following formula: Where: C represents the number of grabs required for the first layer; V all It represents the total volume of the material pile to be loaded; v represents the volume of the material grabbed by the loader.

7. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 4, characterized in that: In step S203, if the theoretical volume of the first layer of materials is greater than the capacity of the ship's cargo hold, the maximum number of grabbing times for the first layer is calculated by combining the capacity of the ship's cargo hold with the volume of materials that the loader grabs at a single time; a corresponding number of grid cells are selected from the grid of the ship's cargo hold according to the maximum number of grabbing times for the first layer; and a loading planning scheme for the first layer of materials is generated using all the selected grid cells as the unloading position of the loader when loading the first layer of materials in the ship's cargo hold.

8. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 4, characterized in that: In step S4, the loading plan for the next layer of materials is generated through the following steps: S401: Acquire the three-dimensional point cloud data of the materials loaded in the ship's cargo hold; S402: Identifying the loading position of the next layer of materials in the ship's cargo hold according to the three-dimensional point cloud data of the materials already loaded in the ship's cargo hold; S403: Calculate the theoretical volume of the next layer of materials in the ship cargo hold by combining the number of available loading positions with the volume of materials grabbed by the ship loader; determine whether the theoretical volume of the next layer of materials is greater than the remaining volume of the material pile to be loaded: if so, execute step S404; Otherwise, execute step S405; S404: Calculate the number of times the ship loader needs to grab the next layer of materials by combining the remaining volume of the material pile to be loaded and the volume of materials grabbed by the ship loader at a time; select a corresponding number of loadable positions according to the number of times the next layer of materials needs to be grabbed; generate a loading plan for the next layer of materials with the selected loadable positions as the unloading positions of the ship loader when loading the next layer of materials in the ship's cargo hold; S405: Generate a loading planning scheme for the next layer of materials using all available loading positions as the unloading positions of the loading machine when loading the next layer of materials in the ship's cargo hold.

9. The material loading scheduling planning method for a ship loader based on three-dimensional point cloud according to claim 8, characterized in that: In step S402, the low-lying areas of the loaded materials in the ship's cargo hold, as well as the position coordinates and area, are identified through the three-dimensional point cloud data of the loaded materials in the ship's cargo hold; the low-lying areas with an area greater than a set area threshold are used as the loading positions for the next layer of materials.

10. The method for scheduling and planning material loading for a ship loader based on three-dimensional point cloud according to claim 9, characterized in that: In step S402, the low-lying area of ​​the material in the ship's cargo hold is identified by the following steps: S4021: Preprocessing the three-dimensional point cloud data of the materials loaded in the ship's cargo hold; S4022: Modeling the preprocessed 3D point cloud data to generate a 3D model of the material surface; Generate a 3D model of the material surface using the Delaunay triangulation algorithm. The specific steps are as follows: S40221: Select a super triangle containing all point cloud data and add it to the mesh; S40222: traverse each data point in the three-dimensional point cloud data and insert it into the current grid in turn; S40223: For each newly inserted data point, find the triangle or super triangle where the data point is located, and connect the data point to the three vertices of the triangle to form three new edges; S40224: Check whether the new edge meets the Delaunay condition. If there is an edge that does not meet the Delaunay condition, perform an edge flip operation, that is, replace the current triangle with two adjacent triangles until all edges meet the Delaunay condition. S40225: Repeat steps S40222 to S40224 until all data points are inserted into the grid and all edges satisfy the Delaunay condition; S40226: Remove the initially added super triangle and its associated triangles to generate the final Delaunay triangulated mesh; S40227: Perform mesh smoothing and hole filling on the Delaunay triangulated mesh to generate a three-dimensional model of the material surface; S4023: Perform morphological analysis on the three-dimensional model of the material surface to identify low-lying areas on the material surface; The specific steps for identifying low-lying areas are as follows: S40231: Select a projection plane, traverse each vertex in the three-dimensional model of the material surface, calculate its coordinates on the projection plane, and record the height information of each vertex; S40232: Fill the blank areas between vertices through interpolation algorithm to generate height map; S40233: Preprocessing and morphological operations are performed on the height map; the morphological operations include corrosion operations, dilation operations, opening operations, and closing operations; S40234: Apply threshold segmentation technique to divide the height map after preprocessing and morphological operation into low-lying areas and non-low-lying areas; S4024: Calculate the location coordinates and area of ​​the low-lying area; The specific steps for calculating the location coordinates and area of ​​the low-lying area are as follows: S40241: Mark the pixel points in the low-lying area; calculate the coordinates of the centroid of each low-lying area as its position coordinates; S40242: Count the number of pixels in the low-lying area, and calculate the area of ​​the low-lying area based on the actual area represented by each pixel.

Images