Container space determining method, device and equipment for container yard and storage medium

Abstract

The invention discloses a container space determining method, device and equipment for a container yard and a storage medium. The method comprises the following steps: constructing a three-dimensional model of a target storage yard; obtaining a plurality of container images of the target area; splicing each image to obtain a panoramic image of the target area; detecting recognizable containers in the panoramic image, and judging whether unrecognizable containers exist in the target area or not; if not, executing the first scheme; if yes, the first scheme is executed for the recognizable containers, and the second scheme is executed for the unrecognizable containers; according to the first scheme, on the basis of the mapping relation between a three-dimensional model and a panoramic image, the container position of an identifiable container is determined; according to the second scheme, the positions of the unidentifiable containers are determined based on the in-out information of the containers in the target area, the cargo types of the containers, the receiving and delivering places, the recognizable container information and the stacking position information of which the images cannot be collected. According to the invention, the container position of each container in the storage yard can be rapidly determined, and the accuracy is high.

Description

Technical Field

[0001] The present invention relates to the field of electromagnetic characteristic calculation technology, and in particular to a method, device, equipment and storage medium for determining a container position in a container yard. Background Art

[0002] At present, with the rapid development of logistics business, the number of containers in the container yard and the frequency of entry and exit have increased dramatically. In order to ensure the orderly storage of containers, it is necessary to timely inventory the containers in the yard and update the yard data. Any change in the location of any container requires staff to record it in time. However, manual recording is not only inefficient, but also prone to errors in the location recording. It happens that the correct container cannot be found according to the location in the yard or the location of the newly entered container is occupied, which seriously affects the normal operation of the yard.

[0003] Therefore, there is an urgent need for a method, device, equipment and storage medium for determining the container position in a container yard. Summary of the invention

[0004] The present invention provides a method, device, equipment and storage medium for determining the location of containers in a container yard, which can quickly determine the location of each container in the yard with high accuracy. The technical solution is as follows:

[0005] In one aspect, a method for determining a container location in a container yard is provided, the method comprising:

[0006] Constructing a three-dimensional model of a target storage yard; the three-dimensional model includes a plurality of container areas, each of the container areas includes a plurality of stacking locations, and each of the stacking locations is used to store containers;

[0007] Acquire multiple container images of a target area, where the target area is at least a portion of the target yard;

[0008] Stitching each of the container images to obtain a panoramic image of the target area;

[0009] Detecting recognizable containers in the panoramic image based on a pre-trained detection model, and determining whether there are unrecognizable containers in the target area; if not, executing the first solution; if yes, executing the first solution for recognizable containers, and executing the second solution for unrecognizable containers;

[0010] The first solution is: determining the location of each identifiable container based on the mapping relationship between the three-dimensional model and the panoramic image;

[0011] The second solution is to determine the location of each unrecognizable container based on the entry and exit information of the containers in the target area, the container cargo type and the shipping and receiving locations, the identifiable container information and the stacking location information of which the image cannot be collected.

[0012] On the other hand, a device for determining a container position in a container yard is provided, the device comprising:

[0013] A construction unit is used to construct a three-dimensional model of a target storage yard; the three-dimensional model includes a plurality of container areas, each of the container areas includes a plurality of stacking locations, and each of the stacking locations is used to store containers;

[0014] An acquisition unit, used for acquiring a plurality of container images of a target area, wherein the target area is at least a part of the target yard;

[0015] A stitching unit, used for stitching each of the container images to obtain a panoramic image of the target area;

[0016] a judgment unit, configured to detect recognizable containers in the panoramic image based on a pre-trained detection model, and to judge whether there are unrecognizable containers in the target area;

[0017] a first determining unit, configured to execute a first solution for the identifiable containers in the target area, wherein the first solution is to determine the location of each identifiable container in the target area based on a mapping relationship between the three-dimensional model and the panoramic image;

[0018] The second determination unit is used to execute a second solution for the unrecognizable containers in the target area, wherein the second solution is: based on the entry and exit information of the containers in the target area, the type of container cargo and the shipping and receiving locations, the recognizable container information and the stacking information of the unrecognizable containers in the target area, determine the container location of each unrecognizable container in the target area.

[0019] On the other hand, a computer device is provided, which includes a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of the above-mentioned method for determining a container yard location.

[0020] On the other hand, a computer-readable storage medium is provided, wherein a computer program is stored in the storage medium, and when the computer program is executed by a processor, the steps of the method for determining a container location in a container yard are implemented.

[0021] On the other hand, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the method for determining a container location in a container yard described above are implemented.

[0022] The embodiment of the present invention provides a method for determining the location of a container yard. First, a three-dimensional model of a target yard is constructed. Then, when it is necessary to take inventory of a target area in the target yard, a panoramic image of the target area can be spliced ​​by capturing images of the target area, and the containers in the panoramic image can be identified. For recognizable containers, the location of each container is determined based on the mapping relationship between the three-dimensional model and the panoramic image; for unrecognizable containers, the location of each container is determined based on the entry and exit information of the container in the target area, the type of container cargo and the shipping and receiving locations, the recognizable container information and the stacking information of which the image cannot be captured. In this way, the location of each container can be determined through three-dimensional modeling, image recognition, and information such as the entry and exit of the container and the type of cargo. The present application does not require manual operation and can quickly determine the location of each container in the yard with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 This is a flow chart of a method for determining a container yard space provided by an embodiment of the present invention;

[0025] Figure 2 This is a structural diagram of a container yard location determination device provided by one embodiment of the present invention;

[0026] Figure 3 It is a hardware architecture diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0028] The specific implementation of the above concept is described below.

[0029] Please refer to Figure 1 , an embodiment of the present invention provides a method for determining a container location in a container yard, the method comprising:

[0030] Step 100, constructing a three-dimensional model of the target container yard; the three-dimensional model includes multiple container areas, each container area includes multiple stacking locations, and each stacking location is used to store containers;

[0031] Step 102, acquiring multiple container images of a target area, where the target area is at least a portion of a target yard;

[0032] Step 104, stitching each container image to obtain a panoramic image of the target area;

[0033] Step 106, detecting recognizable containers in the panoramic image based on the pre-trained detection model, and determining whether there are unrecognizable containers in the target area;

[0034] Step 108, executing a first solution for the identifiable containers in the target area, the first solution being: determining the location of each identifiable container based on a mapping relationship between the three-dimensional model and the panoramic image;

[0035] Step 110, executing the second solution for the identifiable containers in the target area, the second solution is: based on the entry and exit information of the containers in the target area, the container cargo type and the shipping and receiving locations, the identifiable container information and the stacking information of the uncaptured images, determine the location of each unidentifiable container.

[0036] In an embodiment of the present invention, a three-dimensional model of a target yard is first constructed, and then when it is necessary to inventory a target area in the target yard, a panoramic image of the target area can be spliced ​​by capturing images of the target area, and the containers in the panoramic image can be identified. For recognizable containers, the location of each container is determined based on the mapping relationship between the three-dimensional model and the panoramic image; for unrecognizable containers, the location of each container is determined based on the entry and exit information of the container in the target area, the type of container cargo and the shipping and receiving locations, the recognizable container information and the stacking information of the uncaptured image. In this way, the location of each container can be determined through three-dimensional modeling, image recognition, and information such as the entry and exit of the container, the type of cargo, etc. The present application does not require manual operation, and can quickly determine the location of each container in the yard with high accuracy.

[0037] Described below Figure 1 How the various steps are performed.

[0038] First, for step 100, a three-dimensional model of the target storage yard is constructed, including:

[0039] Collect geographic coordinate information of each container area in the target yard;

[0040] Based on the geographic coordinate information of each container area, a three-dimensional engine is used to perform three-dimensional modeling of the target yard to obtain a three-dimensional model of the target yard, and the correspondence between the three-dimensional model and the actual geographic coordinates is determined based on the three-dimensional map.

[0041] In this step, the geographic coordinate information of each box area is determined based on a high-precision positioning device, mainly including the length, width, height of each box area and the longitude and latitude of each corner point. By determining the correspondence between the three-dimensional model and the actual geographic coordinates, a basis can be provided for subsequent box location identification.

[0042] With respect to step 102, a plurality of container images of a target area are acquired, and the target area is at least a portion of the target yard.

[0043] In this step, the target area may be one container area or multiple container areas in the target yard, or the entire target yard, and its specific range is determined according to user needs.

[0044] In some embodiments, each container image is captured by an image acquisition device, and the image acquisition device is mounted on a mobile platform; the mobile platform moves along a pre-planned path, and a plurality of acquisition points are arranged on the pre-planned path, and the image acquisition device captures the corresponding container image at each acquisition point according to a preset angle.

[0045] In this step, the mobile platform can be a drone, a vehicle, or an automated guided vehicle (AGV), etc., so as to adapt to yards of different sizes and layouts. By using a mobile platform, when the image acquisition device acquires images at each acquisition point at a set angle, it can cover the entire area of ​​the target yard and ensure that each container is identified. In addition, when shooting, ensure that there is a 30%-50% overlap between adjacent images, and record the location information of the sample corresponding to each image when taking the photo.

[0046] In addition, the mobile platform is also equipped with a fill light device and a processor. The fill light device can ensure that high-quality container images can be obtained under various environmental conditions (such as different weather and light conditions). The device processor can integrate edge computing capabilities on the mobile platform to perform pre-processing operations such as image denoising and color correction, and then use a deep learning algorithm to identify the container number, and send the identified container number and coordinate information in the image to the client computer, reducing the amount of data transmission and improving the system response speed.

[0047] In some embodiments, the pre-planned path is determined based on the layout of the target yard, the width of the passage, the location of obstacles, the busyness of the target area, and the container turnover rate. For example, for areas with high container turnover rates, the mobile platform needs to travel back and forth frequently, and vice versa, the frequency of the mobile platform's passage is reduced. Similarly, the frequency of image acquisition at each acquisition point by the image acquisition device is determined based on the turnover rate of the container corresponding to the acquisition point. If the turnover rate of the container corresponding to the acquisition point is high, the number of acquisitions needs to be increased, and vice versa, the number of acquisitions needs to be reduced.

[0048] With respect to step 104, each container image is stitched together to obtain a panoramic image of the target area.

[0049] In this step, the scale-invariant feature transform matching algorithm (SIFT) is used to extract feature points in the image, the fast nearest neighbor search package (FLANN) is applied for feature matching, and the estimated homography matrix (RANSAC) is used to apply multi-band fusion technology to generate a seamless panoramic image of the target area.

[0050] With respect to step 106 , the recognizable containers in the panoramic image are detected based on the pre-trained detection model, and it is determined whether there are unrecognizable containers in the target area.

[0051] In this step, the pre-trained detection model can be a model such as YOLOv5. Image recognition models are widely used in various fields, and the model structure and training process will not be described here.

[0052] In some embodiments, determining whether there is an unrecognizable container in the target area is based on a first formula:

[0053] The first formula is: Y = A + CDB

[0054] If Y = 0, it is determined that there are no unrecognizable containers in the target area;

[0055] If Y ≥ 1, it is determined that there are unrecognizable containers in the target area;

[0056] Where Y is the number of unrecognizable containers in the target area; A is the number of containers in the target area before the current image acquisition; C and D are the number of containers entering and leaving the target area between the current image acquisition and the previous image acquisition, respectively; B is the number of recognizable containers in the panoramic image corresponding to the current image acquisition; Y, A, B, C, and D are all natural numbers.

[0057] With respect to step 108, based on the mapping relationship between the three-dimensional model and the panoramic image, determining the location of each identifiable container includes:

[0058] Based on the position and angle of the acquisition point where the image acquisition device is located when acquiring the panoramic image, a conversion relationship between the coordinate system of the panoramic image and the geographic coordinate system is established to generate a GeoTIFF file with geographic information;

[0059] Based on the panoramic image and the GeoTIFF file, the panoramic image is reconstructed into a three-dimensional grid and texture mapped based on a preset algorithm to obtain the coordinates of each identifiable container in the panoramic image;

[0060] Calculate the actual geographic coordinates of each identifiable container in the panoramic image based on the coordinates of each identifiable container in the panoramic image and the correspondence between the three-dimensional model and the actual geographic coordinates;

[0061] The actual geographic coordinates of each identifiable container in the panoramic image are compared with the container location layout database of the target yard to obtain the location of each identifiable container.

[0062] In this embodiment, the SfM algorithm is used to estimate the position and posture of the image acquisition device, the MVS algorithm is applied to generate a dense point cloud, and the panoramic image is meshed and texture mapped.

[0063] For step 110, based on the entry and exit information of containers in the target area, the type of container cargo and the shipping and receiving locations, the identifiable container information and the stacking location information of which the image cannot be collected, the location of each unidentifiable container is determined, including:

[0064] Based on the box location layout database of the target area and the box location determination result of the target area before the current image acquisition, determine the stacking location set where the image cannot be acquired;

[0065] Calculating the number of unrecognizable containers in the target area based on the first formula;

[0066] Based on the container number of each container in the target area before the current image acquisition, the container numbers of the containers entering and leaving the target area between the current image acquisition and the previous image acquisition, and the container numbers of the recognizable containers in the panoramic image corresponding to the current image acquisition, the container number set corresponding to the unrecognizable containers in the target area is determined; the container number of each container in the target area is unique, and the cargo type, entry and exit time, and shipping and receiving address of the corresponding container are found through the container number;

[0067] Based on the loading and unloading rules of the target area, the type of goods corresponding to each container number, the entry and exit time and the shipping and receiving address, a stacking location is determined for each container number from the stacking location set where images cannot be collected, and the container location corresponding to the container number is obtained.

[0068] In this step, once the target yard is determined, the layout of the container slots in each area of ​​the yard has been determined, that is, the database of the container slot layout of the target yard is known, so which container slots are visible and which are invisible is also known. In addition, since the database is determined based on factors such as the container acquisition type, entry and exit time, and shipping and receiving addresses, once the container number of the unrecognizable container is determined, the relevant information of the container can be searched based on the container number to match it with the container slot with the highest credibility.

[0069] In addition, in some embodiments, after determining the container locations of each container in the target area, the method further includes: allocating container locations for the next new container to enter the site based on the determination result, and the allocation method is:

[0070] Construct the overall objective function of container allocation, which aims to minimize the vehicle's passage cost and the number of container transfers in the target yard;

[0071] Determine the following constraints: each slot can only store one container, a container can only occupy one slot, the initial position of the yard crane is at the first bay, the total number of allocated containers is less than the total capacity of the corresponding area, each container cannot be placed in the air, the containers are placed in the order of first down and then up, and the number of containers stored in each container area is between the maximum capacity and the minimum capacity;

[0072] Under the constraints, the preset algorithm is used to solve the objective function and obtain the allocation result of the new containers entering the yard.

[0073] In some embodiments, the expression of the overall objective function is:

[0074] Q=min(r 1 ×E+r 2 ×F)

[0075] In the formula, Q is the overall objective function, r 1 is the cost of the vehicle traveling one kilometer; r 2 is the cost of unloading boxes; E is the objective function with the minimum number of unloading boxes; F is the objective function with the minimum vehicle travel cost.

[0076] In some embodiments, the objective function for minimizing the number of box flips is:

[0077]

[0078] Where i represents the i-th bay; j represents the j-th row; n represents the n-th container; k represents the k-th layer; I, J, N, K are the number of bays, the number of rows, the total number of containers entering the yard, and the number of layers in the yard, respectively; L nijk It indicates whether there is a container reverse for the exit container m at the lower position (i,j,kz) when the exit container n is placed at the position (i,j,k). When the container at the position (i,j,k) leaves the yard later than the container at the position (i,j,kz), a container reverse is recorded. The exit probability of a container is related to its attribute value. The attribute value of a container is related to its delivery address, exit time level, weight level and entry sequence. The larger the attribute value of a container, the heavier its weight and the earlier it leaves the yard.

[0079] In some embodiments, the objective function for minimizing the vehicle travel cost is:

[0080]

[0081] Where P nijk Indicates whether the box position (i, j, k) is stacked with the exit box n; P (n-1)ijk Indicates whether the container location (i, j, k) is stacked with exit container n-1.

[0082] It should be noted that the preset algorithm is an ant colony algorithm or a genetic algorithm. Under the above constraints, using the ant colony algorithm or the genetic algorithm to solve the overall objective function is a commonly used technology and will not be repeated in this application.

[0083] like Figure 2 , Figure 3 As shown, an embodiment of the present invention provides a device for determining the location of a container yard. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, Figure 2 As shown, it is a hardware architecture diagram of a computing device where a container yard container position determination device provided by an embodiment of the present invention is located. Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown in the figure, the computing device in which the device is located in the embodiment may also generally include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 3 As shown, as a device in a logical sense, the CPU of the computing device in which it is located reads the corresponding computer program in the non-volatile memory into the internal memory and runs it.

[0084] Please refer to Figure 3 The embodiment of the present invention provides a device for determining a container position in a container yard, the device comprising:

[0085] The construction unit 300 is used to construct a three-dimensional model of the target storage yard; the three-dimensional model includes a plurality of container areas, each of which includes a plurality of stacking locations, and each stacking location is used to store containers;

[0086] An acquisition unit 302 is used to acquire multiple container images of a target area, where the target area is at least a part of a target yard;

[0087] A stitching unit 304 is used to stitch each container image to obtain a panoramic image of the target area;

[0088] A determination unit 306, configured to detect recognizable containers in the panoramic image based on a pre-trained detection model, and to determine whether there are unrecognizable containers in the target area;

[0089] A first determining unit 308 is configured to execute a first solution for the identifiable containers in the target area, wherein the first solution is to determine the location of each identifiable container in the target area based on a mapping relationship between the three-dimensional model and the panoramic image;

[0090] The second determination unit 310 is used to execute a second solution for the unrecognizable containers in the target area. The second solution is: based on the entry and exit information of the containers in the target area, the container cargo type and the shipping and receiving locations, the recognizable container information and the stacking information of the unrecognizable containers in the target area, determine the container location of each unrecognizable container in the target area.

[0091] In some embodiments, the construction unit 300 is used to perform the following operations:

[0092] Collect geographic coordinate information of each container area in the target yard;

[0093] Based on the geographic coordinate information of each container area, a three-dimensional engine is used to perform three-dimensional modeling of the target yard to obtain a three-dimensional model of the target yard, and the correspondence between the three-dimensional model and the actual geographic coordinates is determined based on the three-dimensional map.

[0094] In some embodiments, each container image is captured by an image acquisition device, and the image acquisition device is mounted on a mobile platform; the mobile platform moves along a pre-planned path, and a plurality of acquisition points are arranged on the pre-planned path, and the image acquisition device captures the corresponding container image at each acquisition point according to a preset angle.

[0095] In some embodiments, determining whether there is an unrecognizable container in the target area is based on a first formula:

[0096] The first formula is: Y = A + CDB

[0097] If Y = 0, it is determined that there are no unrecognizable containers in the target area;

[0098] If Y ≥ 1, it is determined that there are unrecognizable containers in the target area;

[0099] Where Y is the number of unrecognizable containers in the target area; A is the number of containers in the target area before the current image acquisition; C and D are the number of containers entering and leaving the target area between the current image acquisition and the previous image acquisition, respectively; B is the number of recognizable containers in the panoramic image corresponding to the current image acquisition; Y, A, B, C, and D are all natural numbers.

[0100] In some implementations, the first determining unit 308 is configured to perform the following operations:

[0101] Based on the position and angle of the acquisition point where the image acquisition device is located when acquiring the panoramic image, a conversion relationship between the coordinate system of the panoramic image and the geographic coordinate system is established to generate a GeoTIFF file with geographic information;

[0102] Based on the panoramic image and the GeoTIFF file, the panoramic image is reconstructed into a three-dimensional grid and texture mapped based on a preset algorithm to obtain the coordinates of each identifiable container in the panoramic image;

[0103] Calculate the actual geographic coordinates of each identifiable container in the panoramic image based on the coordinates of each identifiable container in the panoramic image and the correspondence between the three-dimensional model and the actual geographic coordinates;

[0104] The actual geographic coordinates of each identifiable container in the panoramic image are compared with the container location layout database of the target yard to obtain the location of each identifiable container.

[0105] In some implementations, the second determining unit 310 is configured to perform the following operations:

[0106] Based on the box location layout database of the target area and the box location determination result of the target area before the current image acquisition, determine the stacking location set where the image cannot be acquired;

[0107] Calculating the number of unrecognizable containers in the target area based on the first formula;

[0108] Based on the container number of each container in the target area before the current image acquisition, the container numbers of the containers entering and leaving the target area between the current image acquisition and the previous image acquisition, and the container numbers of the recognizable containers in the panoramic image corresponding to the current image acquisition, the container number set corresponding to the unrecognizable containers in the target area is determined; the container number of each container in the target area is unique, and the cargo type, entry and exit time, and shipping and receiving address of the corresponding container are found through the container number;

[0109] Based on the loading and unloading rules of the target area, the type of goods corresponding to each container number, the entry and exit time and the shipping and receiving address, a stacking location is determined for each container number from the stacking location set where images cannot be collected, and the container location corresponding to the container number is obtained.

[0110] In some embodiments, after determining the container locations of each container in the target area, the method further includes: allocating container locations for the next new container to enter the container yard based on the determination result, and the allocation method is:

[0111] Construct the overall objective function of container allocation, which aims to minimize the vehicle's passage cost and the number of container transfers in the target yard;

[0112] Determine the following constraints: each slot can only store one container, a container can only occupy one slot, the initial position of the yard crane is at the first bay, the total number of allocated containers is less than the total capacity of the corresponding area, each container cannot be placed in the air, the containers are placed in the order of first down and then up, and the number of containers stored in each container area is between the maximum capacity and the minimum capacity;

[0113] Under the constraints, the preset algorithm is used to solve the objective function and obtain the allocation result of the new containers entering the yard.

[0114] It should be noted that the container yard location determination device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the container yard location determination device provided in the above embodiment and the container yard location determination method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0115] The embodiment of the present application also provides a computer device, please refer to Figure 3 The computer device includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, at least one program, a code set or an instruction set is loaded and executed by the processor to implement the container yard location determination method provided by the above-mentioned method embodiments.

[0116] An embodiment of the present application also provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement the container yard location determination method provided by the above-mentioned method embodiments.

[0117] An embodiment of the present application also provides a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the method for determining a container yard location as described in any of the above embodiments.

[0118] For the convenience of description, the above system or device is described by dividing it into various modules or units according to its functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0119] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0120] Finally, it should be noted that, in this article, relational terms such as first, second, third and fourth are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0121] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining container space in a container yard, characterized in that: The method comprises: Constructing a three-dimensional model of a target storage yard; the three-dimensional model includes a plurality of container areas, each of the container areas includes a plurality of stacking locations, and each of the stacking locations is used to store containers; Acquire multiple container images of a target area, where the target area is at least a portion of the target yard; Stitching each of the container images to obtain a panoramic image of the target area; Detecting recognizable containers in the panoramic image based on a pre-trained detection model, and determining whether there are unrecognizable containers in the target area; if not, executing the first solution; if yes, executing the first solution for recognizable containers, and executing the second solution for unrecognizable containers; The first solution is: determining the location of each identifiable container based on the mapping relationship between the three-dimensional model and the panoramic image; The second solution is to determine the location of each unrecognizable container based on the entry and exit information of the containers in the target area, the container cargo type and the shipping and receiving locations, the identifiable container information and the stacking location information of which the image cannot be collected.

2. The method according to claim 1, characterized in that The three-dimensional model of the target storage yard is constructed, including: Collect geographic coordinate information of each container area in the target yard; Based on the geographic coordinate information of each container area, the target yard is three-dimensionally modeled using a three-dimensional engine to obtain a three-dimensional model of the target yard, and the correspondence between the three-dimensional model and the actual geographic coordinates is determined based on a three-dimensional map.

3. The method according to claim 2, characterized in that Each of the container images is captured by an image acquisition device, which is mounted on a mobile platform; the mobile platform moves along a pre-planned path, and a plurality of acquisition points are arranged on the pre-planned path. The image acquisition device captures a corresponding container image at each acquisition point according to a preset angle.

4. The method according to claim 1, characterized in that The determination of whether there is an unrecognizable container in the target area is based on the first formula: The first formula is: Y = A + CDB If Y=0, it is determined that there is no unrecognizable container in the target area; If Y≥1, it is determined that there is an unrecognizable container in the target area; Where Y is the number of unrecognizable containers in the target area; A is the number of containers in the target area before the current image acquisition; C and D are the numbers of containers entering and leaving the target area between the current image acquisition and the previous image acquisition, respectively; B is the number of recognizable containers in the panoramic image corresponding to the current image acquisition; Y, A, B, C and D are all natural numbers.

5. The method according to claim 3, characterized in that: The determining the location of each identifiable container based on the mapping relationship between the three-dimensional model and the panoramic image includes: Based on the position and angle of the acquisition point where the image acquisition device is located when acquiring the panoramic image, a conversion relationship between the coordinate system of the panoramic image and the geographic coordinate system is established to generate a GeoTIFF file with geographic information; Based on the panoramic image and the GeoTIFF file, three-dimensional mesh reconstruction and texture mapping are performed on the panoramic image based on a preset algorithm to obtain the coordinates of each identifiable container in the panoramic image; Calculate the actual geographic coordinates of each identifiable container in the panoramic image based on the coordinates of each identifiable container in the panoramic image and the correspondence between the three-dimensional model and the actual geographic coordinates; The actual geographic coordinates of each identifiable container in the panoramic image are compared with the container location layout database of the target yard to obtain the container location of each identifiable container.

6. The method according to claim 4, characterized in that The determining of the location of each unrecognizable container based on the entry and exit information of the containers in the target area, the container cargo type and the shipping and receiving locations, the identifiable container information and the stacking location information of which the image cannot be collected includes: Determine a stacking location set for which images cannot be acquired based on a location layout database of the target area and a location determination result of the target area before the current image acquisition; Calculating the number of unrecognizable containers in the target area based on the first formula; Based on the container number of each container in the target area before the current image acquisition, the container numbers of containers entering and leaving the target area between the current image acquisition and the previous image acquisition, and the container numbers of recognizable containers in the panoramic image corresponding to the current image acquisition, a set of container numbers corresponding to unrecognizable containers in the target area is determined; the container number of each container in the target area is unique, and the cargo type, entry and exit time, and shipping and receiving address of the corresponding container are found through the container number; Based on the loading and unloading rules of the target area, the cargo type, entry and exit time and delivery and receiving address corresponding to each container number, a stacking location is determined for each container number from the stacking location set whose images cannot be collected, and the container location corresponding to the container number is obtained.

7. The method according to claim 1, characterized in that After determining the container locations of each container in the target area, the method further includes: allocating container locations for the next new container to enter the container yard based on the determination result, and the allocation method is: Constructing a total objective function for container allocation, wherein the total objective function aims to minimize the passage cost of vehicles in the target yard and minimize the number of container unloading times; Determine the following constraints: each slot can only store one container, a container can only occupy one slot, the initial position of the yard crane is at the first bay, the total number of allocated containers is less than the total capacity of the corresponding area, each container cannot be placed in the air, the containers are placed in the order of first down and then up, and the number of containers stored in each container area is between the maximum capacity and the minimum capacity; Under the constraints, a preset algorithm is used to solve the objective function to obtain the allocation result of the new containers entering the yard.

8. A container yard location determination device, characterized in that: The device comprises: A construction unit is used to construct a three-dimensional model of a target storage yard; the three-dimensional model includes a plurality of container areas, each of the container areas includes a plurality of stacking locations, and each of the stacking locations is used to store containers; An acquisition unit, used for acquiring a plurality of container images of a target area, wherein the target area is at least a part of the target yard; A stitching unit, used for stitching each of the container images to obtain a panoramic image of the target area; a judgment unit, configured to detect recognizable containers in the panoramic image based on a pre-trained detection model, and to judge whether there are unrecognizable containers in the target area; a first determining unit, configured to execute a first solution for the identifiable containers in the target area, wherein the first solution is to determine the location of each identifiable container in the target area based on a mapping relationship between the three-dimensional model and the panoramic image; The second determination unit is used to execute a second solution for the unrecognizable containers in the target area, wherein the second solution is: based on the entry and exit information of the containers in the target area, the type of container cargo and the shipping and receiving locations, the recognizable container information and the stacking information of the unrecognizable containers in the target area, determine the container location of each unrecognizable container in the target area.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of any one of the methods described in claims 1-7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

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