Volume calculation method, volume calculation system, and volume calculation program

Abstract

Even when an object other than the object is present on the surface above the object contained within the target area, the volume of the object can be calculated with greater accuracy. [Solution] The volume calculation method (S1) includes a point cloud data acquisition step (S11) which acquires point cloud data from a target area containing an object using a three-dimensional sensor; a grid height calculation step (S12) which calculates the grid height for each of a plurality of grid regions obtained by dividing the target area into a grid pattern when viewed from above; a calculation exclusion identification step (S13) which identifies grid regions that should be excluded from calculation; a column height calculation step (S14) which calculates the column height for each column arranged in the width direction in the plurality of grid regions based on the grid height of each grid region that is not excluded from calculation; and a volume calculation step (S15) which calculates the volume of the object by referring to the column height of each column and the width direction length of each column.

Description

Technical Field

[0001] The present invention relates to a technique for calculating the volume of an object accommodated in a target area.

Background Art

[0002] Patent Document 1 discloses a technique for calculating the volume of earth and sand loaded in a ship's hold. This technique determines a plurality of cross-sections perpendicular to the central axis of the ship's hold, obtains a spline function that smoothly connects the measurement points on the surface of the loaded earth and sand measured by a laser measuring instrument for each cross-section, and determines the deposition of the loaded earth and sand by integrating the spline function.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Here, there may be an object different from the object on the upper surface of the object (for example, earth and sand, stone, etc.) accommodated in the target area (for example, a ship's hold, a construction waste storage place, etc.). For example, on top of the stone loaded in the ship's hold, there may be a bucket for unloading the stone temporarily placed when the unloading work is not being carried out. Also, for example, on top of the earth and sand dumped at the construction waste storage place, there may be a bucket of the backhoe that dumped the earth and sand temporarily placed when the dumping is not being carried out. However, in the technique described in Patent Document 1, when there is an object different from the object on the upper surface of the object, there is a problem that the volume including the different object is likely to be calculated.

[0005] One aspect of the present invention aims to realize a technique for accurately calculating the volume of the object even when there is an object different from the object on the upper surface of the object accommodated in the target area. [Means for solving the problem]

[0006] To solve the above problems, a volume calculation method according to one aspect of the present invention includes: a point cloud data acquisition step of acquiring point cloud data measured using a three-dimensional sensor from a target area containing an object; a grid height calculation step of calculating a grid height indicating the height from a reference plane based on the point cloud data for each of a plurality of grid regions obtained by dividing the target area into a grid pattern in a top view; a calculation exclusion identification step of a grid region to be excluded from calculation among the plurality of grid regions; a column height calculation step of calculating a column height indicating a representative value of the grid height in each column based on the grid height of each grid region that is not excluded from calculation for each column arranged in the width direction in the plurality of grid regions; and a volume calculation step of calculating the volume of the object by referring to the column height of each column and the width direction length of each column.

[0007] To solve the above problems, a volume calculation system according to one aspect of the present invention includes: a point cloud data acquisition unit that acquires point cloud data measured using a three-dimensional sensor from a target area containing an object; a grid height calculation unit that calculates a grid height indicating the height from a reference plane based on the point cloud data for each of a plurality of grid regions obtained by dividing the target area into a grid shape when viewed from above; a calculation exclusion identification unit that identifies grid regions that should be excluded from calculation among the plurality of grid regions; a column height calculation unit that calculates a column height indicating a representative value of the grid height in each column based on the grid height of each grid region that is not excluded from calculation for each column arranged in the width direction in the plurality of grid regions; and a volume calculation unit that calculates the volume of the object by referring to the column height of each column and the width direction length of each column.

[0008] To solve the above problems, a volume calculation program according to one aspect of the present invention is a volume calculation program for causing a computer to function as the above-described volume calculation system, wherein the computer functions as the point cloud data acquisition unit, the grid height calculation unit, the unit for identifying items not to be calculated, the column height calculation unit, and the volume calculation unit. [Effects of the Invention]

[0009] According to one aspect of the present invention, even when an object different from the object is present on the upper surface of the object contained within the target area, the volume of the object can be calculated with greater accuracy. [Brief explanation of the drawing]

[0010] [Figure 1] This figure schematically illustrates the configuration of a volume calculation system according to Embodiment 1 of the present invention. [Figure 2] This is a block diagram showing the functional configuration of a volume calculation system according to Embodiment 1 of the present invention. [Figure 3] This is a flowchart showing the flow of the volume calculation method according to Embodiment 1 of the present invention. [Figure 4] This flowchart shows a detailed flow of the specific steps excluded from calculation according to Embodiment 1 of the present invention. [Figure 5] This is a top view of a hopper boat according to Embodiment 1 of the present invention. [Figure 6] This figure shows an example of point cloud data according to Embodiment 1 of the present invention. [Figure 7] This is a schematic diagram illustrating an example of a grid region and grid height according to Embodiment 1 of the present invention. [Figure 8] This is a schematic diagram illustrating an example of a representative cross-section according to Embodiment 1 of the present invention. [Figure 9] This is a three-view drawing showing an example of a target region in a modified example of Embodiment 1 of the present invention. [Figure 10] This figure shows another example of the target area and soil in a modified example of Embodiment 1 of the present invention. [Figure 11] This is a block diagram showing the functional configuration of a point cloud data processing device according to Embodiment 2 of the present invention. [Figure 12] This is a flowchart illustrating the flow of the point cloud data processing method according to Embodiment 2 of the present invention. [Modes for carrying out the invention]

[0011] 〔Embodiment 1〕 Hereinafter, the volume calculation system 1 according to an embodiment of the present invention will be described in detail with reference to the drawings.

[0012] <Problems of Conventional Inspection Work> When constructing a breakwater, the stones for forming the foundation mound that serves as the foundation of the breakwater are stored in the hold of a gut boat and transported to the installation location of the breakwater. The stones are also called waste stones, but hereinafter, the term "stones" will be used. Also, the fact that the stones are "stored" in the hold is hereinafter also referred to as "loaded". For example, before the stones are put into the installation location, an inspection work of the stones is carried out. The inspection work of the stones is an operation of measuring the volume of the stones loaded on the gut boat. Conventional inspection work has the following problems.

[0013] Conventionally, the inspection work of stones is carried out by, for example, workers. In this case, since the worker measures the height of the stones and calculates the volume based on the measurement result, there is a problem that it takes a lot of manpower and time. Also, when there are objects (buckets, wires, etc.) different from the stones on the stones loaded in the hold, the work of removing the objects different from the stones is complicated. For this reason, a technology that can accurately perform the inspection work of stones without taking a lot of manpower and time without removing the objects existing on the upper part of the stones is desired.

[0014] Also, conventionally, as the inspection work of stones, acquiring point cloud data and calculating the volume has been carried out. Also, in this case, mainly the mesh earthwork method is used. However, when there is an object on the stones, the point cloud data includes the point cloud indicating the object. Also, if the point cloud indicating the object is excluded from the calculation target, the stones under the object are not considered, and there is a problem that a missing part occurs.

[0015] In addition, in order to perform inspection work without manual labor and time consumption, for example, it is also conceivable to use the technology described in Patent Document 1 mentioned above. However, as described above, this technology cannot handle the case where an object exists on the stone material. Further, since this technology performs measurement and processing for a plurality of cross-sections, there is also a problem that it requires a high computational cost. Therefore, a technology that can accurately perform the inspection work of stone materials while reducing the computational cost without removing the object existing on the upper part of the stone material is desired.

[0016] <Configuration of Volume Calculation System 1> The volume calculation system 1 can be used to solve the problems of conventional inspection work. FIG. 1 is a diagram schematically explaining the configuration of the volume calculation system 1. As shown in FIG. 1, the volume calculation system 1 is a system that calculates the volume of the stone material 90 loaded in the hold 81 of the gut boat 80, and includes a server 10, a terminal 20, and a LiDAR 30. The orthogonal coordinates shown in FIG. 1 define the direction from the stern to the bow of the gut boat 80 as the positive x-axis direction, the zenith direction as the positive z-axis direction, and define the positive y-axis direction so as to form a left-handed orthogonal coordinate system together with the positive x-axis direction and the positive z-axis direction. Note that the orthogonal coordinate system shown in each drawing described later is the same as the orthogonal coordinate system shown in FIG. 1.

[0017] Note that some or all of the functional blocks described later included in the server 10 may be provided in the terminal 20, or some or all of the functional blocks described later included in the terminal 20 may be provided in the server 10. For example, an aspect in which all the functional blocks included in the server 10 are included in the terminal 20 (in other words, an aspect in which the server 10 is not required) may be possible.

[0018] Furthermore, the following description will primarily focus on an example where measurements are taken by a worker carrying and moving the terminal 20 and LiDAR 30. However, one or both of the terminal 20 and LiDAR 30 do not necessarily have to be carried by the moving worker. For example, the LiDAR 30 may be installed in the cargo hold 81 so that measurements can be taken, and the terminal 20 may be operated by a worker on the bridge 83. In this case, the measurement may begin when the worker on the bridge 83 operates the terminal 20 to control the LiDAR 30. Also, the terminal 20 and LiDAR 30 may be connected by wire or wireless connection.

[0019] (Gatt ship 80) The hoisting vessel 80 is an example of a work vessel. The hoisting vessel 80 is a transport vessel capable of loading and unloading materials using its own equipment, and is equipped with a cargo hold 81, a crane 82, and a bridge 83. For example, the hoisting vessel 80 is used to transport stone materials 90, which will be used as materials for a foundation mound, to the site where the foundation mound will be formed.

[0020] (Ship hold 81) A cargo hold 81 is provided in the central part of the hob carrier 80. The space within the cargo hold 81 is an example of a target area for accommodating objects, and is an example of a region within the loadable space of a workboat. In the following, "the space within the cargo hold 81" will also be simply referred to as "cargo hold 81". The cargo hold 81 has a rectangular or rectangular shape when viewed from above. It is also a rectangular prism or a shape that can be approximated as a rectangular prism. The top surface of the cargo hold 81 is open. The bottom surface 811 of the cargo hold 81 is an example of a reference surface used when calculating the volume of the stone material 90. The capacity of the cargo hold 81 varies depending on the size of the hob carrier 80, but one example is 1000 cubic meters.

[0021] (Crane 82) A crane 82 is provided near the bow of the hoisting vessel 80. The crane 82 comprises a control room 821, a boom 822, a lifting wire 823, and a bucket 824. The boom 822 is configured to rotate freely around a predetermined axis of rotation and to be able to control its posture. The lifting wire 823 suspends the bucket 824 from the tip of the boom 822. The bucket 824 has openable and closable claws for gripping the stone 90. The volume of the bucket 824 is not limited, but examples include 10 cubic meters and 30 cubic meters.

[0022] The crane 82 is controlled by the operator in the cab 821. The crane 82 grasps the stone materials 90 loaded in the cargo hold 81 using the bucket 824 and then moves the bucket 824 to the loading area (for example, the location where the foundation mound is formed). The crane 82 also loads the stone materials 90 into the loading area by opening the bucket 824 that is gripping the stone materials 90. When such loading operations are not performed (for example, when inspection work is being performed), the bucket 824 may be temporarily placed on top of the stone materials 90. The location and orientation of the temporarily placed bucket 824 are not limited to the example shown in Figure 1.

[0023] (Funabashi 83) The bridge 83 is located in the stern area of ​​the hopper 80, oriented in the left-right direction (y-axis direction as shown in Figure 1). The indoor portion of the bridge 83 functions as the control room of the hopper 80. The rooftop portion of the bridge 83 is positioned higher than the operator's cab 821 of the crane 82, allowing for a panoramic view of the hopper 80 in all directions.

[0024] (Stone 90) The stone material 90 is a rock that will be used as the material for the foundation mound. The stone material 90 is an example of an object to be contained in the target area (for example, the ship's hold 81). The weight of each stone used as stone material 90 is typically between 10 kg and 100 kg, with an average of about 50 kg. However, it is not limited to this typical example, and for example, larger stones weighing between 100 kg and 500 kg may be used.

[0025] (LiDAR30) LiDAR30 is a device that detects the shape of an object in three-dimensional space by measuring the distance to the object using reflected laser light. LiDAR30 is an example of a three-dimensional sensor. In this embodiment, an example using LiDAR30 as an example of a three-dimensional sensor is described, but the three-dimensional sensor is not limited to this, and may be, for example, a stereo camera.

[0026] For example, the LiDAR 30 may be in a form that can be carried by the worker U (for example, a form referred to as a handheld scanner), as shown in Figure 1. The LiDAR 30 is connected to the terminal 20 in a communicative manner and transmits the shape of the detected object to the terminal 20 as point cloud data. Note that the LiDAR 30 is not limited to being connected to the terminal 20, but may also be built into the terminal 20. Note that the LiDAR 30 is not limited to being in a portable form, but may also be installed in a predetermined location. Furthermore, if installed in a predetermined location, the LiDAR 30 may be permanently installed or temporarily installed. The predetermined location is preferably a place where the entire upper surface of the cargo hold 81 can be included in the field of view, for example, the upper part of the bridge 83. Alternatively, instead of installing one LiDAR 30, multiple LiDAR 30s may be installed so that each field of view includes a portion of the upper surface of the cargo hold 81 divided into sections.

[0027] For example, LiDAR30 is equipped with an attitude detection sensor that generates attitude information representing the tilt in the pitching, yawing, and rolling directions. LiDAR30 changes its field of view in response to changes in attitude and detects the shapes of surrounding objects using a three-dimensional local coordinate system shared across each field of view. The detected object shapes are represented as point cloud data. Each point that makes up the point cloud data is associated with coordinates in the three-dimensional local coordinate system.

[0028] (Terminal 20) Terminal 20 is a computer used by worker U, and is, for example, a portable terminal (e.g., a smartphone, tablet, wearable device, notebook computer, etc.). However, terminal 20 is not limited to a portable terminal; it may also be a stationary terminal. The computer comprising terminal 20 includes a processor, memory, communication interface, input / output interface, and peripheral device connection interface. Details of the functional configuration of terminal 20 will be described later.

[0029] (Server 10) Server 10 is a computer that calculates the volume of an object contained in a target area in response to a request from terminal 20, and is an example of a device that constitutes a volume calculation system. Server 10 is also a computer that processes point cloud data in response to a request from terminal 20, and is an example of a device that constitutes a point cloud data processing system. Server 10 calculates the volume of the object in response to a request from terminal 20 and presents the calculated volume to terminal 20. The computer comprising server 10 includes a processor, memory, and a communication interface. Details of the functional configuration of server 10 will be described later.

[0030] Server 10 is connected to terminal 20 via a network NW so that it can communicate with it. For example, server 10 may be located in the cloud or on a galley ship 80. The network NW may include, but is not limited to, a wireless LAN (Local Area Network), a wired LAN, a WAN (Wide Area Network), or part or all of a mobile data communication network.

[0031] <Functional configuration of volume calculation system 1> The functional configuration of the volume calculation system 1 will be explained with reference to Figure 2. Figure 2 is a block diagram showing the functional configuration of the volume calculation system 1.

[0032] (Functional configuration of Server 10) As shown in Figure 2, the server 10 includes a control unit 110, a storage unit 120, and a communication unit 130. The control unit 110 is implemented by a processor executing a program stored in memory and comprehensively controls each part of the server 10. The storage unit 120 is composed of memory and stores various data referenced or generated by the control unit 110. The communication unit 130 is composed of a communication interface and communicates with external devices (e.g., terminal 20) via a network NW. The control unit 110 includes a point cloud data acquisition unit 111, a grid height calculation unit 112, a calculation exclusion identification unit 113, a column height calculation unit 114, a volume calculation unit 115, and a display control unit 116.

[0033] The point cloud data acquisition unit 111 acquires point cloud data measured using a three-dimensional sensor (e.g., LiDAR 30) from the target area (e.g., ship's hold 81) in which the object (e.g., stone material 90) is contained. Details and specific examples of the point cloud data will be described later.

[0034] The grid height calculation unit 112 calculates the grid height, which indicates the height from the reference plane (e.g., the bottom surface 811), for each of the multiple grid regions obtained by dividing the target area (e.g., the ship's hold 81) into a grid pattern when viewed from above, based on point cloud data. Details and specific examples of grid regions and grid heights will be described later.

[0035] The calculation exclusion unit 113 identifies the grid regions that should be excluded from the calculation among multiple grid regions. Details and specific examples of grid regions to be excluded from the calculation will be described later.

[0036] The column height calculation unit 114 calculates a representative value of the grid height for each column arranged in the width direction across multiple grid regions, based on the grid heights of each grid region that is not excluded from the calculation. Details and specific examples of column height will be described later.

[0037] The volume calculation unit 115 calculates the volume of the object by referring to the column height and the width of each column. For example, if the top view shape of the object area is rectangular, as in the ship's hold 81 described above, the width of the rectangle is used as the width of each column.

[0038] The display control unit 116 displays an image on a display device (for example, the display device of terminal 20) in which display elements indicating the grid height of each grid region are added to the image showing the point cloud data in a manner that allows identification of whether or not they are excluded from the calculation. The display control unit 116 also displays an image on a display device (for example, the display device of terminal 20) in which display elements indicating the column height of each column are added to the image showing the point cloud data.

[0039] (Functional configuration of terminal 20) As shown in Figure 2, the terminal 20 includes a control unit 210, a storage unit 220, a communication unit 230, an input unit 240, a display unit 250, and a peripheral device connection unit 260. The control unit 210 is implemented by a processor executing a program stored in memory and comprehensively controls each part of the terminal 20. The storage unit 220 is composed of memory and stores various data referenced or generated by the control unit 210. The communication unit 130 is composed of a communication interface and communicates with an external device (e.g., server 10) via a network NW.

[0040] The input unit 240 is configured to include, for example, an input device. Examples of input devices include, but are not limited to, a mouse, keyboard, touchpad, microphone, etc. Furthermore, the input unit 240 is not limited to being built into the terminal 20, but may also be connected to the outside via the peripheral device connection unit 260. The display unit 250 is configured to include, for example, a display device. Examples of display devices include, but are not limited to, a liquid crystal display, an organic EL (electroluminescence), etc. Furthermore, the display unit 250 is not limited to being built into the terminal 20, but may also be connected to the outside via the peripheral device connection unit 260. Note that the input unit 240 and the display unit 250 may include an input / output device integrally formed as a touch panel, etc.

[0041] The peripheral device connection unit 260 includes a peripheral device connection interface for connecting peripheral devices. Examples of peripheral device connection interfaces include, but are not limited to, USB (Universal Serial Bus) and Bluetooth® short-range wireless communication modules. The peripheral device connection unit 260 connects to, for example, the LiDAR 30.

[0042] The control unit 210 includes a volume calculation user interface unit 211 (hereinafter referred to as the volume calculation UI unit 211). The volume calculation UI unit 211 provides a user interface for using the function provided by the server 10 to calculate the volume of an object contained in a target area. For example, the volume calculation UI unit 211 controls the LiDAR 30 to acquire point cloud data from the target area based on operations from the input unit 240. The volume calculation UI unit 211 also uploads the acquired point cloud data to the server 10 based on operations from the input unit 240. The volume calculation UI unit 211 also displays information received from the server 10 (various images, images including the calculated volume, etc.) on the display unit 250.

[0043] <Flow of volume calculation method S1> The flow of the volume calculation method S1 executed by the volume calculation system 1 configured as described above will be explained with reference to Figures 3 and 4. Figure 3 is a flowchart showing the flow of the volume calculation method S1. Figure 4 is a flowchart showing the detailed flow of the process of identifying steps not included in the calculation (step S13) included in the volume calculation method S1. As shown in Figure 3, the volume calculation method S1 includes steps S11 to S16. For example, the volume calculation method S1 is started when worker U operates the volume calculation UI unit 211 of terminal 20.

[0044] (Step S11) Step S11 is an example of a point cloud data acquisition process. In step S11, the point cloud data acquisition unit 111 acquires point cloud data measured using LiDAR 30 from the ship's hold 81 containing the stone materials 90 by receiving it from the terminal 20. Each point constituting the acquired point cloud data is associated with coordinate values ​​indicating its position in three-dimensional space.

[0045] An example of the process for acquiring point cloud data in step S11 will be explained with reference to the example in Figure 5. Figure 5 is a top view of the cargo ship 80 shown in Figure 1. A top view means viewing in the negative z-axis direction. As shown in Figure 5, the cargo ship 80 has a passable area including a route R around the opening of the cargo hold 81. Worker U is carrying a terminal 20 and a LiDAR 30. The volume calculation UI unit 211 controls the LiDAR 30 to start acquiring point cloud data based on the operation of worker U. Worker U walks along route R with the LiDAR 30 pointed towards the cargo hold 81. As a result, the LiDAR 30 acquires point cloud data from the cargo hold 81 where the stone materials 90 are loaded. The volume calculation UI unit 211 receives the point cloud data acquired by the LiDAR 30 and transmits the received point cloud data to the server 10. If the bucket 824 is temporarily placed on the stone 90, the acquired point cloud data will show a shape that includes both the stone 90 and the bucket 824.

[0046] A specific example of acquired point cloud data will be explained with reference to Figure 6. Figure 6 is a diagram showing an example of acquired point cloud data. In Figure 6, image G1 shows a top view of the acquired point cloud data. In image G1, rectangle G11 indicates the outer perimeter of the opening of the cargo hold 81. Furthermore, the area within rectangle G11 may be assigned pixel values ​​according to the size of the z coordinate of each point constituting the point cloud data. In addition, if a reflection intensity is associated with each point constituting the point cloud data, pixel values ​​may be assigned according to that reflection intensity. For example, the reflection intensity of the stone material 90 and the bucket 824 may differ. In this case, as will be described later, in the embodiment in which image G1 is displayed on the display unit 250, it is possible to assist the user in identifying the points that represent the stone material 90 and the bucket 824, respectively.

[0047] (Step S12) Step S12 is an example of a grid height calculation process. In step S12, the grid height calculation unit 112 calculates the grid height, which indicates the height from the bottom surface 811, for each of the multiple grid regions obtained by dividing the cargo hold 81 into a grid pattern when viewed from above, based on point cloud data. The division into multiple grid regions is performed along the z-axis direction. Therefore, if the cargo hold 81 is roughly shaped like a rectangular parallelepiped, each divided grid region is also roughly shaped like a rectangular parallelepiped. For example, the grid height may be a statistical value of the height of the point cloud included in the grid region (e.g., the highest value, the average value, etc.). The statistical value adopted as the grid height is not limited to the example described above. For example, when using this system as an alternative to the conventional manual inspection process where the highest part was measured, the highest value is applied as the grid height.

[0048] Specific examples of grid regions and grid heights will be explained with reference to Figure 7. Figure 7 is a schematic diagram illustrating an example of a grid region and grid height. Image G2 shown in Figure 7 is a top-down view of point cloud data, with 220 rectangular display elements (22 in the x-axis direction × 10 in the y-axis direction) superimposed (for example, G22a, G22b). In Figure 7, each display element that has the same appearance as display element G22a (a striped rectangle) but is not labeled will also be referred to as display element G22a. Display element G22a corresponds to the grid region being calculated. Similarly, each display element that has the same appearance as display element G22b (a white rectangle) but is not labeled will also be referred to as display element G22b. Display element G22b corresponds to the grid region not being calculated. Furthermore, when there is no need to distinguish between display elements G22a and G22b, they will simply be referred to as display element G22. Furthermore, the star-shaped display element G24 has a column height associated with it. Note that each star-shaped display element in Figure 7 that is not labeled is also referred to as display element G24.

[0049] Grid G21 indicates the grid area corresponding to display element G22a. Grid G21 is one of 220 grids obtained by dividing the rectangle G11, which represents the cargo hold 81 viewed from above, into 22 equal parts in the x-axis direction and 10 equal parts in the y-axis direction. In other words, grid G21 represents one grid area viewed from above. Grid G21 corresponds, for example, to a 1-meter square in the real world. That is, in this example, the length of the cargo hold 81 in the longitudinal direction (x-axis direction) is 22 meters, and the length in the width direction (y-axis direction) is 10 meters.

[0050] Furthermore, the display element G22 is associated with a grid height. The grid height associated with display element G22 is the highest z-coordinate among the point cloud in the grid region indicated by grid G21. In this example, the origin in the z-axis direction is assumed to be the z-coordinate of the reference plane 811.

[0051] (Step S13) Step S13 is an example of a process for identifying areas to be excluded from calculation. In step S13, the area to be excluded from calculation unit 113 identifies a grid region from among a plurality of grid regions that should be excluded from calculation. For example, the area to be excluded from calculation unit 113 may identify a grid region to be excluded from calculation based on an operation by a user (e.g., worker U). For example, the above-described image G2 may be displayed on the display unit 250 of the terminal 20, and the system may accept user operations on the display elements (e.g., tap operations, click operations, etc. on the display elements). In this case, the grid region corresponding to the display element that received the operation may be identified as an area to be excluded from calculation, or the system may switch between being included in the calculation and being excluded from calculation each time an operation is received.

[0052] Furthermore, the calculation exclusion identification unit 113 may identify grid regions that should be excluded from calculation without user intervention (in other words, automatically). As a concrete example of automatically identifying regions to be excluded from calculation, for example, the calculation exclusion identification unit 113 may use a machine learning model to identify grid regions that should be excluded from calculation. The machine learning model may be a model that has been trained to take multiple grid regions, each with associated grid heights, as input and output grid regions that should be excluded from calculation. The machine learning model may be an AI (Artificial Intelligence) model or a model based on other machine learning algorithms.

[0053] Furthermore, as another specific example of automatically identifying areas to be excluded from calculation, the calculation exclusion identification unit 113 may identify grid regions where the grid height is an outlier in each column arranged in the width direction in multiple grid regions as areas to be excluded from calculation. A specific example of the calculation exclusion identification process in this case will be explained with reference to Figure 4. As shown in Figure 4, the calculation exclusion identification process S13 includes steps S21 to S22.

[0054] (Step S21) Step S21 is an example of a threshold calculation process. In step S21, the exclusion-from-calculation-target identification unit 113 calculates a threshold for the grid height of the grid region included in the column. The median may be used as the threshold, but is not limited to this.

[0055] Step S22 is an example of an outlier identification step. In step S22, the calculation exclusion unit 113 identifies lattice heights in the lattice regions included in the column whose difference from the threshold exceeds the upper limit as outliers. As a result, lattice regions whose lattice heights have been identified as outliers are identified as being excluded from calculation. For example, when the threshold is z1 and the upper limit is α, lattice regions in which the lattice height z does not satisfy the following equation (1) are identified as being excluded from calculation. In other words, lattice regions in which the lattice height z satisfies the following equation (1) are included in the calculation. |z-z1| ≤ α …(1) Note that the left-hand side of equation (1) represents the absolute value of "z-z1".

[0056] For example, the upper limit α may be determined based on the specifications of the stone material 90. A specific example of a method for determining the upper limit α based on the specifications of the stone material 90 will be described. For example, the non-calculation-target identification unit 113 calculates the volume of one stone material 90 based on the weight of one stone material 90 based on the specifications of the stone material 90 and the specific gravity measured during the inspection work. Next, the non-calculation-target identification unit 113 calculates the size (e.g., the length of one side) of a virtual stone material having the shape corresponding to the volume of one stone material 90 by assuming the shape (e.g., a cube). As a result, the non-calculation-target identification unit 113 may determine the size of the virtual stone material as the upper limit α.

[0057] For example, if the weight range for one piece of stone material 90 is defined as a standard (e.g., 10 kg to 100 kg), the maximum value (e.g., 100 kg) or the average value (e.g., 55 kg) may be applied as the weight used to determine the upper limit α, but is not limited to these. Furthermore, the shape assumed as a virtual stone material is not limited to a cube, but may also be a sphere, a rectangular prism with defined side size ratios, an ellipsoid with defined major and minor axis ratios, etc. Also, the size of the virtual stone material to be calculated as the upper limit α is not limited to the length of one side of a cube, but may also be the length of one side, the length of the diagonal, the diameter, the radius, the major axis, the minor axis, or the length obtained by multiplying these values ​​by a predetermined ratio, etc.

[0058] Here, grid regions where the grid height is higher than the upper limit α relative to the threshold z1 are likely to be part of an area where an object larger than one stone 90 (e.g., a bucket 824) is temporarily placed on top of the stacked stone 90. Also, grid regions where the grid height is lower than the upper limit α relative to the threshold z1 are likely to be part of an area where a small depression has occurred. By excluding such grid regions from the calculation, it becomes possible to calculate the volume of the stone 90 without having to remove objects other than the stone 90 (such as bucket 824) that are present on top of the stone 90.

[0059] Referring to Figure 7, the grid regions included in the calculation and those not included in the calculation will be explained. In Figure 7, as mentioned above, display element G22a is the grid region included in the calculation, and display element G22b is the grid region not included in the calculation. The region G23 corresponding to the display element not included in the calculation corresponds to the region G23 where the bucket 824 is placed on the stone material 90.

[0060] (Step S14) Step S14 is an example of a column height calculation process. In step S14, the column height calculation unit 114 calculates a representative value of the grid height in each column, which is arranged in the width direction in a plurality of grid regions, based on the grid height of each grid region to be calculated. The representative value may be, for example, an average value, but is not limited to this.

[0061] Refer to Figure 7 to explain the column height. In Figure 7, among the 22 columns in which grid regions are arranged in the width direction (y-axis direction), we will explain column G25, which is an example of a column that includes grid regions not included in the calculation, and column G26, which is an example of a column that does not include grid regions not included in the calculation.

[0062] Column G25 contains display elements G22-1 to G22-10. Of these display elements, display elements G22-1 to G22-3 and G22-9 to G22-10 correspond to the grid region included in the calculation, while display elements G22-4 to G22-8 correspond to the grid region not included in the calculation. The star-shaped display element G24-1 indicates the display element associated with the column height of column G25. Note that display element G24-1 can be placed anywhere in column G25, but in this example, it is placed near the center in the y-axis direction, in a position that does not overlap with other display elements G22. The column height of column G25 is the average value of the grid heights associated with the display elements G22-1 to G22-3 and G22-9 to G22-10, respectively. Thus, the column height of column G25 is calculated excluding the display elements G22-4 to G22-8 that are not included in the calculation.

[0063] Column G26 contains display elements G22-11 to G22-20. All of these display elements are included in the calculation. The star-shaped display element G24-2 indicates the display element associated with the column height of column G26. The position of display element G24-2 is explained in the same way as display element G24-1. The column height of column G26 is the average value of the grid heights associated with the calculation-included display elements G22-11 to G22-20 in column G26. Thus, since column G26 does not include grid areas that are not included in the calculation, the column height of column G26 is calculated from all the display elements in column G26.

[0064] In Figure 7, each column without a corresponding label will be explained in the same way as column G25 or column G26.

[0065] Furthermore, the column heights of each column calculated in this manner constitute a representative cross-section of the stone material 90. An example of a representative cross-section will be explained with reference to Figure 8. Figure 8 is a schematic diagram illustrating an example of a representative cross-section. In Figure 8, the same elements as in Figure 7 are given the same reference numerals. As shown in Figure 8, image G3 shows a side view of the point cloud data and display elements G22 and G24 shown in image G2. The polyline G31 in image G3 corresponds to the rectangle G11 in images G1 and G2, and shows the bottom and side views of the cargo hold 81.

[0066] In image G3, each display element G22 is positioned at a height corresponding to the grid height associated with that display element G22 in the z-axis direction. In other words, each display element G22 indicates the grid height. Each display element G24 is positioned at a height corresponding to the column height associated with that display element G24 in the z-axis direction. In other words, each display element G24 indicates the column height. Here, the region G32 enclosed by the approximation curve and polyline G31 connecting multiple display elements G24 is called the representative cross section. The representative cross section can be said to represent the cross section in the longitudinal direction (x-axis direction) of the stacked stone material 90. In image G3, it can be seen that the z-axis position of display element G24a in column G25 is based on the display elements G22-1 to G22-3 and G22-9 to G22-10 that are included in the calculation, and not on the display elements G22-4 to G22-8 that are not included in the calculation. Furthermore, it can be seen that the z-axis position of display element G24b in column G26 is based on the display elements G22-11 to G22-20 that are being calculated.

[0067] (Step S15) Step S15 is an example of a volume calculation process. In step S15, the volume calculation unit 115 calculates the volume of the stone material 90 by referring to the column height and the width of each column. Here, if the top view shape of the cargo hold 81 is rectangular (for example, rectangle G11 in Figure 7), the length in the y-axis direction of rectangle G11 is commonly used as the width direction of each column. For example, in the example in Figure 8, the volume may be calculated by multiplying the area of ​​the region G32 obtained by integrating the approximation curve connecting multiple display elements G24 by the length in the y-axis direction of rectangle G11.

[0068] (Step S16) Step S16 is an example of a display control process. In step S16, the display control unit 116 transmits the calculated volume to the terminal 20, causing it to be displayed on the display unit 250 of the terminal 20. This allows the user (worker U) to know the volume displayed on the display unit 250 of the terminal 20.

[0069] The display control unit 116 may also display an image showing the acquired point cloud data (for example, image G1) on the display unit 250. Alternatively, the display control unit 116 may display an image on the display unit 250 of the terminal 20 in which display elements indicating the grid height of each grid region are superimposed on the image showing the point cloud data in a manner that allows identification of whether or not they are excluded from calculation (for example, images G2 and G3 described above). Alternatively, the display control unit 116 may also display an image on the display unit 250 of the terminal 20 in which display elements indicating the column height of each column are superimposed on the image showing the point cloud data (for example, images G2 and G3 described above). Furthermore, the timing of displaying images G1, G2 and G3 on the display unit 250 is not limited to step S16. For example, the display control unit 116 may display image G1 in step S11, and then display image G2 by sequentially superimposing the generated display elements on image G1 in steps S12, S13, and S14. Similarly, the display control unit 116 may display a side view image of the point cloud data in step S11, and then sequentially superimpose the display elements generated in steps S12, S13, and S14 onto the image to display image G3.

[0070] (Effects of this embodiment) The volume calculation method S1 and volume calculation system 1 according to this embodiment can perform inspection work on the stone materials 90 without removing the bucket 824, even when the bucket 824 is temporarily placed on top of the stone materials 90 loaded in the cargo hold 81 of the cargo ship 80.

[0071] [Variation 1] In the embodiments described above, an example was given in which the target area was a ship's hold 81 with a flat bottom surface 811. The volume calculation system 1 according to this modified example can calculate the volume of an object contained in the target area even when the bottom surface of the target area is not flat.

[0072] Figure 9 is a three-view drawing showing an example of the target area in this modified example. As shown in Figure 9, the cargo hold 81A, which is an example of the target area, has a bottom surface 811A-1 to 811A-5, side surfaces 811A-6 to 811A-9, and an opening surface 811-10. The bottom surface 811A-1 and the opening surface 811A-10 are rectangles contained in the xy plane. The opening surface 811A-10 is located higher in the z-axis direction than the bottom surface 811A-1 and has a larger area than the bottom surface 811A-1. The side surfaces 811A-6 to 811A-9 are rectangles contained in the xz plane or yz plane, respectively, and each contains one of the sides of the opening surface 811A-10. The base surfaces 811A-2 to 811A-5 are inclined surfaces that connect one side of base surface 811A-1 to one side of any of the sides 811A-6 to 811A-9. In other words, the cargo hold 81A has a shape in which the four sides of the base of a rectangular parallelepiped are chamfered, and the base of the cargo hold 81A, which is composed of base surfaces 811A-1 to 811A-5, is not a flat surface.

[0073] In this modified example, the point cloud data acquisition unit 111, grid height calculation unit 112, calculation exclusion identification unit 113, column height calculation unit 114, and volume calculation unit 115 are configured as follows, in addition to the above configuration.

[0074] The point cloud data acquisition unit 111, the grid height calculation unit 112, the unit excluding calculation targets 113, the column height calculation unit 114, and the volume calculation unit 115 perform the same processing as in steps S11 to S15 on a target area (for example, a ship's hold 81A) that does not contain an object (for example, a stone material 90) instead of a target area containing an object. This calculates the reference volume. The reference volume corresponds to the volume of a virtual object if it were assumed that a virtual object with the same surface shape as the inclined bottom surfaces 811A-2 to 811A-5 were placed in the ship's hold 81, which is approximated as a rectangular parallelepiped. Here, even if the stone material 90 is not loaded in the ship's hold 81A, there is a possibility that a bucket 824 is temporarily placed inside the ship's hold 81A. Even in such a case, the grid area corresponding to the bucket 824 is excluded from the calculation, so it is possible to calculate the reference volume without removing the bucket 824.

[0075] The process for calculating the reference volume is performed in advance, for example, before the object (e.g., stone material 90) is placed in the target area (e.g., ship's hold 81A). The reference volume calculated in advance may be stored in the memory unit 120 in association with the identification information of the target area (e.g., ship's hold 81A). Furthermore, the reference volume is not limited to being calculated in the manner described above, but may be calculated by other methods.

[0076] Next, the volume calculation method S1 is performed on the target area (for example, the ship's hold 81A) in which the object (for example, the stone material 90) is contained. However, in this modified example, step S15 is modified as follows.

[0077] In step S15, the volume calculation unit 115 further refers to the reference volume when nothing is stored in the target area (for example, the cargo hold 81A) to calculate the volume of the object. Specifically, the volume calculation unit 115 subtracts the reference volume from the volume calculated by referring to the column height and width of each column, and uses this volume as the volume of the object.

[0078] This allows the volume of the contained object to be calculated without requiring manual labor or computational costs, even when the bottom surface of the target area is not flat.

[0079] In the above-described embodiment 1 and modification 1, examples were given in which the top view shape of the target area is rectangular, such as in the cargo hold 81 and cargo hold 81A, but the invention is not limited to this. For example, the length in the width direction of the top view shape does not have to be constant. In this case, the volume calculation unit 115 can calculate the volume of the object by summing the volumes calculated for each row using the row height and the length in the width direction.

[0080] [Variation 2] In the embodiments described above, an example was given in which the cargo hold 81 of a hoarder 80 is used as an example of the target area, but the target area is not limited to this. For example, the target area may be the space on a surface (for example, a surface called a deck) on a crane ship or barge on which objects can be loaded. The space on such a surface is an example of a loadable space. Such a loadable space does not necessarily have to be demarcated by a physical boundary surface (for example, a wall), and may be a space defined by a virtually defined boundary surface. Furthermore, a crane ship or barge is an example of a work vessel. However, the work vessel is not limited to these examples, and may be any other work vessel capable of accommodating objects.

[0081] [Variation 3] In the embodiments described above, an example was given in which the cargo hold 81 of a hoarder was used as an example of the target area and stone material 90 was used as an example of the target object. However, the target area and target object are not limited to these. For example, an example will be given in which the target area is a surplus soil storage area and the target object is soil and sand.

[0082] Figure 10 shows another example of the target area and soil. As shown in Figure 10, the excavated soil storage area 81B has a shape that approximates a rectangular parallelepiped, with the top surface and one of the four sides open. The backhoe 82B enters the excavated soil storage area 81B from the open side and discharges the soil 90B.

[0083] Additionally, the bucket 824B of the backhoe 82B may be temporarily placed on top of the soil 90B dumped into the soil storage area 81B during periods of temporary work interruption.

[0084] In such cases, the volume calculation system 1 operates similarly by replacing the ship's hold 81 with the excavated soil storage area 81B and the stone material 90 with soil 90B as described above. As a result, the volume calculation system 1 can accurately calculate the volume of soil 90B without having to remove the bucket 824B that is temporarily placed on top of the soil 90B, and while reducing manpower and calculation costs.

[0085] [Embodiment 2] Other embodiments of the present invention are described below. For the sake of clarity, components having the same function as those described in the above embodiments will be denoted by the same reference numerals, and their descriptions will not be repeated.

[0086] The point cloud data processing device 10A according to this embodiment is a device that processes point cloud data acquired from a target area containing an object. For example, examples of the object and target area include the stone material 90 and ship hold 81, similar to those in Embodiment 1. Another example of the target area is the loading space on a crane ship or barge, similar to Modification 2. Yet another example of the object and target area is the soil 90B and excavated soil storage area 81B, similar to Modification 3. However, the object and target area are not limited to these.

[0087] The point cloud data processing device 10A may be provided in place of the server 10 in the volume calculation system 1 according to Embodiment 1, for example. However, the point cloud data processing device 10A can be used for purposes other than volume calculation. The point cloud data processing device 10A can identify points affected by an object other than the object contained in the target area as points to be excluded from calculation in the acquired point cloud data, even if an object other than the object exists on top of the object.

[0088] (Configuration of point cloud data processing device 10A) The point cloud data processing device 10A is configured by a computer similar to that of the server 10, for example. Figure 11 is a block diagram showing the functional configuration of the point cloud data processing device 10A. As shown in Figure 11, the point cloud data processing device 10A includes a control unit 110, a storage unit 120, and a communication unit 130. The control unit 110, the storage unit 120, and the communication unit 130 are described in the same way as the corresponding parts of the server 10. However, the functional block configuration included in the control unit 110 is different.

[0089] The control unit 110 includes a point cloud data acquisition unit 111 and a unit 113A that identifies areas to be excluded from calculation. The point cloud data acquisition unit 111 will be described in the same way as the point cloud data acquisition unit 111 provided in the server 10.

[0090] The calculation exclusion unit 113A identifies points in the point cloud data that have outlier coordinates in the height direction of the target region, for each column arranged in the width direction of the target region, as points to be excluded from calculation without requiring any user operation.

[0091] Furthermore, the exclusion unit 113A may calculate a threshold based on the height coordinates of the point cloud included in the column. Also, the exclusion unit 113A may identify points in the point cloud included in the column where the difference between the height coordinate and the threshold exceeds the upper limit as outliers.

[0092] (Flow of point cloud data processing method S3) The point cloud data processing device 10A, configured as described above, executes the point cloud data processing method S3. Figure 12 is a flowchart illustrating the flow of the point cloud data processing method S3. As shown in Figure 12, the point cloud data processing method S3 includes steps S31 to S34.

[0093] Step S31 is an example of the point cloud data acquisition process. Step S31 will be explained in the same way as the point cloud data acquisition process in Step S11, so a detailed explanation will not be repeated. Each point that makes up the acquired point cloud data is associated with coordinate values ​​that indicate its position in three-dimensional space.

[0094] Step S32 is an example of a threshold calculation process. In step S32, the exclusion-from-calculation-target-determination unit 113 calculates a threshold for each column arranged in the width direction of the target region in the point cloud data, based on the height coordinates of the point clouds contained in that column. For example, the median value may be applied as the threshold, but is not limited to this.

[0095] Step S33 is an example of an outlier identification process. In step S33, the calculation exclusion unit 113 identifies points in the point cloud included in each column where the difference between the coordinate in the height direction and the threshold exceeds the upper limit as outliers. Here, the upper limit may be determined based on the specifications of the object. A specific example of determining the upper limit based on the specifications of the stone material 90 when the object is a stone material 90 is the same as in Embodiment 1, so the details will not be repeated.

[0096] Steps S32 to S33 are an example of a process for identifying points to be excluded from calculation. Instead of performing steps S32 to S33, the point exclusion identification unit 113A may, for example, identify outlier points using a machine learning model. The machine learning model may be a model that has been trained to output outlier points, taking at least the height coordinates of the point cloud included in the column as input. The machine learning model may be an AI model or a model based on other machine learning algorithms.

[0097] In step S34, the control unit 110 outputs information that adds information indicating points not to be included in the calculation to the point cloud data acquired in step S31. Alternatively, the control unit 110 may output a post-removed point cloud data consisting of the remaining points after removing the points not to be included in the calculation from the point cloud data acquired in step S31.

[0098] The point cloud data output by the point cloud data processing method S3 can be used in various processes related to objects contained within the target region. For example, specific examples of various processes related to objects include, but are not limited to, processes for calculating volume and processes for displaying the shape of objects.

[0099] The point cloud data processing device 10A may, like the server 10, divide the target area into grid areas before processing. In this case, the point cloud data processing method S3 further includes a grid height calculation step that calculates the grid height, which indicates the height from the reference plane, based on the point cloud data for each of the multiple grid areas obtained by dividing the target area into a grid pattern when viewed from above. Furthermore, in the calculation exclusion identification step S32-S33, each column arranged in the width direction in the multiple grid areas may be applied as each column, and the grid height may be applied as the coordinate in the height direction, thereby identifying grid areas where the grid height in each column is an outlier as being excluded from calculation. Steps S32-S33, modified in this way, will be explained in the same way as steps S21-S22, which were explained with reference to Figure 4.

[0100] (Effects of this embodiment) The point cloud data processing device 10A and point cloud data processing method S3 according to this embodiment can identify points affected by an object other than the object in point cloud data acquired from a target area containing the object as being excluded from calculation. For example, in point cloud data acquired from a ship's hold 81 loaded with stone 90, even if a bucket 824 is temporarily placed on top of the stone 90, the point cloud affected by the bucket 824 can be identified as being excluded from calculation.

[0101] 〔summary〕 The volume calculation method according to embodiment A1 includes: a point cloud data acquisition step of acquiring point cloud data measured using a three-dimensional sensor from a target area containing an object; a grid height calculation step of calculating a grid height indicating the height from a reference plane based on the point cloud data for each of a plurality of grid regions obtained by dividing the target area into a grid pattern in a top view; a calculation exclusion identification step of a grid region to be excluded from calculation among the plurality of grid regions; a column height calculation step of calculating a column height indicating a representative value of the grid height in each column based on the grid height of each grid region that is not excluded from calculation for each column arranged in the width direction in the plurality of grid regions; and a volume calculation step of calculating the volume of the object by referring to the column height of each column and the width direction length of each column.

[0102] With the above configuration, even if an object other than the object contained within the target region exists on top of it, the grid region containing the point cloud affected by that other object is excluded from the calculation and is not referenced when calculating the volume. As a result, even if an object other than the object exists on the surface above the object contained within the target region, the volume of the object can be calculated with greater accuracy. Furthermore, since there is no need to remove the other object present on top of the object, the volume of the object can be calculated without manual intervention. In addition, since the volume is calculated using the column height, which is a representative value of each column excluding the grid region excluded from the calculation, the calculation cost can be reduced compared to directly referencing the grid height of each grid region.

[0103] The volume calculation method according to embodiment A2, in the volume calculation step of embodiment A1, further refers to the reference volume when nothing is contained in the target area to calculate the volume of the target object.

[0104] With the above configuration, even if the bottom surface of the target area is not flat, the volume of the object contained within the target area can be calculated with high accuracy.

[0105] The volume calculation method according to embodiment A3 calculates the reference volume by performing the point cloud data acquisition step, the grid height calculation step, the exclusion from calculation step, the column height calculation step, and the volume calculation step on the target area in which the object is not contained, instead of the target area in which the object is contained, in embodiment A2.

[0106] With the above configuration, the reference volume can be calculated accurately even if an object other than the target object exists in the target area where the target object is not contained.

[0107] The volume calculation method according to embodiment A4 further includes a display control step of displaying an image on a display device in which display elements corresponding to the grid height of each grid region are added to the image showing the point cloud data in a manner that allows identification of whether or not they are excluded from the calculation.

[0108] With the above configuration, the user can visually identify the grid regions that have been identified as being excluded from the calculation.

[0109] The volume calculation method according to embodiment A5 further includes a display control step of displaying on a display device an image obtained by adding display elements indicating the column height of each column to the image showing the point cloud data, in any one of embodiments A1 to A4.

[0110] With the above configuration, the user can see the representative cross-section formed by the column height of each column.

[0111] The volume calculation method according to embodiment A6 is such that, in any one of embodiments A1 to A5, the target area is the area within the loadable space of the work vessel.

[0112] According to the above configuration, even if there is another object (e.g., a bucket) on top of the object (e.g., stone, soil, etc.) loaded in a space (e.g., a cargo hold, space on the deck, etc.) on a work vessel (e.g., a hopper ship, a crane ship, a barge, etc.) where the object can be loaded, the inspection work can be performed without removing the other object.

[0113] The volume calculation system according to embodiment A7 includes: a point cloud data acquisition unit that acquires point cloud data measured using a three-dimensional sensor from a target area containing an object; a grid height calculation unit that calculates a grid height indicating the height from a reference plane based on the point cloud data for each of a plurality of grid regions obtained by dividing the target area into a grid pattern when viewed from above; a calculation exclusion identification unit that identifies grid regions among the plurality of grid regions that should be excluded from calculation; a column height calculation unit that calculates a column height indicating a representative value of the grid height in each column based on the grid height of each grid region that is not excluded from calculation for each column arranged in the width direction in the plurality of grid regions; and a volume calculation unit that calculates the volume of the object by referring to the column height of each column and the width direction length of each column.

[0114] The above configuration produces the same effect as in embodiment A1.

[0115] The volume calculation program according to embodiment A8 is a volume calculation program for causing a computer to function as the volume calculation device described in embodiment A7, and causes the computer to function as the point cloud data acquisition unit, the grid height calculation unit, the unit for identifying items not to be calculated, the column height calculation unit, and the volume calculation unit.

[0116] The above configuration produces the same effect as in embodiment A1.

[0117] The point cloud data processing method according to embodiment B1 includes a point cloud data acquisition step of acquiring point cloud data measured using a three-dimensional sensor from a target area containing an object, and an exclusion from calculation step of identifying points in the point cloud data where the coordinates in the height direction of the target area are outliers, without requiring user operation.

[0118] According to the above configuration, the influence of different objects present on the upper surface of the object can be removed from the point cloud data measured for the area in which the object is contained.

[0119] The point cloud data processing method according to embodiment B2 further includes a grid height calculation step in which, in embodiment B1, for each of a plurality of grid regions obtained by dividing the target region into a grid pattern in a top view, a grid height indicating the height from a reference plane is calculated based on the point cloud data, and in the calculation exclusion identification step, each column arranged in the width direction in the plurality of grid regions is applied as each column, and the grid height is applied as the coordinate in the height direction, thereby identifying grid regions in each column where the grid height is an outlier as excluded from calculation.

[0120] With the above configuration, outliers can be identified accurately while reducing computational costs by identifying them at the lattice region level.

[0121] The point cloud data processing method according to embodiment B3, in embodiment B1 or B2, includes a threshold calculation step of calculating a threshold based on the height coordinates of the point clouds included in each column, and an outlier identification step of identifying points among the point clouds included in each column where the difference between the height coordinates and the threshold exceeds the upper limit as outliers.

[0122] With the above configuration, outliers can be identified accurately while reducing computational costs by using thresholds and upper limits.

[0123] The point cloud data processing method according to embodiment B4 is such that, in embodiment B3, the object is a stone material, and the upper limit is determined based on the specifications of the stone material.

[0124] According to the above configuration, the influence of objects other than stone present on top of the stone can be precisely removed.

[0125] The point cloud data processing method according to embodiment B5 is such that, in any one of embodiments B1 to B4, the target area is an area within the loadable space of the work vessel.

[0126] According to the above configuration, the influence of objects present on top of objects loaded in a space (e.g., cargo hold, deck space, etc.) on a work vessel (e.g., a hopper ship, a crane ship, a barge, etc.) where objects (e.g., stones, soil, etc.) can be loaded can be accurately eliminated.

[0127] The point cloud data processing system according to embodiment B6 includes a point cloud data acquisition unit that acquires point cloud data measured using a three-dimensional sensor from a target area containing an object, and a calculation exclusion identification unit that identifies points in the point cloud data where the coordinates in the height direction of the target area are outliers, without requiring user operation, for each column arranged in the width direction of the target area.

[0128] The above configuration produces the same effects as in embodiment B1.

[0129] The point cloud data processing program according to embodiment B7 is a point cloud data processing program for causing a computer to function as the point cloud data processing system described in embodiment B6, wherein the computer functions as the point cloud data acquisition unit and the unit for identifying data not to be calculated.

[0130] The above configuration produces the same effects as in embodiment B1.

[0131] [Examples of implementation using software] The functions of each device and the point cloud data processing device 10A (hereinafter referred to as "device") that constitute the volume calculation system 1 can be realized by a program that causes a computer to function as the device, and by a program that causes a computer to function as each control block of the device (in particular, each part included in the control unit 110).

[0132] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., memory) as hardware for executing the program. By executing the program using this control device and storage device, the functions described in each of the embodiments are realized.

[0133] The above program may be recorded on one or more computer-readable recording media, not temporary ones. These recording media may or may not be provided by the above device. In the latter case, the program may be supplied to the above device via any wired or wireless transmission medium.

[0134] Furthermore, some or all of the functions of each of the above control blocks can also be realized by logic circuits. For example, an integrated circuit in which logic circuits functioning as each of the above control blocks are formed is also included in the scope of the present invention. In addition, it is also possible to realize the functions of each of the above control blocks by, for example, a quantum computer.

[0135] Furthermore, each process described in the above embodiments may be performed by AI (Artificial Intelligence). In this case, the AI ​​may operate on the control device described above, or it may operate on other devices (for example, an edge computer or a cloud server).

[0136] [Additional Notes] The present invention is not limited to the embodiments described above, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. [Explanation of Symbols]

[0137] 1. Volume Calculation System 10 servers 10A Point Cloud Data Processing Unit 20 devices 30 LiDAR 80 Gat ship 81, 81A cargo hold 81B Soil storage area 824, 824B bucket 90 Stone 90B Soil and sand 110, 210 Control Unit 111 Point cloud data acquisition unit 112 Grid height calculation unit 113, 113A Specific parts excluded from calculation 114 Column Height Calculation Unit 115 Volume Calculation Unit 116 Display Control Unit 120, 220 storage section 130, 230 Communications Department 211 Volume calculation UI part 240 Input section 250 Display section 260 Peripheral device connection section S1 Volume calculation method S3 Point Cloud Data Processing Method S11 Point cloud data acquisition process S12 Grid height calculation process S13 Specific processes excluded from calculation S14 Column Height Calculation Process S15 Volume calculation process

Claims

1. A point cloud data acquisition process is performed to acquire point cloud data measured using a three-dimensional sensor from a target area containing an object, A grid height calculation step is performed for each of the multiple grid regions obtained by dividing the target region into a grid pattern when viewed from above, and for each of these grid regions, a grid height indicating the height from the reference plane is calculated based on the point cloud data. A step of identifying grid regions that should be excluded from calculations among the aforementioned plurality of grid regions, A column height calculation step for each column arranged in the width direction in the plurality of grid regions, which calculates a representative value of the grid height in that column based on the grid height of each grid region that is not excluded from the calculation, A volume calculation step in which the volume of the object is calculated by referring to the column height and the width of each column, A method for calculating volume, including the following.

2. In the volume calculation step, the volume of the object is calculated by further referring to the reference volume when nothing is contained in the target area. The volume calculation method according to claim 1.

3. The reference volume is calculated by performing the point cloud data acquisition step, the grid height calculation step, the calculation of areas not to be calculated, the column height calculation step, and the volume calculation step on the target area not to be The volume calculation method according to claim 2.

4. The process further includes a display control step of displaying an image on a display device in which display elements corresponding to the grid height of each grid region are added to the image showing the point cloud data in a manner that allows for identification of whether or not they are excluded from the calculation. The volume calculation method according to claim 1 or 2.

5. The process further includes a display control step of displaying an image on a display device in which display elements indicating the column height of each column have been added to the image showing the point cloud data. The volume calculation method according to claim 1 or 2.

6. The aforementioned target area is the area within the loading space of the work vessel. The volume calculation method according to claim 1 or 2.

7. A point cloud data acquisition unit that acquires point cloud data measured using a three-dimensional sensor from a target area containing an object, A grid height calculation unit calculates a grid height, which indicates the height from the reference plane, for each of the multiple grid regions obtained by dividing the target region into a grid pattern when viewed from above, based on the point cloud data. A calculation exclusion identification unit that identifies grid regions that should be excluded from calculation among the aforementioned plurality of grid regions, A column height calculation unit calculates a column height that represents a representative value of the grid height in a given column, based on the grid height of each grid region that is not excluded from the calculation, for each column arranged in the width direction in the plurality of grid regions. A volume calculation unit calculates the volume of the object by referring to the column height and width of each of the aforementioned columns, A volume calculation system that includes this.

8. A volume calculation program for causing a computer to function as the volume calculation system described in claim 7, comprising: a point cloud data acquisition unit, a grid height calculation unit, a unit for identifying units not to be calculated, a column height calculation unit, and a volume calculation unit, wherein the computer functions as the point cloud data acquisition unit, the grid height calculation unit, the unit for identifying units not to be calculated, the column height calculation unit, and the volume calculation unit.

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