Measurement system, measurement method, and measurement program

Abstract

To improve the position measurement of a cargo vehicle.SOLUTION: The measurement system includes a laser measurement device installed above a preset parking area, and a measurement processing part for calculating the position information of the cargo vehicle stopped in the parking area based on the output of the laser measurement device. The laser measuring device scans a laser beam along the longitudinal direction of the parking area and receives reflected light of the laser beam to acquire point group data along the longitudinal direction. The measurement processing unit extracts a loading platform point cloud located on an upper surface of the loading platform of the freight vehicle from the point cloud data, and calculates a front end position and a rear end position of the upper surface of the loading platform based on the extracted loading platform point cloud.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present disclosure relates to a measurement system, a measurement method, and a measurement program. [Background technology]

[0002] There is known a technology for performing cargo handling operations such as loading and unloading cargo from trucks and other freight vehicles using a mobile object that moves automatically and transports objects such as luggage. Furthermore, there is known a technology for measuring the stopping position of a freight vehicle so that the mobile object automatically approaches the freight vehicle. For example, Patent Document 1 describes a positioning system that identifies the position of a cargo bed in a parking space by capturing an image of a vehicle parked in the parking space with an imaging unit installed above the parking space and extracting feature points from the captured image to estimate the shape of the cargo bed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-109063 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology in Patent Document 1 has problems such as a large limit on the size of vehicles that can be detected because the vehicle must be contained within the angle of view of the imaging unit, the possibility that feature point extraction may not be performed properly for vehicles with unexpected shapes, and the extraction of feature points from images is susceptible to disturbances that affect image quality, such as sunlight reflection.There is a need for improvements in freight vehicle position measurement.

[0005] The present disclosure has been made in consideration of the above, and aims to provide a measurement system, a measurement method, and a measurement program that can improve the position measurement of freight vehicles. [Means for solving the problem]

[0006] The measurement system disclosed herein comprises a laser measurement device installed above a predetermined parking area, and a measurement processing unit that calculates position information of a cargo vehicle parked in the parking area based on the output of the laser measurement device, wherein the laser measurement device scans a laser beam along the longitudinal direction of the parking area and receives reflected light of the laser beam to obtain point cloud data along the longitudinal direction, and the measurement processing unit extracts a loading platform point cloud located on the top surface of the loading platform of the cargo vehicle from the point cloud data and calculates the front and rear end positions of the top surface of the loading platform based on the extracted loading platform point cloud.

[0007] The measurement method disclosed herein includes the steps of: a laser measurement device installed above a predetermined parking area scans a laser beam along the longitudinal direction of the parking area and receives reflected light of the laser beam, thereby acquiring point cloud data along the longitudinal direction; extracting a loading platform point cloud located on the top surface of the loading platform of a cargo vehicle parked in the parking area from the point cloud data; and calculating the front end position and rear end position of the top surface of the loading platform based on the extracted loading platform point cloud.

[0008] The measurement program of the present disclosure causes a computer to execute the following steps: acquiring point cloud data along the longitudinal direction of a predetermined parking area, generated by a laser measurement device installed above the parking area scanning a laser beam along the longitudinal direction of the parking area and receiving reflected light of the laser beam; extracting a loading platform point cloud located on the top surface of the loading platform of a cargo vehicle parked in the parking area from the point cloud data; and calculating the front end position and rear end position of the top surface of the loading platform based on the extracted loading platform point cloud. [Effects of the Invention]

[0009] The present disclosure provides improved position measurement of freight vehicles. [Brief explanation of the drawings]

[0010] [Figure 1]FIG. 1 is a schematic diagram of a measurement system according to this embodiment. [Figure 2] FIG. 2 is a schematic block diagram of the management device. [Figure 3] FIG. 3 is a schematic block diagram of an information processing device. [Figure 4] FIG. 4 is a diagram illustrating the installation position of the laser measurement device according to the embodiment. [Figure 5] FIG. 5 is a schematic side view showing a measurement technique using a laser measurement device. [Figure 6] FIG. 6 is a flowchart showing an example of the operation of the measurement system according to this embodiment. [Figure 7] FIG. 7 is a schematic diagram for explaining the processing for estimating the height and inclination of the loading platform. [Figure 8] FIG. 8 is a schematic diagram illustrating extraction of the loading platform point cloud. [Figure 9] FIG. 9 is a schematic diagram showing the front and rear end positions of the upper surface of the loading platform. [Figure 10] FIG. 10 is a diagram for explaining the determination of the type of freight vehicle. [Figure 11] FIG. 11 is a schematic diagram illustrating the calculation of the calibration parameters of the installation height and the pitch angle. [Figure 12] FIG. 12 is a diagram illustrating a regression line calculated from point cloud data of the reference plane. [Figure 13] FIG. 13 is a schematic diagram illustrating the calculation of the calibration parameters for the X direction position and the yaw angle. [Figure 14] FIG. 14 is a diagram illustrating point cloud data of the reference plane. [Figure 15] FIG. 15 is a diagram for explaining measurement by the front measurement device according to the third embodiment. [Figure 16] FIG. 16 is a diagram for explaining measurement by the rear measurement device according to the third embodiment. [Figure 17] FIG. 17 is a diagram showing the first measuring device and the second measuring device according to the fourth embodiment. [Figure 18]FIG. 18 is a diagram illustrating the stopping angle of a freight vehicle in the fourth embodiment. [Figure 19] FIG. 19 is a diagram illustrating a process of detecting a stopped vehicle based on a time-series change in point cloud data. [Figure 20] FIG. 20 is a diagram illustrating the process of detecting whether a vehicle is stopped and whether the loading platform is open or closed based on time-series changes in point cloud data. [Figure 21] FIG. 21 is a flowchart showing an example of the operation of the measurement system according to the sixth embodiment. [Figure 22] FIG. 22 is a schematic diagram for explaining a method for calculating a regression line according to the seventh embodiment. [Figure 23] FIG. 23 is a diagram showing a laser measurement device according to the eighth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Note that the present disclosure is not limited to these embodiments, and when there are multiple embodiments, the present disclosure also includes configurations in which the respective embodiments are combined.

[0012] (measurement system) FIG. 1 is a schematic diagram of a measurement system according to this embodiment. As shown in FIG. 1, the measurement system 100 according to this embodiment is configured as part of a mobile object control system including a mobile object 10, a management device 12, and an information processing device 14. The mobile object control system is a system that controls the movement of the mobile object 10 belonging to a facility W. The facility W is, for example, a facility that is managed by logistics, such as a warehouse, but may be any facility that operates the mobile object 10. In the mobile object control system, the mobile object 10 picks up an object P placed within the facility W, transports it, and drops it at another location. In this embodiment, the object P transported by the mobile object 10 is a transport object in which cargo is loaded on a pallet. However, the object P is not limited to a pallet in which cargo is loaded, and may be in any form, for example, it may be cargo only without a pallet. The mobile object 10 loads and unloads the object P onto a freight vehicle V parked in a parking area 1 within the facility W.

[0013] (work area) As shown in Fig. 1, a work area AR is set in the facility W. The work area AR is an area where the moving body 10 of this embodiment performs predetermined work such as loading and unloading work. The work area AR includes a first area AR1 and a second area AR2. Note that the layout of the work area AR described below is an example and may be set as appropriate.

[0014] The first area AR1 is provided with a parking area 1. The mobile object 10 is capable of moving within the first area AR1. However, the mobile object 10 loads and unloads objects P onto and from cargo vehicles V parked in the parking area 1 of the first area AR1.

[0015] The first area AR1 is a so-called truck berth. The parking area 1 is an area for parking freight vehicles V. The freight vehicles V are parked in a predetermined position and posture relative to the parking area 1. A guide unit 2 indicating the outline of the parking area 1 is provided in the first area AR1. The guide unit 2 is a sign or structure that serves as a landmark to enable the driver of the freight vehicle V to recognize the parking area 1 and park the freight vehicle V in a predetermined parking position and posture. The sign that serves as a landmark is a line or colored area marked on the ground in the first area AR1, such as a white line. The structure that serves as a landmark is, for example, a step or groove formed on the ground in the first area AR1.

[0016] The cargo vehicle V is a motor vehicle (i.e., a truck) that primarily transports cargo. The cargo vehicle V carries and transports an object P. The cargo vehicle V includes a cabin V1 with a driver's seat, a cargo bed V2, and a chassis with tires and a drive mechanism. The cabin V1 is located at the front of the cargo vehicle V, and the cargo bed V2 is located behind the cabin V1. The cargo bed V2 provides a space for carrying cargo. The cargo bed V2 has, for example, a rectangular parallelepiped shape and has an accommodation chamber inside that can accommodate the object P. The cargo bed V2 has a portion of its peripheral wall that can be opened and closed, and cargo can be loaded and unloaded by opening the cargo bed V2, and cargo can be stored when the cargo bed V2 is closed. In one example, the cargo vehicle V is a gull-wing type truck. The gull-wing type refers to a cargo bed structure in which the side of the cargo bed V2 rotates around a hinge located on the top surface of the cargo bed V2, making substantially the entire side of the cargo bed V2 openable and closable. However, the structure of the cargo vehicle V and the structure of the loading platform V2 are not particularly limited.

[0017] In FIG. 1, for convenience, only one parking area 1 is shown in the first area AR1, but a plurality of parking areas 1 may be provided.

[0018] The second area AR2 is located adjacent to the first area AR1. The second area AR2 is a storage location for the facility W, such as a logistics warehouse. The mobile body 10 can, for example, pick up an object P loaded onto a cargo vehicle V in the first area AR1 and load the object P into a predetermined position in the second area AR2. The mobile body 10 can, for example, pick up an object P placed in the second area AR2 and load the object P into a cargo vehicle V in the first area AR1.

[0019] (Waypoint) In the working area AR, a waypoint WP is set for each position (coordinate). The movement route of the moving body 10 is set so as to connect the waypoints WP. In other words, the movement route of the moving body 10 is the route connecting the waypoints WP that the moving body 10 is scheduled to pass through.

[0020] The moving body 10 is a device that can move automatically. There are no particular limitations on the structure of the moving body 10. In this embodiment, the moving body 10 is a forklift, more specifically, a so-called AGV (Automated Guided Vehicle) or AGF (Automated Guided Forklift). However, the moving body 10 is not limited to a forklift that transports a target object, and may be any device that can move automatically. Based on information received from the information processing device 14, the moving body 10 moves along a movement path connecting the source and destination of the target object P, and automatically performs loading and unloading work on the target object P.

[0021] (Management device) FIG. 2 is a schematic block diagram of a management device. The management device 12 is a system that manages logistics in the facility W. In this embodiment, the management device 12 is a WCS (Warehouse Control System) or a WMS (Warehouse Management System), but is not limited to a WCS or a WMS and may be any system, for example, a back-end system such as another production management system. The location where the management device 12 is installed is arbitrary, and the management device 12 may be installed within the facility W or at a location remote from the facility W to manage the facility W from that location. The management device 12 is a computer, and as shown in FIG. 3, includes a communication unit 30, a memory unit 32, and a control unit 34.

[0022] The communication unit 30 is a module used in the control unit 34 to communicate with external devices such as the information processing device 14, and may include, for example, an antenna. In this embodiment, the communication method used by the communication unit 30 is wireless communication, but any communication method may be used. The storage unit 32 is a memory that stores various information such as the calculation contents and programs of the control unit 34, and includes, for example, at least one of a main storage device such as a RAM (Random Access Memory), a ROM (Read Only Memory), and an external storage device such as an HDD (Hard Disk Drive).

[0023] The control unit 34 is a computing device and includes a computing circuit such as a CPU (Central Processing Unit). The control unit 34 includes an information acquisition unit 40 and a transfer instruction unit 42. The control unit 34 implements the information acquisition unit 40 and the transfer instruction unit 42 and executes the processes thereof by reading and executing a program (software) from the storage unit 32. The control unit 34 may execute the processes using a single CPU, or may be provided with multiple CPUs and execute the processes using the multiple CPUs. At least a portion of the information acquisition unit 40 and the transfer instruction unit 42 may be implemented using hardware circuits. The program for the control unit 34 stored in the storage unit 32 may be stored in a recording medium readable by the management device 12.

[0024] The information acquisition unit 40 acquires information such as the estimated arrival time of the freight vehicle V moving toward the facility W, the number of objects P to be loaded on the freight vehicle V, and the availability of the second area AR2 of the facility W. The transport instruction unit 42 generates transport instruction information based on the acquired information and causes the communication unit 30 to transmit the generated transport instruction information.

[0025] (Information processing device) FIG. 3 is a schematic block diagram of an information processing device. The information processing device 14 is a device that processes information related to the movement of the mobile object 10. The information processing device 14 is, for example, a fleet control system (FCS), but is not limited thereto and may be any device that processes information related to the movement of the mobile object 10. The information processing device 14 is a computer and, as shown in FIG. 3, includes a communication unit 50, a storage unit 52, and a control unit 54. The communication unit 50 is a module used by the control unit 54 to communicate with external devices such as the management device 12 and the mobile object 10, and may include, for example, an antenna. In this embodiment, the communication method used by the communication unit 50 is wireless communication, but any communication method may be used. The storage unit 52 is a memory that stores various information such as the calculation contents and programs of the control unit 54, and includes, for example, at least one of a RAM, a main storage device such as a ROM, and an external storage device such as an HDD.

[0026] The control unit 54 is a calculation device and includes a calculation circuit such as a CPU. The control unit 54 includes an information processing unit 60 and a measurement processing unit 62. The control unit 54 implements the information processing unit 60 and the measurement processing unit 62 by reading and executing a program (software) from the storage unit 52. The control unit 54 executes these processes by using a single CPU, or may be provided with multiple CPUs and execute the processes by using the multiple CPUs. At least a portion of the information processing unit 60 and the measurement processing unit 62 may be implemented by hardware circuits. The program for the control unit 54 stored in the storage unit 52 may be stored in a recording medium readable by the information processing device 14.

[0027] The information processing unit 60 acquires transport instruction information transmitted from the management device 12. The information processing unit 60 sets work instructions for the mobile body 10 based on the acquired information. The measurement processing unit 62 acquires the output (measurement results) of the laser measurement device 16 via the communication unit 50. The measurement processing unit 62 calculates position information of the cargo vehicle V parked in the parking area 1 based on the output of the laser measurement device 16.

[0028] In this embodiment, the management device 12 and the information processing device 14 are separate devices, but they may be integrated into one device. That is, the management device 12 may have at least some of the functions of the information processing device 14, and the information processing device 14 may have at least some of the functions of the management device 12.

[0029] (measurement system) The measurement system 100 according to the embodiment includes a laser measurement device 16 and a measurement processing unit 62. In the measurement system 100 configured as a part of a mobile object control system, the measurement processing unit 62 is provided in the information processing device 14. That is, the control unit 54 of the information processing device 14 executes a measurement program 66 stored in the storage unit 52 to realize the measurement processing unit 62 of the measurement system 100. The measurement processing unit 62 may be provided in the management device 12. Furthermore, the measurement system 100 according to the embodiment may be realized by a computer independent of the management device 12 and the information processing device 14 of the mobile object control system. In that case, the measurement system 100 may be configured to provide the mobile object control system with position information calculated by the measurement processing unit 62 through communication processing between the computer and the management device 12 and the information processing device 14.

[0030] The measurement system 100 is a system that measures the stopping position of a freight vehicle V parked in a parking area 1 within a facility W. The measurement system 100 measures the position of the freight vehicle V parked in the parking area 1 using a laser measurement device 16. The measurement system 100 calculates position information of the freight vehicle V from the measurement data using a measurement processing unit 62. Based on the position information calculated by the measurement system 100, a target position is set when the mobile body 10 performs loading and unloading work of an object P on the freight vehicle V.

[0031] FIG. 4 is a diagram illustrating the installation position of a laser measurement device according to an embodiment. A coordinate system used to calculate the position information of a cargo vehicle V will be described. A measurement coordinate system is set in the parking area 1. The parking area 1 is, for example, rectangular along a predetermined direction of the first area AR1. The parking area 1 has a shape corresponding to the dimensions of one cargo vehicle V. The longitudinal direction (direction along the long side) of the parking area 1 is the X direction, the lateral direction (direction along the short side) of the parking area 1 is the Y direction, and the up-down direction is the Z direction. The Z direction is a vertical direction perpendicular to the X and Y directions. The stopping position and posture (vehicle orientation) of the cargo vehicle V when stopped in the parking area 1 are set in advance and known. One end side (+X side) of the parking area 1 in the longitudinal direction is the front side, and the other end side (-X side) is the rear side. One end side (+Y side) of the parking area 1 in the lateral direction is the left side, and the other end side (-Y side) is the right side.

[0032] That is, the parking area 1 is displayed with the outline of the parking area 1 by the guide unit 2, and is also provided with markers such as white lines (not shown) that indicate the stopping position. Using the guide unit 2 and other markers as clues, the driver stops the cargo vehicle V in a predetermined stopping position in the parking area 1 as shown in FIG. 4 so that the cargo vehicle V is in a predetermined stopping position. The driver is instructed to stop the cargo vehicle V with its fore-and-aft direction aligned with the X direction and its front side facing the +X direction. The driver is instructed to stop the cargo vehicle V so that the rear end position of the cargo vehicle V is located at a predetermined position in the X direction of the parking area 1 and the left-right direction of the cargo vehicle V is located at the middle position in the Y direction of the parking area 1.

[0033] Based on the above positional relationship, the origin O of the measurement coordinate system is set to a position near the rear end of the parking area 1 and in the center in the left-right direction. In particular, with regard to the X coordinate, the origin O coincides with the normal parking position of the cargo vehicle V (the position of the rear end of the cargo vehicle V). Furthermore, the direction of rotation around the X axis is defined as the roll direction, the direction of rotation around the Y axis as the pitch direction, and the direction of rotation around the Z axis as the yaw direction.

[0034] FIG. 5 is a schematic side view illustrating a measurement method using a laser measurement device. As shown in FIGS. 4 and 5, in this embodiment, the laser measurement device 16 is installed above a predetermined parking area 1. The laser measurement device 16 is installed, for example, on the eaves 3 of a truck berth. The laser measurement device 16 is a laser-type distance measuring device. The laser measurement device 16 scans a laser beam along the longitudinal direction (X direction) of the parking area 1 and receives reflected laser beams to acquire point cloud data 70 along the longitudinal direction. As shown in FIG. 4, the laser measurement device 16 is installed at a height position a predetermined distance in the Z direction from the ground of the parking area 1. The laser measurement device 16 is provided directly above the X axis passing through the origin O. The installation height H11 of the laser measurement device 16 is greater than the height dimension of a freight vehicle V parked in the parking area 1. The laser measurement device 16 is installed at a position a predetermined distance L11 in the X direction from the origin O in the +X direction. The X-direction position of the laser measurement device 16 is set, for example, to be between the front and rear ends of the freight vehicle V parked in the parking area 1. The Y-direction position of the laser measurement device 16 is set to the middle (origin position) in the Y direction of the parking area 1. Therefore, in the example of FIG. 4, the measurement plane (scanning trajectory of the laser light) by the laser measurement device 16 is on the X-axis line that passes through the origin O and is parallel to the XZ plane.

[0035] The laser measurement device 16 according to the embodiment is a so-called two-dimensional (2D) LiDAR (Light Detection and Ranging). The laser measurement device 16 includes a laser light source, a scanning mechanism, and a light receiving element. The laser measurement device 16 may be configured to acquire point cloud data 70 along the X direction by mounting a one-dimensional laser ranging sensor on a moving mechanism that moves on rails or the like along the X direction. The laser measurement device 16 may also be a so-called three-dimensional (3D) LiDAR that can scan laser light in multiple directions including the longitudinal direction (X direction).

[0036] In this manner, the laser measurement device 16 measures the positions of the bed V2 and the upper surface of the cabin V1 of the cargo vehicle V along the longitudinal direction from above the cargo vehicle V parked in the parking area 1. The acquired point cloud data 70 is a collection of irradiation points (measurement points 71) of the laser light on the surface of the cargo vehicle V in the XZ plane. The measurement points 71 are individual points included in the point cloud data 70. The position coordinates of each measurement point 71 in the XZ plane can be acquired from the point cloud data 70. In this embodiment, the measurement system 100 includes one laser measurement device 16, and the measurement range (laser scanning angle range in the pitch direction) of the laser measurement device 16 is set with respect to the parking area 1 so as to acquire a point cloud in a range including the front and rear ends of the bed V2 of the cargo vehicle V. Note that an air guide plate V3 (see FIG. 5) may be provided above the cabin V1. The point cloud data 70 may include points on the bed upper surface V4 and points on the upper surface of the cabin V1 or the upper surface of the air guide plate V3.

[0037] In the embodiment, the measurement processing unit 62 extracts a platform point cloud 74 located on the platform upper surface V4 of the cargo vehicle V from the point cloud data 70, and calculates the front end position Pf and rear end position Pr (see FIG. 9) of the upper surface of the platform V2 based on the extracted platform point cloud 74. Then, the measurement processing unit 62 acquires the stopping position of the cargo vehicle V in the longitudinal direction and length information (length LB) of the platform V2 of the cargo vehicle V based on the calculated front end position Pf and rear end position Pr. In the embodiment, the stopping position of the cargo vehicle V is based on the rear end of the cargo vehicle V, i.e., the rear end position Pr of the platform V2.

[0038] (Measurement system processing) The processing contents of the measurement system 100 are described below. Fig. 6 is a flowchart showing an example of the operation of the measurement system 100 according to this embodiment. The processing in Fig. 6 is executed by the measurement processing unit 62. In other words, the control unit 54 executes the measurement program 66 to realize the function of the measurement processing unit 62, thereby executing the processing of each step shown in Fig. 6.

[0039] First, the laser measurement device 16 acquires point cloud data 70 (step S10). The laser measurement device 16 scans a laser beam along the longitudinal direction (X direction) of the parking area 1 and receives reflected laser light to acquire point cloud data 70 along the longitudinal direction. The information processing device 14 acquires the point cloud data 70 from the laser measurement device 16 via the communication unit 50. As a result, the measurement processing unit 62 acquires the point cloud data 70 as an output of the laser measurement device 16.

[0040] The measurement processing unit 62 executes processing for estimating the height and tilt of the loading platform (step S11). Fig. 7 is a schematic diagram for explaining processing for estimating the height and tilt of the loading platform.

[0041] As shown in Fig. 7, the point cloud data 70 obtained by the laser measurement device 16 includes measurement points on the upper surface V4 of the loading platform and measurement points other than the loading platform V2 (such as measurement points on the upper surface of the air guide plate V3). The measurement processing unit 62 calculates a regression line 76A based on a point cloud 72 located on the rear side of the cargo vehicle V, excluding the point cloud located on the front side of the point cloud data 70. In Fig. 7, the point cloud 72 located on the rear side is indicated by solid dots, and the point clouds other than the point cloud 72 located on the rear side (point clouds located on the front side) are indicated by open dots.

[0042] 7, the measurement processing unit 62 calculates a regression line 76A by using the point cloud included in a measurement area 78 that is set in advance in the parking area 1 to cover a range including the rear of the cargo vehicle V as the point cloud 72 located on the rear side. The measurement area 78 is an area set on the XZ plane in the parking area 1 to include a portion of the point cloud data 70. The measurement area 78 is set in advance based on prior information such as the type and size range of the cargo vehicle V used in the facility W.

[0043] The measurement area 78 is set to extend rearward (in the -X direction) from the origin O. The distance K1 from the origin O to the rear end of the measurement area 78 is set to a predetermined distance that takes into account variations in the planned stopping position (X coordinate of the origin O). The distance K2 from the origin O to the front end of the measurement area 78 is set to a distance that does not include the cabin V1 (air guide plate V3) of the vehicle with the shortest overall length, in accordance with the vehicle with the shortest overall length among the cargo vehicles V to be measured. The lower end height K3 of the measurement area 78 is set to a distance that is lower than the top surface of the loading platform V2 of the vehicle with the shortest overall height. The upper end height K4 of the measurement area 78 is set to a position higher than the top surface of the loading platform V2 of the vehicle with the highest overall height.

[0044] As a result, the measurement processing unit 62 extracts points included in a predetermined measurement area 78 from the point cloud data 70, thereby extracting a point cloud 72 located on the rear side of the cargo vehicle V. The point cloud 72 located on the rear side includes points on the loading platform V2 of the vehicle, regardless of variations in size of the parked cargo vehicle V, but does not include points on the cabin V1 (air guide plate V3) of the vehicle.

[0045] The measurement processing unit 62 calculates a regression line 76A of the point cloud 72 based on an estimation method such as RANSAC (Random Sample Consensus) from the position coordinates of the extracted point cloud 72. Because the point cloud 72 does not include points on the cabin V1 (air guide plate V3), the regression line 76A is a straight line that follows the loading platform upper surface V4. The height (intercept) of the regression line 76A corresponds to the height of the loading platform upper surface V4, and the slope of the regression line 76A corresponds to the slope of the loading platform upper surface V4.

[0046] The measurement processing unit 62 extracts the loading platform point cloud 74 (step S12). The measurement processing unit 62 extracts a point cloud within the distance threshold Ht from the regression line 76A from the point cloud data 70 as the loading platform point cloud 74. The loading platform point cloud 74 is a set of points on the loading platform upper surface V4.

[0047] FIG. 8 is a schematic diagram illustrating the extraction of the platform point cloud. The distance threshold Ht is set to distinguish between points on the platform top surface V4 and points on the cabin V1 or the air guide plate V3. Among all point cloud data 70, including not only the point cloud 72 located on the rear side of the cargo vehicle V but also the point cloud located on the front side of the cargo vehicle V, points whose distance from the regression line 76A is within the distance threshold Ht are considered to be located on the platform top surface V4. Points whose distance from the regression line 76A is greater than the distance threshold Ht and that are farther from the regression line 76A are considered to be located somewhere other than the platform top surface V4, such as on the top surface of the cabin V1 or the air guide plate V3. The measurement processing unit 62 then extracts a platform point cloud 74 from the point cloud data 70, which is a collection of all points located on the platform top surface V4. The platform point cloud 74 includes measurement points 71 located at the front and rear ends of the platform top surface V4.

[0048] The measurement processing unit 62 calculates the front end position Pf and the rear end position Pr of the upper surface of the loading platform V2 (step S13).

[0049] 9 is a schematic diagram showing the front and rear end positions of the upper surface of the loading platform. The measurement processing unit 62 calculates a regression line 76B of the loading platform point cloud 74 based on the position coordinates of the extracted loading platform point cloud 74 using an estimation method such as RANSAC (Random Sample Consensus). The regression line 76B is a regression line calculated from all measurement points 71 on the loading platform upper surface V4, and therefore reflects the position and tilt of the loading platform upper surface V4 more accurately than the regression line 76A. The measurement processing unit 62 determines the position of the foot of a perpendicular line (the intersection of the perpendicular line and the regression line 76B) drawn from the measurement point 71A (the point with the smallest X coordinate) at the rear end of the loading platform point cloud 74 to the regression line 76B as the rear end position Pr of the loading platform upper surface V4. The measurement processing unit 62 determines the position of the foot of a perpendicular line (the intersection of the perpendicular line and the regression line 76B) drawn from the measurement point 71B (the point with the largest X coordinate) at the front end of the platform point cloud 74 to the regression line 76B as the front end position Pf of the platform upper surface V4. In this way, the measurement processing unit 62 obtains the front end position Pf and the rear end position Pr of the upper surface of the platform V2.

[0050] The measurement processing unit 62 acquires the stopping position of the cargo vehicle V in the longitudinal direction and length information of the bed V2 of the cargo vehicle V based on the calculated front end position Pf and rear end position Pr (step S14). As described above, in this embodiment, the measurement processing unit 62 determines the rear end position Pr of the bed top surface V4 as the stopping position of the cargo vehicle V in the longitudinal direction. In this way, the measurement system 100 measures the stopping position of the cargo vehicle V stopped in the parking area 1. In addition, the measurement processing unit 62 determines the distance between the front end position Pf and the rear end position Pr as the length LB (length information) of the bed V2.

[0051] In this embodiment, the measurement processing unit 62 determines the type of the cargo vehicle V based on the length information of the loading platform V2 (step S15).

[0052] FIG. 10 is a diagram for explaining the classification of the freight vehicle. As shown in FIG. 10, in the embodiment, classification data 68 defining the correspondence between the length LB of the loading platform V2 and the type of the freight vehicle V is stored in the storage unit 52 in advance. The type of the freight vehicle V is not particularly limited. In the example of FIG. 10, it is information for classifying the freight vehicle V based on the maximum number of pallets that can be arranged when the pallets of the object P are arranged in the storage space of the loading platform V2. In the classification data 68 shown in FIG. 10, when the length LB of the loading platform V2 is "equal to or more than D1 m and less than D2 m", it is a vehicle type (typeA) capable of arranging the first number of pallets, and when the length LB of the loading platform V2 is "equal to or more than D2 m and less than D3 m", it is a vehicle type (typeB) capable of arranging the second number of pallets, and such a correspondence is defined. Note that D1 < D2 < D3. The measurement processing unit 62 determines the type of the freight vehicle V measured this time based on which section of the classification data 68 the length LB of the loading platform V2 corresponds to. As a result, the measurement system 100 can obtain the number of pallets (that is, the object P) that can be loaded side by side on the freight vehicle V parked in the parking area 1.

[0053] In the first embodiment, the measurement system 100 obtains the parking position of the freight vehicle V and the number of objects P that can be loaded side by side on the freight vehicle V as described above, and ends the measurement process.

[0054] Note that the information processing unit 60 of the information processing device 14 adjusts the approach position to the loading platform V2 of the moving body 10 based on the parking position of the freight vehicle V and the number of loadable pallets. Thereby, the moving body 10 can move to the approach position of the loading platform V2 of the freight vehicle V and perform loading and unloading of the object P.

[0055] <{ As described above, in this embodiment, the laser measurement device 16 acquires point cloud data 70 along the longitudinal direction (X direction) of the parking area 1, extracts the bed point cloud 74 located on the bed top surface V4 of the cargo vehicle V from the point cloud data 70, and calculates the front end position Pf and rear end position Pr of the top surface of the bed V2 based on the extracted bed point cloud 74. This makes it easier to measure a wider range than when capturing images using an imaging device. Furthermore, unlike when extracting feature points in an image, position calculation can be performed even if the shape of the cargo vehicle V is unexpected, and measurement can be performed with less influence from sunlight reflection, etc. These features enable improved position measurement of the cargo vehicle V.

[0056] (Second embodiment) Next, a second embodiment will be described. The second embodiment will describe an example in which calibration parameters related to the position and orientation of the laser measurement device 16 are calculated using point cloud data acquired by the laser measurement device 16. In the second embodiment, descriptions of parts that have the same configuration as the first embodiment will be omitted.

[0057] In the measurement system 100 according to the second embodiment, the measurement processing unit 62 calculates calibration parameters related to the position and orientation of the laser measurement device 16 based on point cloud data 70 of the reference plane RS acquired by the laser measurement device 16 when no cargo vehicle V is present in the parking area 1 and known position and orientation information of the reference plane RS. The position and orientation information includes position information (X coordinate, Y coordinate, Z coordinate) and orientation information (roll angle, pitch angle, yaw angle). If the installation position and installation orientation of the laser measurement device 16 deviate from the designed position and orientation, errors will occur in the measurement results. Therefore, the deviation of the position and orientation of the laser measurement device 16 is calculated as calibration parameters, and the measurement results are corrected based on the calibration parameters. Normally, the calibration parameters are acquired by precisely measuring the position and orientation of the laser measurement device 16 in the installed state. However, in the second embodiment, the calibration parameters are calculated from the point cloud data 70 of the reference plane RS acquired by the laser measurement device 16. The calibration parameters are acquired as a calibration operation when no loading and unloading operations are being performed in the facility W.

[0058] FIG. 11 is a schematic diagram illustrating the calculation of calibration parameters for the installation height and pitch angle. In the example of FIG. 11, the reference plane RS is the ground (floor) of the parking area 1. The laser measurement device 16 performs laser light scanning when no vehicle is present in the parking area 1, and acquires point cloud data 70 of the reference plane RS. The position and attitude (tilt) of the reference plane RS are known. Here, the reference plane RS is considered to be parallel to the XY plane passing through the origin O. The point cloud data 70 of the reference plane RS is located on a straight line extending from the origin O along the X direction (i.e., the X axis).

[0059] FIG. 12 is a diagram illustrating a regression line calculated from point cloud data of the reference plane. The measurement processing unit 62 calculates a regression line 80 based on the position coordinates of the obtained point cloud data 70 of the reference plane RS. In FIG. 12, for convenience of explanation, the slope of the regression line 80 is exaggerated. The installation height of the laser measurement device 16 corresponds to the intercept of the regression line 80, and the pitch angle of the laser measurement device 16 corresponds to the slope of the regression line 80. The measurement processing unit 62 calculates calibration parameters for matching the obtained regression line 80 with the reference plane RS (a line on the reference plane in the XZ plane). This enables the measurement processing unit 62 to acquire point cloud data 70 in which deviations in the installation height and pitch angle of the laser measurement device 16 have been corrected.

[0060] FIG. 13 is a schematic diagram illustrating calculation of calibration parameters for the X-direction position and yaw angle. In the example of FIG. 13, the reference plane RS is the surface of a jig plate 84 having a known shape. The jig plate has a flat plate shape with known dimensions. In the example of FIG. 13, multiple (three) jig plates 84 are installed in the parking area 1, spaced apart at a predetermined interval L21 in the X direction and standing upright in the Z direction. The laser measurement device 16 performs laser light scanning when no vehicle is present in the parking area 1, and acquires point cloud data 70 of each reference plane RS. The position and attitude (tilt) of the reference plane RS are known. For convenience of explanation, in FIG. 13, the rearmost jig plate 84 is placed at the origin O, but this is not particularly limited.

[0061] FIG. 14 is a diagram illustrating point cloud data of the reference planes RS. The measurement processing unit 62 calculates calibration parameters for the X-direction position and yaw angle of the laser measurement device 16 based on the position coordinates of the point cloud data 70 of each reference plane RS. The X-direction position of the laser measurement device 16 corresponds to the X-coordinate of the point cloud data 70, and the yaw angle of the laser measurement device 16 corresponds to the X-direction spacing of the point cloud data 70. In other words, if the X-direction position of the laser measurement device 16 deviates from the design position, the three groups of point cloud data 70 corresponding to the three reference planes RS will be misaligned from the designed X-coordinates. If the yaw angle of the laser measurement device 16 is tilted (the scanning direction of the laser light is tilted from the X-axis direction), the spacing L22 between the measurement points 71 located on the three reference planes RS will increase in accordance with the tilt angle. The measurement processing unit 62 calculates a representative value of the measurement positions of the three reference planes RS from the three groups of point cloud data 70 corresponding to the three reference planes RS. The representative value is, for example, the average value of the position coordinates of the point cloud data 70 for each group. The measurement processing unit 62 calculates calibration parameters for matching the X coordinate and interval L22 of the obtained representative value with the known X coordinate and interval L21 of each reference plane RS. This enables the measurement processing unit 62 to acquire point cloud data 70 in which the deviations in the X direction position and yaw angle of the laser measurement device 16 have been corrected.

[0062] As described above, in this embodiment, the measurement processing unit 62 calculates calibration parameters related to the position and orientation of the laser measurement device 16 based on the point cloud data 70 of the reference plane RS acquired by the laser measurement device 16 when no freight vehicle V is present in the parking area 1 and the known position and orientation information of the reference plane RS. This makes it possible to easily calculate the calibration parameters. Since there is no need to accurately measure, for example, the installation height and mounting angle of the laser measurement device 16 in order to acquire the calibration parameters, the convenience of the measurement system 100 is improved.

[0063] (Third embodiment) Next, a third embodiment will be described. The third embodiment will describe an example in which laser measurement devices 16 are provided at multiple positions in the front-to-rear direction (X direction) of the parking area 1. In the third embodiment, descriptions of parts that are common to the first embodiment will be omitted.

[0064] Fig. 15 is a diagram for explaining measurement by the front measurement device according to the third embodiment, and Fig. 16 is a diagram for explaining measurement by the rear measurement device according to the third embodiment.

[0065] In the measurement system 100 according to the third embodiment, the laser measurement device 16 includes a front measurement device Mf arranged at a position on the front side of the parking area 1 and a rear measurement device Mr arranged at a position on the rear side of the parking area 1. Both the front measurement device Mf and the rear measurement device Mr are laser measurement devices such as two-dimensional (2D)-LiDAR. That is, in the third embodiment, two laser measurement devices 16 are provided along the longitudinal direction of the parking area 1. The front measurement device Mf and the rear measurement device Mr are arranged at an interval in the X direction.

[0066] 15, the front measuring device Mf is placed further forward (in the +X direction) in the parking area 1 than the rear measuring device Mr. The front measuring device Mf is placed in a position where it can measure a range including the front end position Pf of the loading platform V2 of the cargo vehicle V. For example, the front measuring device Mf is installed in a position where the front end position Pf of the vehicle type with the longest overall length among the cargo vehicles V to be measured is included in the measurement range 90A.

[0067] 16, the rear measurement device Mr is placed in a position where it can measure a range including the rear end position Pr of the loading platform V2 of the cargo vehicle V. In other words, the rear measurement device Mr is provided in a position where the rear end position Pr of the cargo vehicle V to be measured (in this embodiment, the position of the origin O of the parking area 1) is included within the measurement range 90B. The front end position Pf of the vehicle type with the shortest overall length among the cargo vehicles V to be measured may be included within either the measurement range 90A or the measurement range 90B.

[0068] The measurement processing unit 62 calculates the front end position Pf of the loading platform V2 based on the point cloud data 70 acquired by the front measurement device Mf. The measurement processing unit 62 calculates the rear end position Pr of the loading platform V2 based on the point cloud data 70 acquired by the rear measurement device Mr. The method of calculating the front end position Pf and the rear end position Pr is the same as in the first embodiment. That is, the measurement processing unit 62 calculates a regression line based on the point cloud included in a preset measurement area 78 from the point cloud data 70 acquired by the front measurement device Mf, and extracts the point cloud within a distance threshold Ht (see FIG. 8) from the regression line as the loading platform point cloud. The measurement processing unit 62 determines the position of the foot of a perpendicular line drawn from the measurement point 71 at the front end (the point with the largest X coordinate) of the loading platform point cloud to the regression line as the front end position Pf of the loading platform top surface V4. Similarly, the measurement processing unit 62 calculates a regression line based on the point cloud included in a preset measurement area 78 from the point cloud data 70 obtained by the rear measurement device Mr, and extracts the point cloud that is within a distance threshold Ht (see FIG. 8) from the regression line as the loading platform point cloud. The measurement processing unit 62 determines the position of the foot of a perpendicular line drawn from the measurement point 71 at the rear end (the point with the smallest X coordinate) of the loading platform point cloud to the regression line as the rear end position Pr of the loading platform top surface V4. The measurement area 78 can be set as a single area common to the front measurement device Mf and the rear measurement device Mr. The measurement area 78 may also be set separately for the front measurement device Mf and the rear measurement device Mr.

[0069] With this configuration, in the third embodiment, even if a single laser measurement device 16 cannot measure the front end position Pf and the rear end position Pr of the loading platform V2, it is possible to calculate the front end position Pf and the rear end position Pr from the point cloud data 70 acquired from each of the front measurement device Mf and the rear measurement device Mr. For example, even in cases where the length LB of the loading platform V2 of the cargo vehicle V is large or where the installation height of the laser measurement device 16 (the distance to the loading platform top surface V4) cannot be sufficiently secured so that the front end position Pf and the rear end position Pr cannot be accommodated within the measurement range, the front end position Pf and the rear end position Pr can be accurately calculated.

[0070] In addition, the front measurement device Mf and the rear measurement device Mr may be installed so that the measurement range 90A of the front measurement device Mf and the measurement range 90B of the rear measurement device Mr partially overlap, and the point cloud data 70 of the front measurement device Mf and the point cloud data 70 of the rear measurement device Mr may be combined.

[0071] (Fourth embodiment) Next, a fourth embodiment will be described. The fourth embodiment will describe an example in which laser measurement devices 16 are provided at multiple positions in the width direction (Y direction) of the parking area 1. In the fourth embodiment, descriptions of parts that are common to the first embodiment will be omitted.

[0072] FIG. 17 is a diagram showing a first measuring device and a second measuring device according to the fourth embodiment. The laser measuring device 16 includes a first measuring device 16A and a second measuring device 16B arranged at a predetermined interval L41 in the width direction of the parking area 1. The first measuring device 16A and the second measuring device 16B are both laser measuring devices such as two-dimensional (2D)-LiDAR. That is, in the fourth embodiment, the two laser measuring devices 16 are arranged at an interval in the width direction (Y direction) of the parking area 1. In the example of FIG. 17, the first measuring device 16A and the second measuring device 16B are arranged side by side in the Y direction at the same position in the X direction. The positions of the first measuring device 16A and the second measuring device 16B in the X direction may be different.

[0073] The first measurement device 16A and the second measurement device 16B each scan a laser beam along the longitudinal direction of the parking area 1 and receive reflected light of the laser beam to acquire point cloud data 70. A first measurement plane 100A, which is the plane scanned with the laser beam by the first measurement device 16A, and a second measurement plane 100B, which is the plane scanned with the laser beam by the second measurement device 16B, are separated by a predetermined distance L41. The predetermined distance L41 is known. The first measurement plane 100A and the second measurement plane 100B are either parallel or can be corrected to be parallel based on calibration parameters acquired using the method of the second embodiment or the like.

[0074] The measurement processing unit 62 calculates the stopping angle θ of the cargo vehicle V with respect to the parking area 1 based on the position information of the loading platform V2 calculated based on the point cloud data 70 acquired by each of the first measurement device 16A and the second measurement device 16B and the predetermined distance L41 between the first measurement device 16A and the second measurement device 16B. The stopping angle θ is the yaw angle (angle in the rotational direction around the Z axis) in the measurement coordinate system set in the parking area 1.

[0075] Fig. 18 is a diagram illustrating the stopping angle θ of a cargo vehicle V in the fourth embodiment. Fig. 18 shows the state of the cargo vehicle V stopped with its fore-and-aft direction tilted relative to the X direction of the parking area 1, as viewed from the +Z direction. The stopping angle θ is the angle formed between an axis (indicated by a dotted line) along the fore-and-aft direction of the cargo vehicle V (bed V2) and the X axis of the parking area 1. For convenience of explanation, Fig. 18 shows the stopping angle θ in an exaggerated manner.

[0076] The measurement processing unit 62 acquires point cloud data 70 within the first measurement plane 100A from the first measuring device 16A. The measurement processing unit 62 calculates the rear end position PrA of the loading platform V2 on the first measurement plane 100A based on the point cloud data 70 acquired from the first measuring device 16A.

[0077] The measurement processing unit 62 acquires point cloud data 70 within the second measurement plane 100B from the second measurement device 16B. The measurement processing unit 62 calculates the rear end position PrB of the loading platform V2 on the second measurement plane 100B based on the point cloud data 70 acquired from the second measurement device 16B. The rear end positions PrA and PrB are both points on the rear edge of the loading platform upper surface V4 (the rear surface of the loading platform V2).

[0078] The measurement processing unit 62 calculates the distance L42 in the X direction between the rear end position PrA and the rear end position PrB in the X direction. The measurement processing unit 62 calculates the stopping angle θ using the following formula (1) based on the distance L42 between the rear end positions and the distance L41 between the measurement surfaces.

number

[0079] As a result, the measurement processing unit 62 calculates the stopping angle θ of the cargo vehicle V in the parking area 1. The measurement processing unit 62, for example, compares the stopping angle θ with a preset threshold value, and performs processing to notify the driver that the tilt is excessive if the stopping angle θ is greater than the threshold value. Examples of the notification processing include sending information to a pre-specified destination such as an information terminal used by the driver of the cargo vehicle V, or outputting information from a device such as a display or speaker provided near the parking area 1. The measurement processing unit 62 also calculates the approach position of the mobile object 10 with respect to the loading platform V2 according to the calculated stopping angle θ. The measurement processing unit 62 also performs processing to correct the length information of the loading platform V2 based on the calculated stopping angle θ.

[0080] As described above, in this embodiment, the measurement processing unit 62 calculates the stopping angle θ of the cargo vehicle V with respect to the parking area 1 based on the position information of the cargo platform V2 (i.e., the rear end position PrA and the rear end position PrB) calculated based on the point cloud data 70 acquired by each of the first measuring device 16A and the second measuring device 16B, and the predetermined distance L41 between the first measuring device 16A and the second measuring device 16B. This makes it possible to easily measure the stopping angle of the cargo vehicle V (i.e., the yaw angle of the cargo platform V2) using the point cloud data 70 acquired by each of the first measuring device 16A and the second measuring device 16B.

[0081] Instead of calculating the rear end position PrA and the rear end position PrB, the front end position Pf on each measurement plane may be calculated. In this case, l in equation (1) may be set to the distance in the X direction between the front end position Pf on the first measurement plane 100A and the front end position Pf on the second measurement plane 100B.

[0082] (Fifth embodiment) Next, a fifth embodiment will be described. The fifth embodiment will describe an example of acquiring time-series changes in point cloud data 70 acquired by a laser measurement device 16. In the fifth embodiment, descriptions of parts that have the same configuration as the first embodiment will be omitted.

[0083] In the measurement system 100 according to the fifth embodiment, the measurement processing unit 62 detects at least one of the stopping of a cargo vehicle V in the parking area 1 and the opening and closing of the cargo vehicle V2's loading platform based on changes in the point cloud data 70 of the laser measurement device 16 acquired at multiple points in time.

[0084] (Vehicle stop detection) Fig. 19 is a diagram illustrating the vehicle stop detection process based on time-series changes in the point cloud data 70. Fig. 19 shows a state (A) where there is no freight vehicle V parked in the parking area 1, a state (B) where a freight vehicle V enters the parking area 1, a state (C) where the freight vehicle V that has entered the parking area 1 is stopped, and a state (D) where the freight vehicle V exits the parking area 1. When the freight vehicle V exits the parking area 1 in state (D), the state returns to state (A).

[0085] The measurement processing unit 62 periodically acquires the point cloud data 70 of the laser measurement device 16 at predetermined time intervals. This allows the measurement processing unit 62 to acquire the point cloud data 70 acquired at multiple points in time.

[0086] The measurement processing unit 62 determines whether the position of each measurement point included in the acquired point cloud data 70 is included in a presence / absence determination area 110 for determining the presence or absence of a cargo vehicle V. If a cargo vehicle V is present in the parking area 1, point cloud data 70 located on the loading platform upper surface V4 and the upper surface of the cabin V1 (air guide plate V3) is acquired. If a cargo vehicle V is not present in the parking area 1, point cloud data 70 located on the ground surface GR of the parking area 1 is acquired. Therefore, the presence / absence determination area 110 is set to a range that is above the ground surface GR of the parking area 1 and includes the height position of the loading platform upper surface V4 of the cargo vehicle V. The presence / absence determination area 110 may be the same range as the measurement area 78 shown in the first embodiment above.

[0087] For example, the measurement processing unit 62 determines that a cargo vehicle V is present in the parking area 1 when the number of measurement points included in the presence / absence determination area 110 of the acquired point cloud data 70 is greater than or equal to a threshold, and determines that a cargo vehicle V is not present in the parking area 1 when the number of measurement points included in the presence / absence determination area 110 is less than the threshold.

[0088] As a result, the measurement processing unit 62 determines that there is no freight vehicle V in the parking area 1 in state (A), and determines that there is a freight vehicle V in the parking area 1 in state (B).

[0089] When the measurement processing unit 62 determines that a cargo vehicle V is present in the parking area 1, it acquires the rear end position Pr of the loading platform V2 of the cargo vehicle V based on the point cloud data 70. The method of acquiring the rear end position Pr is the same as in the first embodiment.

[0090] The measurement processing unit 62 then determines whether the acquired rear end position Pr is included in a vehicle stop determination area 112 for determining a stopped state. The vehicle stop determination area 112 is an allowable range for a stopped position that takes into account variations in the rear end position Pr in the parking area 1. Under the condition that the rear end position Pr is included in the vehicle stop determination area 112, the measurement processing unit 62 determines that the cargo vehicle V is stopped if the rear end position Pr has been stopped for a certain period of time or more, and determines that the cargo vehicle V is not stopped if the stopped period of the rear end position Pr is less than the certain period of time. The rear end position Pr is stopped when the rear end position Pr acquired from the point cloud data 70 at each time point falls within a preset error range.

[0091] As a result, the measurement processing unit 62 determines that the cargo vehicle V is not stopped until it stops in the parking area 1 in state (B), and determines that the cargo vehicle V has stopped in state (C) when the movement of the cargo vehicle V has stopped.

[0092] After determining that the cargo vehicle V has stopped, the measurement processing unit 62 determines whether the rear end position Pr acquired from the point cloud data 70 at each time point has become outside the stopping determination area 112. If the rear end position Pr is observed outside the stopping determination area 112 after the cargo vehicle V has stopped inside the stopping determination area 112, the measurement processing unit 62 determines that the cargo vehicle V has exited the parking area 1.

[0093] As a result, in state (C), while the rear end position Pr remains within the stopping determination area 112, the measurement processing unit 62 determines that the cargo vehicle V is stopped in the parking area 1, and when the rear end position Pr begins to move outside the stopping determination area 112, the measurement processing unit 62 determines that the cargo vehicle V has exited the parking area 1. Thereafter, when the entire cargo vehicle V moves outside the parking area 1 and point cloud data 70 within the presence determination area 110 is no longer acquired, the measurement processing unit 62 determines that the cargo vehicle V is not present in the parking area 1 as shown in state (A).

[0094] (Loading platform V2 opening / closing detection) Fig. 20 is a diagram illustrating the process of detecting whether a vehicle is parked and whether the loading platform is open or closed based on time-series changes in the point cloud data 70. Fig. 20 shows a state (A) in which there is no freight vehicle V parked in the parking area 1, a state (B) in which a freight vehicle V enters the parking area 1, a state (C) in which a freight vehicle V that has entered the parking area 1 is stopped, a state (D) in which the loading platform V2 of the freight vehicle V is open, a state (E) in which the loading platform V2 of the freight vehicle V is closed, and a state (F) in which a freight vehicle V exits the parking area 1. The determination of states (A), (B), (C), and (F) by the measurement processing unit 62 is the same as in Fig. 19, and therefore description thereof will be omitted.

[0095] The measurement processing unit 62 detects the opening of the bed V2 based on changes in the height position of the point cloud data 70 at each time point. Here, as described above, a gull-wing truck is exemplified as the cargo vehicle V. In a gull-wing truck, when the bed V2 is opened, the side surface V5 of the bed V2 rotates about a longitudinal axis, and the side surface V5 moves to a position above the bed V2. Note that state (D) shows a state in which the side surface V5 is in the middle of moving. In a gull-wing truck, at least a portion of the point cloud data 70 is acquired at a height position of the bed top surface V4 when the bed V2 is closed, and when the bed V2 is opened, the point cloud data 70 is acquired at a height position of the side surface V5 that has moved above the bed top surface V4.

[0096] Therefore, the measurement processing unit 62 determines that the loading platform V2 has been opened when the height position of the observed point cloud data 70 has changed upward by a predetermined amount or more. The measurement processing unit 62 determines that the loading platform V2 has not been opened when the change in height position of the observed point cloud data 70 is less than a predetermined amount. Note that what is actually measured when the height position of the point cloud data 70 has changed upward by a predetermined amount or more is the height position of the side surface V5. The height position of the point cloud data 70 is the height position of the regression line 76B.

[0097] Furthermore, after determining that the loading platform V2 has been opened, if the height position of the observed point cloud data 70 has changed downward by a predetermined amount or more, the measurement processing unit 62 determines that the loading platform V2 has been closed. If the change in the height position of the observed point cloud data 70 is less than the predetermined amount, the measurement processing unit 62 determines that the loading platform V2 remains open.

[0098] As a result, when the height position of the point cloud data 70 changes upward by more than a predetermined amount in state (D), the measurement processing unit 62 determines that the loading platform V2 has been opened, and after determining that it has been opened, when the height position of the point cloud data 70 changes downward by more than a predetermined amount as shown in state (E), the measurement processing unit 62 determines that the loading platform V2 has been closed.

[0099] The measurement processing unit 62 issues a notification based on the determination result. For example, when the measurement processing unit 62 determines that the cargo vehicle V has stopped in the parking area 1, it notifies the information processing unit 60 of the determination result that the cargo vehicle V has stopped. The information processing unit 60 sets work instructions for each moving body 10 based on the notification. For example, when the moving body 10 starts loading / unloading work after the cargo vehicle V has stopped but before it is determined that the loading platform V2 has been opened, the measurement processing unit 62 issues a warning to the information processing unit 60. Based on the warning, the information processing unit 60 transmits a control signal, for example, a standby instruction, to each moving body 10. For example, after detecting the entry of the cargo vehicle V, the measurement processing unit 62 notifies the driver of the cargo vehicle V if the rear end position Pr does not stop within the stop determination area 112. Based on the notification, the driver moves the cargo vehicle V so that the cargo vehicle V stops at an appropriate position (within an allowable range). For example, if the measurement processing unit 62 detects that a cargo vehicle V has left the facility and then detects that the cargo vehicle V is not present in the parking area 1, it can output permission for the cargo vehicle V to pass through the facility W to the management device 12, or output permission for the mobile body 10 to pass through the parking area 1 to the information processing unit 60.

[0100] As described above, in this embodiment, the measurement processing unit 62 detects at least one of the stopping of the cargo vehicle V in the parking area 1 and the opening and closing of the loading platform V2 of the cargo vehicle V. This makes it possible to determine the presence or absence of the cargo vehicle V and the open / closed state of the loading platform V2 only from the point cloud data 70 of the laser measurement device 16, without providing a sensor such as an imaging device for determining the presence or absence of the cargo vehicle V or the open / closed state of the loading platform V2.

[0101] (Sixth embodiment) Next, a sixth embodiment will be described. The sixth embodiment will describe an example in which various auxiliary determinations are made based on point cloud data 70 acquired by a laser measurement device 16. In the sixth embodiment, descriptions of parts that have the same configuration as the first embodiment will be omitted.

[0102] In the measurement system 100 according to the sixth embodiment, the measurement processing unit 62 determines whether or not the loading platform has been detected based on the number of points in the loading platform point cloud 74. Also, in the measurement system 100 according to the sixth embodiment, the measurement processing unit 62 determines whether or not the loading platform is a cargo vehicle V to be measured based on the calculated distance between the front end position Pf and the rear end position Pr (load platform length LB).

[0103] Fig. 21 is a flowchart showing an example of the operation of the measurement system 100 according to the sixth embodiment. Note that steps S10, S11, S12, S13, S14, and S15 in Fig. 21 are the same as those in the first embodiment.

[0104] When the measurement processing unit 62 acquires the point cloud data 70 from the laser measurement device 16, it extracts the point clouds within the measurement area 78 (step S21). The measurement processing unit 62 determines whether the number of extracted point clouds (number of measurement points) is equal to or greater than a preset first threshold (step S22). If the number of extracted point clouds is less than the first threshold (step S22; NO), the measurement processing unit 62 determines that no cargo vehicle V is present in the parking area 1 and ends the measurement process (step S23).

[0105] If the number of extracted point clouds is greater than or equal to the first threshold (step S22; YES), the measurement processing unit 62 estimates the height and inclination of the platform top surface V4 by calculating the regression line 76A (step S11) and extracts the platform point cloud 74 (step S12).

[0106] The measurement processing unit 62 determines whether the number of points (number of measurement points) in the extracted platform point cloud 74 is equal to or greater than a preset second threshold (step S24). If the number of points in the platform point cloud 74 is less than the second threshold (step S24; NO), the measurement processing unit 62 determines that detection of the platform top surface V4 has failed (step S25) and returns the process to step S21. If the number of points in the platform point cloud 74 is equal to or greater than the second threshold (step S24; YES), the measurement processing unit 62 calculates the front end position Pf and the rear end position Pr of the platform top surface V4 based on the platform point cloud 74 (step S13).

[0107] The measurement processing unit 62 determines whether the distance between the front end position Pf and the rear end position Pr (i.e., the length LB of the bed V2) is equal to or greater than a preset third threshold (step S26). If the distance between the front end position Pf and the rear end position Pr is less than the third threshold (step S26; NO), the measurement processing unit 62 determines that a vehicle other than the cargo vehicle V to be measured has been detected, and outputs a warning to the management device 12, etc. (step S27). If the distance between the front end position Pf and the rear end position Pr is equal to or greater than the third threshold (step S26; YES), the measurement processing unit 62 determines the stopping position of the cargo vehicle V and length information of the bed V2 (step S14), and determines the type of cargo vehicle V based on the length information of the bed V2 (step S15).

[0108] As described above, in this embodiment, the measurement processing unit 62 determines whether or not the loading platform has been detected based on the number of points in the loading platform point cloud 74 (step S25). As a result, for example, when there is an excessive deviation in the stopping position or angle of the cargo vehicle V, it is possible to determine whether or not the loading platform has been detected based only on the point cloud data 70 of the laser measurement device 16. Also, in this embodiment, the measurement processing unit 62 determines whether or not the cargo vehicle V is a measurement target based on the calculated distance between the front end position Pf and the rear end position Pr (load platform length LB). As a result, it is possible to determine whether or not a general vehicle other than the cargo vehicle V loading and unloading luggage has stopped in the parking area 1, for example, without providing a monitoring device or the like in the parking area 1.

[0109] (Seventh embodiment) Next, a seventh embodiment will be described. In the seventh embodiment, a method for calculating a regression line 76A that is different from that of the first embodiment will be described. In the seventh embodiment, a description of parts that are common to the first embodiment will be omitted.

[0110] In the first embodiment described above, as shown in FIG. 7, a measurement area 78 was set in advance in the parking area 1 to cover a range including the rear of the cargo vehicle V, and a regression line 76A was calculated from the point cloud (point cloud 72 located on the rear side of the vehicle) included in the measurement area 78 from the point cloud data 70.

[0111] In contrast to this, in this seventh embodiment, the measurement processing unit 62 calculates a regression line 76A by using a preset number of points from the rear side of the longitudinal direction of the point cloud data 70 as the point cloud 72 located on the rear side.

[0112] FIG. 22 is a schematic diagram illustrating a method for calculating a regression line 76A according to the seventh embodiment. As shown in FIG. 22, in the seventh embodiment, the measurement processing unit 62 focuses on the X coordinate of each measurement point in the point cloud data 70 acquired from the laser measurement device 16 and counts the measurement points in order from the smallest X coordinate. The measurement processing unit 62 then extracts a point cloud consisting of the first to Nth measurement points, which is a predetermined number, as the point cloud 72 located on the rear side. In this manner, the measurement processing unit 62 extracts a predetermined number of point clouds from the rear side in the longitudinal direction (the -X direction side) as the point cloud 72 located on the rear side. The number of measurement points to be extracted is set to a number that is assumed not to include the measurement points of the cabin V1 and the air guide plate V3 of the cargo vehicle V. In other words, the measurement processing unit 62 extracts, from the point cloud data 70 acquired from the laser measurement device 16, point clouds that belong to a predetermined percentage of the lowest X coordinate magnitudes as the point cloud 72 located on the rear side. The point cloud with the highest magnitude of the X coordinate is a measurement point located in the cabin V1 or the air guide plate V3 of the cargo vehicle V, so by using a point cloud with a lower magnitude of the X coordinate, it is possible to extract a measurement point located on the upper surface V4 of the loading platform. Therefore, in the seventh embodiment, it is not necessary to set the measurement area 78 in advance.

[0113] The measurement processing unit 62 calculates a regression line 76A based on the extracted point group 72 located on the rear side. The method of calculating the regression line 76A is the same as in the first embodiment.

[0114] As described above, in this embodiment, a preset number of points from the rear side in the longitudinal direction (-X direction) of the point cloud data 70 are used to calculate the regression line 76A as the point cloud 72 located on the rear side. This makes it possible to easily calculate the regression line 76A of the point cloud 72 located on the rear side of the cargo vehicle V without having to set in advance a measurement area 78 for extracting the point cloud 72 located on the rear side of the cargo vehicle V.

[0115] (Eighth embodiment) Next, an eighth embodiment will be described. The eighth embodiment will describe a configuration example that combines the third embodiment and the fourth embodiment. In the eighth embodiment, a description of parts that are common to the first embodiment will be omitted.

[0116] 23 is a diagram showing a laser measurement device according to the eighth embodiment. In the measurement system 100 according to the eighth embodiment, the laser measurement device 16 includes a first measurement device 16A, a second measurement device 16B, and a third measurement device 16C.

[0117] Similar to the fourth embodiment, the first measuring device 16A and the second measuring device 16B are arranged at a predetermined interval L41 (see FIG. 17) in the width direction (Y direction) of the parking area 1. The first measuring device 16A and the second measuring device 16B are arranged side by side in the Y direction at the same position in the X direction. The third measuring device 16C is arranged in the +X direction relative to the first measuring device 16A and the second measuring device 16B. The third measuring device 16C is arranged at a position offset in the Y direction from the first measuring device 16A and the second measuring device 16B. For example, the third measuring device 16C is arranged between the first measuring device 16A and the second measuring device 16B in the Y direction.

[0118] The first measuring device 16A, the second measuring device 16B, and the third measuring device 16C are arranged at an interval in the longitudinal direction (X direction) of the parking area 1. The first measuring device 16A and the second measuring device 16B are arranged at a rear position in the parking area 1. The third measuring device 16C is arranged at a front position in the parking area 1. Therefore, the third measuring device 16C is the front measuring device Mf shown in the third embodiment above, and the first measuring device 16A and the second measuring device 16B are each the rear measuring device Mr.

[0119] Each measurement device is a laser measurement device such as a two-dimensional (2D) LiDAR.

[0120] As shown in Figure 18, the measurement processing unit 62 calculates the stopping angle θ of the cargo vehicle V relative to the parking area 1 based on the position information of the loading platform V2 calculated based on the point cloud data 70 acquired by each of the first measuring device 16A and the second measuring device 16B and the predetermined distance L41 between the first measuring device 16A and the second measuring device 16B.

[0121] As shown in Fig. 15, the measurement processing unit 62 calculates the front end position Pf of the loading platform V2 based on the point cloud data 70 acquired by the front measuring device Mf (i.e., the third measuring device 16C). As shown in Fig. 16, the measurement processing unit 62 calculates the rear end position Pr of the loading platform V2 based on the point cloud data 70 acquired by the rear measuring device Mr (i.e., the first measuring device 16A and the second measuring device 16B). When calculating the rear end position Pr, both the point cloud data 70 from the first measuring device 16A and the point cloud data 70 from the second measuring device 16B may be used, or either one of the point cloud data 70 may be used.

[0122] As described above, in this embodiment, the stopping angle θ (i.e., yaw angle) of the freight vehicle V with respect to the parking area 1 can be calculated based on the point cloud data 70 acquired by each of the first measuring device 16A and the second measuring device 16B. Then, the front measuring device Mf and the rear measuring device Mr can acquire the front end position Pf and the rear end position Pr even for a large freight vehicle V that cannot be measured by a single laser measuring device 16.

[0123] (effect) As described above, according to the first aspect of the present disclosure, there is provided a measurement system 100 including a laser measurement device 16 installed above a predetermined parking area 1 and a measurement processing unit 62 that calculates position information of a freight vehicle V parked in the parking area 1 based on the output of the laser measurement device 16, wherein the laser measurement device 16 scans a laser beam along the longitudinal direction of the parking area 1 and receives reflected light of the laser beam to obtain point cloud data 70 along the longitudinal direction, and the measurement processing unit 62 extracts a bed point cloud 74 located on a bed top surface V4 of the freight vehicle V from the point cloud data 70 and calculates a front end position Pf and a rear end position Pr of the top surface of the bed V2 based on the extracted bed point cloud 74. According to the present disclosure, data is collected by scanning a laser beam along the longitudinal direction by the laser measurement device 16, making it easier to measure a wider range than when capturing images using an imaging device. Since the position of the loading platform V2 is calculated from the point cloud data 70 generated by the laser measurement device 16, unlike when extracting feature points from an image, the position can be calculated even if the shape of the cargo vehicle V is unexpected, and measurements can be made that are less susceptible to the effects of sunlight reflection, etc. These features enable improved position measurement of the cargo vehicle V.

[0124] According to a second aspect of the present disclosure, in the measurement system 100 according to the first aspect, the measurement processing unit 62 acquires the stopping position of the cargo vehicle V in the longitudinal direction and length information of the loading platform V2 of the cargo vehicle V based on the calculated front end position Pf and rear end position Pr. According to the present disclosure, the stopping position of the cargo vehicle V and length information of the loading platform V2 can be acquired by a simple method of simply performing laser measurement along the longitudinal direction.

[0125] According to a third aspect of the present disclosure, in the measurement system 100 according to the second aspect, the measurement processing unit 62 determines the type of cargo vehicle V based on length information of the loading platform V2. According to the present disclosure, the length information of the loading platform V2 can be used to determine the type of cargo handling work, such as the number of pallets (number of packages) that can be arranged on the loading platform V2. This eliminates the need to provide a dedicated sensor for determining the type of cargo vehicle V, thereby improving the convenience of the measurement system 100.

[0126] According to a fourth aspect of the present disclosure, in the measurement system 100 according to any one of the first to third aspects, the measurement processing unit 62 calculates a regression line 76A based on a point cloud 72 located on the rear side of the cargo vehicle V, excluding a point cloud located on the front side of the point cloud data 70, and extracts a point cloud within a distance threshold from the regression line 76A from the point cloud data 70 as a cargo bed point cloud 74. According to the present disclosure, the cargo bed point cloud 74 can be accurately extracted without using, for example, image processing, excluding the cabin (driver's seat) of the cargo vehicle V and structures associated with the cabin. As a result, the front end position Pf and rear end position Pr of the cargo bed V2 can be accurately calculated.

[0127] According to a fifth aspect of the present disclosure, in the measurement system 100 related to the fourth aspect, the measurement processing unit 62 calculates a regression line 76A using a point cloud included in a measurement area 78 that is preset in a range including the rear of the cargo vehicle V in the parking area 1 as the point cloud 72 located on the rear side. According to the present disclosure, by setting the measurement area 78 to match the expected size of the cargo vehicle V so that the area around the cabin is excluded, it is possible to easily and reliably calculate the regression line 76A of the point cloud 72 located on the rear side of the cargo vehicle V.

[0128] According to a sixth aspect of the present disclosure, in the measurement system 100 according to the fourth aspect, the measurement processing unit 62 calculates a regression line 76A for the point cloud 72 located on the rear side of the cargo vehicle V by using a preset number of point clouds from the rear side in the longitudinal direction among the point cloud data 70. According to the present disclosure, by using a number of point clouds that are assumed to be located in the loading platform V2 portion (not reaching the cabin) when counted from the rear side among the point clouds along the longitudinal direction, it is possible to easily calculate the regression line 76A for the point cloud 72 located on the rear side of the cargo vehicle V.

[0129] According to a seventh aspect of the present disclosure, in the measurement system 100 according to any of the first to sixth aspects, the measurement processing unit 62 calculates calibration parameters related to the position and orientation of the laser measurement device 16 based on point cloud data 70 of the reference plane RS acquired by the laser measurement device 16 when no freight vehicle V is present in the parking area 1 and known position and orientation information of the reference plane RS. According to the present disclosure, the calibration parameters can be easily calculated by acquiring the measurement results (point cloud data 70) of the known reference plane RS by the laser measurement device 16. Since there is no need to accurately measure, for example, the installation height and mounting angle of the laser measurement device 16 in order to acquire the calibration parameters, the convenience of the measurement system 100 is improved.

[0130] According to an eighth aspect of the present disclosure, in the measurement system 100 according to any one of the first to seventh aspects, the laser measurement device 16 includes a front measurement device Mf disposed at a front position in the parking area 1 and a rear measurement device Mr disposed at a rear position in the parking area 1, and the measurement processing unit 62 calculates the front end position Pf of the loading platform V2 based on the point cloud data 70 acquired by the front measurement device Mf, and calculates the rear end position Pr of the loading platform V2 based on the point cloud data 70 acquired by the rear measurement device Mr. According to the present disclosure, the front end position Pf and the rear end position Pr of the loading platform V2 can be separately acquired by the front measurement device Mf and the rear measurement device Mr. Therefore, the front end position Pf and the rear end position Pr can be acquired even for a large cargo vehicle V that cannot be measured by a single laser measurement device 16.

[0131] According to a ninth aspect of the present disclosure, in the measurement system 100 according to any one of the first to eighth aspects, the laser measurement device 16 includes a first measurement device 16A and a second measurement device 16B arranged at a predetermined interval L41 in the width direction of the parking area 1, and the measurement processing unit 62 calculates the stopping angle of the cargo vehicle V with respect to the parking area 1 based on position information of the loading platform V2 calculated based on point cloud data 70 acquired by each of the first measurement device 16A and the second measurement device 16B and the predetermined interval L41 between the first measurement device 16A and the second measurement device 16B. According to the present disclosure, the stopping angle of the cargo vehicle V (i.e., the yaw angle of the loading platform V2) can be easily measured using the point cloud data 70 acquired by each of the first measurement device 16A and the second measurement device 16B.

[0132] According to a tenth aspect of the present disclosure, in the measurement system 100 according to any one of the first to ninth aspects, the measurement processing unit 62 detects at least one of the stopping of the cargo vehicle V in the parking area 1 and the opening or closing of the loading platform V2 of the cargo vehicle V based on changes in the point cloud data 70 of the laser measurement device 16 acquired at multiple points in time. According to the present disclosure, it is possible to determine the presence or absence of the cargo vehicle V and the open / closed state of the loading platform V2 only from the point cloud data 70 of the laser measurement device 16, without providing a sensor such as an imaging device for determining the presence or absence of the cargo vehicle V or the open / closed state of the loading platform V2.

[0133] According to an eleventh aspect of the present disclosure, in the measurement system 100 according to any one of the first to tenth aspects, the measurement processing unit 62 determines whether the loading platform has been detected based on the number of points in the loading platform point cloud 74. According to the present disclosure, for example, when the deviation in the stopping position or angle of the cargo vehicle V is excessive, the success or failure of the loading platform detection can be determined based on only the point cloud data 70 of the laser measurement device 16.

[0134] According to a twelfth aspect of the present disclosure, in the measurement system 100 according to any one of the first to eleventh aspects, the measurement processing unit 62 determines whether the vehicle is a cargo vehicle V to be measured based on the calculated distance between the front end position Pf and the rear end position Pr. According to the present disclosure, it is possible to determine whether a general vehicle other than a cargo vehicle V loading and unloading luggage has stopped in the parking area 1, for example, without providing a monitoring device or the like in the parking area 1.

[0135] According to a thirteenth aspect of the present disclosure, a measurement method is provided, including the steps of: a laser measurement device 16 installed above a predetermined parking area 1 scans a laser beam along the longitudinal direction of the parking area 1 and receives reflected light of the laser beam to acquire point cloud data 70 along the longitudinal direction; extracting a platform point cloud 74 located on the platform top surface V4 of a cargo vehicle V parked in the parking area 1 from the point cloud data 70; and calculating a front end position Pf and a rear end position Pr of the top surface of the platform V2 based on the extracted platform point cloud 74. According to the present disclosure, data is collected by scanning a laser beam along the longitudinal direction using the laser measurement device 16, making it easier to measure a wider range than when capturing images using an imaging device. Because the position of the platform V2 is calculated from the point cloud data 70 obtained by the laser measurement device 16, position calculation can be performed even when the cargo vehicle V has an unexpected shape, unlike when feature points are extracted from an image, and measurement is less affected by sunlight reflection, etc. These steps can improve position measurement of the cargo vehicle V.

[0136] According to a fourteenth aspect of the present disclosure, a measurement program is provided that causes a computer to execute the following steps: acquiring point cloud data 70 along the longitudinal direction of the parking area 1, generated by a laser measurement device 16 installed above a predetermined parking area 1 scanning a laser beam along the longitudinal direction of the parking area 1 and receiving reflected light of the laser beam; extracting a platform point cloud 74 located on the platform top surface V4 of a cargo vehicle V parked in the parking area 1 from the point cloud data 70; and calculating a front end position Pf and a rear end position Pr of the top surface of the platform V2 based on the extracted platform point cloud 74. According to the present disclosure, data is collected by scanning a laser beam along the longitudinal direction using the laser measurement device 16, making it easier to measure a wider range than when capturing images using an imaging device. Because the position of the platform V2 is calculated from the point cloud data 70 obtained by the laser measurement device 16, position calculation can be performed even when the cargo vehicle V has an unexpected shape, unlike when feature points are extracted from an image, and measurement is less affected by sunlight reflection and the like. These steps can improve position measurement of the cargo vehicle V.

[0137] Although the embodiments of the present disclosure have been described above, the embodiments are not limited to the contents of these embodiments. Furthermore, the above-described components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the so-called equivalent range. Furthermore, the above-described components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the spirit of the above-described embodiments. [Explanation of symbols]

[0138] 1 Parking area 16 Laser measurement equipment 16A First Measuring Device 16B Second Measurement Device 16C Third Measurement Device 62 Measurement processing section 70 point cloud data 72 point clouds (point clouds located at the rear of the freight vehicle) 74 Loading platform point cloud 76A, 76B Regression lines 78 Measurement Area 80 Regression Line 100 Measurement System Ht distance threshold LB Length (length information) L41 Predetermined interval Mf Front Measuring Device Mr. Rear Measuring Device Pf front end position Pr, PrA, PrB rear end position RS reference plane V freight vehicle V2 Cargo Bed V4 Top of the loading platform θ Parking angle

Claims

1. A laser measurement device installed above a predetermined parking area; a measurement processing unit that calculates position information of a freight vehicle parked in the parking area based on an output of the laser measurement device, the laser measurement device scans a laser beam along a longitudinal direction of the parking area and receives reflected light of the laser beam to acquire point cloud data along the longitudinal direction; the measurement processing unit extracts a platform point cloud located on an upper surface of a platform of the cargo vehicle from the point cloud data, and calculates a front end position and a rear end position of the upper surface of the platform based on the extracted platform point cloud. Measurement system.

2. the measurement processing unit acquires a stopping position of the cargo vehicle in the longitudinal direction and length information of the cargo vehicle bed based on the calculated front end position and rear end position. The measurement system of claim 1 .

3. The measurement processing unit determines the type of the cargo vehicle based on the length information of the loading platform. The measurement system of claim 2 .

4. The measurement processing unit calculating a regression line based on a point cloud located on a rear side of the freight vehicle, excluding a point cloud located on a front side of the freight vehicle from the point cloud data; extracting, from the point cloud data, a point cloud that is within a distance threshold from the regression line as the loading platform point cloud; The measurement system of claim 1 .

5. the measurement processing unit calculates the regression line by using a point cloud included in a measurement area that is set in advance in the parking area to include a rear portion of the cargo vehicle as a point cloud located on the rear side. The measurement system according to claim 4 .

6. the measurement processing unit calculates the regression line by using a predetermined number of points from the rear side in the longitudinal direction of the point cloud data as a point cloud located on the rear side. The measurement system according to claim 4 .

7. the measurement processing unit calculates calibration parameters related to the position and orientation of the laser measurement device based on the point cloud data of the reference plane acquired by the laser measurement device when the cargo vehicle is not present in the parking area and known position and orientation information of the reference plane. The measurement system of claim 1 .

8. the laser measurement device includes a front measurement device disposed at a front position in the parking area and a rear measurement device disposed at a rear position in the parking area, the measurement processing unit calculates the front end position of the loading platform based on the point cloud data acquired by the front measurement device, and calculates the rear end position of the loading platform based on the point cloud data acquired by the rear measurement device; The measurement system of claim 1 .

9. the laser measurement device includes a first measurement device and a second measurement device arranged at a predetermined interval in a width direction of the parking area, the measurement processing unit calculates a stopping angle of the cargo vehicle with respect to the parking area based on position information of the loading platform calculated based on the point cloud data acquired by each of the first measurement device and the second measurement device, and based on the predetermined interval between the first measurement device and the second measurement device. The measurement system according to claim 1 or 8.

10. the measurement processing unit detects at least one of stopping of the cargo vehicle in the parking area and opening or closing of a loading platform of the cargo vehicle based on changes in the point cloud data of the laser measurement device acquired at multiple points in time. The measurement system of claim 1 .

11. the measurement processing unit determines whether the loading platform has been detected successfully based on the number of points in the loading platform point cloud. The measurement system of claim 1 .

12. the measurement processing unit determines whether the vehicle is a cargo vehicle to be measured based on the calculated distance between the front end position and the rear end position. The measurement system of claim 1 .

13. A laser measurement device installed above a predetermined parking area scans a laser beam along the longitudinal direction of the parking area and receives reflected light of the laser beam, thereby acquiring point cloud data along the longitudinal direction; extracting, from the point cloud data, a loading platform point cloud located on an upper surface of a loading platform of a freight vehicle parked in the parking area; and calculating a front end position and a rear end position of the top surface of the loading platform based on the extracted loading platform point cloud. Measurement method.

14. A laser measurement device installed above a predetermined parking area scans a laser beam along the longitudinal direction of the parking area and receives reflected light of the laser beam, thereby acquiring point cloud data along the longitudinal direction; extracting, from the point cloud data, a loading platform point cloud located on an upper surface of a loading platform of a freight vehicle parked in the parking area; calculating a front end position and a rear end position of the top surface of the loading platform based on the extracted loading platform point cloud; Measurement program.

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