Method, device and equipment for turning over box before box discharging of intelligent storage yard and medium

Abstract

The invention relates to the technical field of storage yard container management, in particular to a method, a device, equipment and a medium for turning over a container before container delivery of an intelligent storage yard, and the method comprises the steps that the initial stockpiling state of a storage space is acquired, and the initial stockpiling state comprises the stack number, the stack height of each stack, the container number of each position and the delivery priority of each container; according to the exit priority of the target container to be exported, traversing containers above the target container to identify a blocked container, searching a candidate stack allowing the blocked container to be stacked, and setting a container turnover rule; taking the stockpiling state of the stockpiling position as a state node, taking a moving primary blocking box as an edge between the state nodes, constructing a state space diagram, and exploring an optimal path from an initial stockpiling state to a target stockpiling state by utilizing a heuristic search algorithm; the target stockpiling state is a stacking state in which all the target boxes are delivered at one time according to the delivery priority; and converting the optimal path into a moving sequence of the blocking box, and sending an operation instruction. The box turnover device can improve the box turnover efficiency.

Description

Technical Field

[0001] This invention relates to the field of container management technology in container yards, and in particular to a method, device, equipment and medium for turning containers before they are unloaded from an intelligent container yard. Background Technology

[0002] With the continued growth in global container shipping demand, container terminals face challenges such as high operational density and complex container unloading sequences. As the core storage area for containers at the terminal, the operational efficiency of the container yard directly impacts the terminal's overall throughput capacity. Container handling in the yard, especially before unloading, is a crucial factor affecting loading efficiency, yard crane utilization, and truck scheduling. The order and efficiency of unloading directly affect the speed of loading and the smooth flow of subsequent logistics.

[0003] Existing container handling strategies are mostly based on rule-driven or static planning, which cannot adapt to the bay structure and actual yard rules of different terminals. They have poor versatility, often resulting in ineffective container handling, poor work efficiency, and increased workload for yard cranes. Summary of the Invention

[0004] In view of the above-mentioned problems in the prior art, the purpose of the present invention is to provide a method, device, equipment and medium for turning over containers before unloading from an intelligent storage yard, which can solve the problems of low efficiency and poor applicability of existing container turning strategies before unloading from storage yards.

[0005] To solve the above problems, the present invention adopts the following technical solution:

[0006] According to a first aspect of the present invention, a method for unpacking containers before unpacking in a smart storage yard is provided, the method comprising:

[0007] Obtain the initial stacking status of the container, which includes the number of stacks, the stack height of each stack, the container number of each location, and the outgoing priority of each container.

[0008] Based on the exit priority of the target container to be exited, traverse the containers above the target container to identify the blocking container, find the candidate stack that allows the blocking container to be stacked, and set the container flipping rules;

[0009] Using the stacking state of the bins as state nodes and the edge between two state nodes by moving the blocking bin once, a state space graph is constructed. A heuristic search algorithm is used to explore the optimal path from the initial stacking state to the target stacking state. The target stacking state is the stacking state in which all target bins are removed at once according to their removal priority.

[0010] The optimal path is converted into the movement order of all blocked boxes for the box-flipping operation.

[0011] Furthermore, determining the exit priority for each container includes:

[0012] Obtain the exit order of the target containers and assign a unique exit priority to each container. The exit priority values ​​are arranged in ascending order of exit order.

[0013] Furthermore, the candidate stack includes a first-type candidate stack, a second-type candidate stack, and an empty stack;

[0014] The exit priority of all containers in the first type of candidate stack is greater than or equal to the exit priority of blocked containers.

[0015] In the second type of candidate stack, the exit priority of all containers is lower than the exit priority of blocked containers.

[0016] An empty stack is empty in both the initial stack state and the target stack state.

[0017] Furthermore, the rules for searching boxes include:

[0018] When selecting candidate stacks for the blocking bins, empty stacks are preferred.

[0019] If no empty stack exists, the first type of candidate stack is chosen as the second-best option.

[0020] If no candidate stack of type 1 exists, then candidate stack of type 2 is selected;

[0021] If there are multiple candidate stacks of the same type, the candidate stack whose outgoing priority has the least impact on the blocked container is selected.

[0022] Furthermore, the heuristic search algorithm employs the A* search algorithm;

[0023] The A* search algorithm uses a cost function to evaluate feasible state nodes, guiding the direction of exploring the optimal path;

[0024] The cost function is defined as: F(q) = g(q) + h(q);

[0025] Where g(q) represents the number of bin flips performed under the current state node, and h(q) represents the estimated number of error stacking blocking bins under the current state node;

[0026] In the process of exploring the optimal path, when multiple state nodes have the same value of f(q), the branch with the smaller value of h(q) is selected first.

[0027] When h(q) is 0, the exploration terminates and the optimal path is obtained.

[0028] Furthermore, during the process of exploring the optimal path using the heuristic search algorithm, branches of the backtracking structure are discarded; and existing state nodes are recorded to avoid duplicate state nodes.

[0029] Furthermore, the movement sequence of all blocking boxes includes:

[0030] The movement sequence of container numbers corresponding to all blocked boxes, the starting stack number corresponding to each blocked box, and the target stack number corresponding to each blocked box.

[0031] Another aspect of the present invention provides a container turning device before unloading from a smart storage yard, the container turning device comprising:

[0032] The bay position status modeling module is used to obtain the initial stacking status of the bay position. The stacking status includes the number of stacks, the stack height of each stack, the container number of each position, and the exit priority of each container.

[0033] The container turning rule constraint module is used to traverse the containers above the target container to identify blocked containers based on the exit priority of the target container to be exited, find candidate stacks that allow the blocking containers to be stacked, and set the container turning rules.

[0034] The optimal path search module is used to construct a state space graph with the stacked state of the bin as the state node and the edge between the two state nodes by moving the blocking bin once. It uses a heuristic search algorithm to explore the optimal path from the initial stacked state to the target stacked state. The target stacked state is that all target bins are stacked according to their exit priority.

[0035] The scheduling output module is used to convert the optimal path into the movement order of all blocked boxes and issue box-flipping operation instructions.

[0036] In another aspect, the present invention provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the intelligent yard unpacking method as described above.

[0037] In another aspect, the present invention provides a computer-readable storage medium storing at least one instruction or at least one program, wherein the at least one instruction or at least one program is loaded and executed by a processor to implement the intelligent yard unpacking method as described above.

[0038] Due to the above technical solution, the present invention has the following beneficial effects:

[0039] This invention proposes a method, apparatus, equipment, and medium for container flipping before unloading in an intelligent container yard. The flipping method includes: obtaining the initial stacking state of the bay, which includes the number of stacks, the stack height of each stack, the container number at each location, and the unloading priority of each container; based on the unloading priority of the target container to be unloaded, traversing the containers above the target container to identify obstructing containers, searching for candidate stacks that allow the stacking of obstructing containers, and setting flipping rules; constructing a state space graph using the stacking state of the bay as state nodes and the edges between state nodes using the movement of one obstructing container, and exploring the optimal path from the initial stacking state to the target stacking state using a heuristic search algorithm; the target stacking state is the stacking state where all target containers are unloaded at once according to their unloading priority; converting the optimal path into the movement order of obstructing containers, and issuing operation commands. This invention can set flipping rules, considers the actual operation rules of the container yard, has strong adaptability and versatility, and improves flipping efficiency by using a heuristic search algorithm to explore the optimal path for the flipping order, thereby reducing the number of container movements and reducing the workload of yard crane operations. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the present invention, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0041] Figure 1 This is a flowchart of a method for turning over containers before unloading from an intelligent storage yard, provided in one embodiment of the present invention;

[0042] Figure 2 This is a flowchart of a method for turning over containers before unloading from an intelligent storage yard, provided in one embodiment of the present invention;

[0043] Figure 3 This is a structural diagram of a smart yard container turning device provided in one embodiment of the present invention;

[0044] Figure 4 This is a block diagram of an electronic device provided in one embodiment of the present invention. Detailed Implementation

[0045] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0047] Embodiments of the present invention provide a method for unpacking containers before unpacking in an intelligent storage yard, the process of which is as follows: Figure 1 As shown, this method aims to reduce the number of container turning operations to improve efficiency and adapt to the actual operational constraints of the yard. The container turning method includes the following steps S101~S104:

[0048] Step S101: Obtain the initial stacking status of the container. The initial stacking status includes the number of stacks, the stack height of each stack, the container number of each location, and the exit priority of each container.

[0049] For example, a single bay in a yard can be viewed as an S×T two-dimensional structure matrix, where S represents the number of stacks and T represents the maximum stack height. Each position in this matrix stores a container, and each container at each position corresponds to a unique container number and an exit priority. The exit priority indicates the order in which containers are extracted from bays.

[0050] Step S102: Based on the exit priority of the target container to be exited, traverse the containers above the target container to identify the blocked containers, find candidate stacks that allow the blocked containers to be stacked, and set the container flipping rules.

[0051] The target container represents the container that is ready to be retrieved. The retrieval order of the blocking container is later than that of the target container, meaning that the target container has a higher priority than the blocking container. It can be understood that the blocking container is relative to the target container, located above the target container, and is an obstruction to the successful retrieval of the target container in one go.

[0052] To ensure that the target containers can be removed in sequence, the obstructing containers above them must first be moved. The purpose of container flipping is to remove all obstructing containers above the target containers, thereby rearranging the stacking positions of the containers on the bay, ultimately allowing all target containers awaiting removal to be removed in a single pass according to their removal priority.

[0053] Among them, the container turning rules can be set according to the actual operating rules of the storage yard.

[0054] Step S103: Construct a state space graph using the stacked state of each bin as a state node and the edge between two state nodes where a blocking bin is moved once. Use a heuristic search algorithm to explore the optimal path from the initial stacked state to the target stacked state. The target stacked state is the stacked state where all target bins are removed at once according to their removal priority.

[0055] Each state node refers to the stacking state of a bay at a specific moment or after a blocking container has been moved once, i.e., the container stacking layout on the bay. The initial stacking state is the starting point of this state space graph, and the target stacking state is the target state that this state space graph needs to explore.

[0056] An edge between two state nodes represents the movement of a blocking container. It's important to note that container movement operations are only allowed to move the top container to the top of another stack, and only operations that conform to the container-flipping rules can form edges. If the container-flipping rules are violated, or if a cycle is formed between a set of states, no edge is generated.

[0057] To illustrate the meaning of the target heap status, consider the example of using Arabic numerals to represent the exit priority. The smaller the number, the higher the exit priority. In this case, the target heap status would be such that the smaller number is on top, and there is no situation where the larger number is on top of the smaller number.

[0058] Heuristic search algorithms are search strategies used to explore optimal solutions. Starting from the initial heap state, they use heuristics to guide the search process and explore the optimal path to the target heap state in the state space graph.

[0059] Step S104: Convert the optimal path into the movement order of all blocked boxes to perform the box-flipping operation.

[0060] In other words, the scheduling sequence indicated by the optimal path is transformed into an operation instruction for the scheduling of the blocked boxes that can be executed by the field bridge, and the instruction is sent to the scheduling operation control system or device to perform the box flipping operation.

[0061] In summary, embodiments of the present invention propose a method, apparatus, equipment, and medium for container flipping before container unloading in an intelligent container yard. The flipping method includes: obtaining the initial stacking state of the bay, which includes the number of stacks, the stack height of each stack, the container number at each location, and the unloading priority of each container; based on the unloading priority of the target container to be unloaded, traversing the containers above the target container to identify obstructing containers, searching for candidate stacks that allow the stacking of obstructing containers, and setting flipping rules; constructing a state space graph using the stacking state of the bay as state nodes and the edges between state nodes using the movement of one obstructing container, and exploring the optimal path from the initial stacking state to the target stacking state using a heuristic search algorithm; the target stacking state is the stacking state in which all target containers are unloaded at once according to their unloading priority; converting the optimal path into the movement order of obstructing containers, and issuing operation commands. The present invention can set flipping rules, considers the actual operation rules of the container yard, has strong adaptability and versatility, and at the same time, uses a heuristic search algorithm to explore the optimal path for the flipping order, improving flipping efficiency, reducing the number of container movements, and reducing the workload of yard crane operations.

[0062] The preferred embodiments for each step are described in further detail below.

[0063] Furthermore, in step S101, determining the exit priority for each container includes:

[0064] Obtain the exit order of the target containers and assign a unique exit priority to each container. The exit priority values ​​are arranged in ascending order of exit order.

[0065] Assigning a unique exit priority to each container ensures the uniqueness and rigor of the exit order, enabling more accurate and efficient container retrieval.

[0066] Furthermore, in step S102, the candidate stack includes a first type of candidate stack, a second type of candidate stack, and an empty stack.

[0067] The exit priority of all containers in the first type of candidate stack is greater than or equal to the exit priority of blocked containers.

[0068] In the second type of candidate stack, the exit priority of all containers is lower than the exit priority of blocked containers.

[0069] An empty stack is empty in both the initial stack state and the target stack state.

[0070] It should be noted that before calculating the box-flipping strategy, a specific location is set as an empty stack to temporarily place blocking boxes during the box-flipping process.

[0071] Dividing the candidate stack makes it easier to place containers in suitable storage locations. Classifying the candidate stack according to the exit priority of the blocking containers to be placed at the top of the candidate stack can reduce the obstruction of the candidate stack by the blocking containers and reduce the number of times the containers need to be moved.

[0072] Further, in step S102, the box-turning rules include:

[0073] When selecting candidate stacks for the blocking bins, empty stacks are preferred.

[0074] If no empty stack exists, the first type of candidate stack is chosen as the second-best option.

[0075] If no candidate stack of type 1 exists, then candidate stack of type 2 is selected;

[0076] If there are multiple candidate stacks of the same type, the candidate stack whose outgoing priority has the least impact on the blocked container is selected.

[0077] Since there are no containers in the empty stack, temporarily placing the blocked container in the empty stack will not affect the retrieval of other containers. Therefore, the empty stack can be given priority as a candidate stack for blocked containers. The empty stack can be used to store any container.

[0078] As mentioned earlier, the exit priority values ​​are arranged from smallest to largest according to the order of exit. This means that the exit priority of all containers in the first type of candidate stack is greater than or equal to the exit priority of the blocked container. Therefore, stacking the blocked container on top of the first type of candidate stack will not hinder the exit of any potential target containers waiting to be extracted in the first type of candidate stack, or the hindrance will be minimal. Thus, when a blocked container searches for a candidate stack, it prioritizes the candidate stack that minimizes its own container exit. Therefore, the first type of candidate stack is superior to the second type of candidate stack, and among candidate stacks of the same type, the one with the smallest exit priority is preferred.

[0079] Furthermore, in step S103, the heuristic search algorithm employs the A* search algorithm. The A* search algorithm is commonly used in tasks such as project management or production scheduling to minimize the total time or cost in planning the task execution order. The A* search algorithm can combine task dependencies and resource constraints to optimize the scheduling scheme through heuristic functions.

[0080] In this embodiment, the A* search algorithm uses a cost function to evaluate feasible state nodes, guiding the direction of exploring the optimal path.

[0081] The cost function is defined as: F(q) = g(q) + h(q).

[0082] Where g(q) represents the number of bin flips performed under the current state node, and h(q) represents the estimated number of error stacking blocking bins under the current state node.

[0083] In the process of exploring the optimal path, when multiple state nodes have the same value of f(q), the branch with the smaller value of h(q) is selected first.

[0084] When h(q) is 0, the exploration terminates and the optimal path is obtained.

[0085] Furthermore, during the process of exploring the optimal path using the heuristic search algorithm, branches of the backtracking structure are discarded; and existing state nodes are recorded to avoid duplicate state nodes.

[0086] In this context, a backtracking structure refers to a situation where the source and target stacks are repeated in two consecutive moves. That is, the same blocking box moves from stack A to stack B and then back from stack B to stack A in two consecutive moves.

[0087] The above two constraints are designed to reduce the number of ineffective box flips and improve box flipping efficiency.

[0088] Further, in step S104, the movement sequence of all blocking boxes includes:

[0089] The movement sequence of container numbers corresponding to all blocked boxes, the starting stack number corresponding to each blocked box, and the target stack number corresponding to each blocked box.

[0090] As a concrete example, such as Figure 2 As shown, one embodiment of the present invention proposes a detailed process for a container turning method before unloading from a smart storage yard, including the following steps:

[0091] ① Read the initial stacking status of the container and construct a status matrix to record the storage location and departure priority information of each container.

[0092] ② Mark the location of the box to be flipped and set a special stacking area that cannot be used as the final box drop point, i.e., an empty stack.

[0093] ③ Determine if the current target box is blocked;

[0094] If not, proceed directly to the next target box and repeat step ③;

[0095] If so, proceed to the next step.

[0096] ④ Identify all blocking boxes located above the current target box, and determine the candidate stack type for each blocking box. The candidate stack types include first-class candidate stack, second-class candidate stack, or empty stack.

[0097] ⑤ Based on the blocking situation, invoke the dynamically weighted A-star search algorithm, construct the state space graph, and execute the search path generation.

[0098] ⑥ Construct all possible state nodes in the state space and perform state transitions, and calculate the total cost function for each state in turn.

[0099] ⑦ Execute priority branching strategies to filter paths. Priority branching strategies include rules such as prioritizing left shifts, avoiding reverse shifts, and pruning, in order to reduce the search space.

[0100] ⑧ Determine if the current state meets the termination condition: that is, all error stack counts are 0, and there are no containers on the flipping position;

[0101] If not, return to step ⑤ to continue the search;

[0102] If so, proceed to the next step.

[0103] ⑨ Output the sequence of operation instructions corresponding to the optimal path and transmit it to the yard scheduling system for actual operation execution.

[0104] ⑩ Determine if there are still target boxes to be processed;

[0105] If so, return to step ③ to continue scheduling;

[0106] If not, the scheduling ends.

[0107] This embodiment constructs a state-space model and combines it with the A* search algorithm to generate the optimal path sequence for container turning under the condition of satisfying yard operation constraints, thereby minimizing the total cost of container turning. Furthermore, it utilizes a priority branching strategy to improve computational efficiency.

[0108] In addition, such as Figure 3 As shown, corresponding to the container turning method, another embodiment of the present invention provides a container turning device before unloading from a smart storage yard. This device includes a location state modeling module 301, a container turning rule constraint module 302, an optimal path search module 303, and a scheduling output module 304. The specific functions of each module are as follows:

[0109] The bay position status modeling module 301 is used to obtain the initial stacking status of the bay position. The stacking status includes the number of stacks, the stack height of each stack, the container number of each position, and the exit priority of each container.

[0110] The container turning rule constraint module 302 is used to traverse the containers above the target container to identify blocked containers according to the exit priority of the target container to be exited, find candidate stacks that allow the blocking containers to be stacked, and set the container turning rules.

[0111] The optimal path search module 303 is used to construct a state space graph with the stacking state of the bin as the state node and the edge between the two state nodes by moving the blocking bin once. It uses a heuristic search algorithm to explore the optimal path from the initial stacking state to the target stacking state. The target stacking state is that all target bins are stacked according to their exit priority.

[0112] The scheduling output module 304 is used to convert the optimal path into the movement order of all blocked boxes and issue box-flipping operation instructions.

[0113] The various modules of the box-flipping device are connected via data streams to ensure the continuity of status reading, judgment, and feedback.

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

[0115] One embodiment of the present invention also provides an electronic device, which includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the intelligent yard unpacking method provided in the above method embodiments.

[0116] Memory can be used to store software programs and modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory. Memory can primarily include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for the functions, etc.; the data storage area can store data created based on the use of the device, etc. Furthermore, memory can include high-speed random access memory, and can also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, memory can also include a memory controller to provide the processor with access to the memory.

[0117] Refer to the attached reference manual Figure 4The diagram shown is a block diagram of an electronic device 400 according to an embodiment of the present invention. The electronic device 400 may include one or more processors 402, system control logic 408 connected to at least one of the processors 402, system memory 404 connected to the system control logic 408, non-volatile memory (NVM) 406 connected to the system control logic 408, and network interface 410 connected to the system control logic 408.

[0118] Processor 402 may include one or more single-core or multi-core processors. Processor 402 may include any combination of general-purpose processors and special-purpose processors (e.g., graphics processors, application processors, baseband processors, etc.). In embodiments herein, processor 402 may be configured to perform operations according to... Figures 1 to 3 One or more embodiments of the various embodiments shown.

[0119] In some embodiments, system control logic 408 may include any suitable interface controller to provide any suitable interface to at least one of the processors 402 and / or any suitable device or component communicating with system control logic 408.

[0120] In some embodiments, system control logic 408 may include one or more memory controllers to provide an interface to system memory 404. System memory 404 may be used to load and store data and / or instructions. In some embodiments, system memory 404 of electronic device 400 may include any suitable volatile memory, such as suitable dynamic random access memory (DRAM).

[0121] NVM / Memory 406 may include one or more tangible, non-transitory computer-readable media for storing data and / or instructions. In some embodiments, NVM / Memory 406 may include any suitable non-volatile memory such as flash memory and / or any suitable non-volatile storage device, such as at least one of HDD (Hard Disk Drive), CD (Compact Disc) drive, and DVD (Digital Versatile Disc) drive.

[0122] NVM / memory 406 may include a portion of storage resources mounted on a device of electronic device 400, or it may be accessible by the device but is not necessarily part of the device. For example, the non-volatile memory NVM / memory 406 may be accessed over a network via network interface 410.

[0123] Specifically, system memory 404 and NVM / memory 406 may each include a temporary copy and a permanent copy of instruction 420. Instruction 420 may include, when executed by at least one of processors 402, causing electronic device 400 to perform, as Figures 1 to 3 The instructions for the container turning method before unloading from the smart yard are shown. In some embodiments, the instructions 420, hardware, firmware and / or their software components may additionally / alternatively be placed in the system control logic 408, network interface 410 and / or processor 402.

[0124] Network interface 410 may include a transceiver for providing a radio interface to electronic device 400, thereby enabling communication with any other suitable device (such as a front-end module, antenna, etc.) via one or more networks. In some embodiments, network interface 410 may be integrated into other components of electronic device 400. For example, network interface 410 may be integrated into at least one of the following: a communication module of processor 402, system memory 404, NVM / memory 406, and firmware device (not shown) with instructions, which, when at least one of processor 402 executes the instructions, enable electronic device 400 to implement... Figures 1 to 3 One or more embodiments of the various embodiments shown.

[0125] The network interface 410 may further include any suitable hardware and / or firmware to provide a multiple-input multiple-output radio interface. For example, the network interface 410 may be a network adapter, a wireless network adapter, a telephone modem, and / or a wireless modem.

[0126] In one embodiment, at least one of the processors 402 may be packaged together with the logic of one or more controllers for system control logic 408 to form a system package (SiP). In another embodiment, at least one of the processors 402 may be integrated on the same die with the logic of one or more controllers for system control logic 408 to form a system on chip (SoC).

[0127] The electronic device 400 may further include an input / output (I / O) device 412. The I / O device 412 may include a user interface enabling a user to interact with the electronic device 400; the peripheral component interface is designed to allow peripheral components to also interact with the electronic device 400. In some embodiments, the electronic device 400 may also include sensors for determining at least one of environmental conditions and location information related to the electronic device 400.

[0128] In some embodiments, the user interface may include, but is not limited to, a display (e.g., a liquid crystal display, a touch screen display, etc.), a speaker, a microphone, one or more cameras (e.g., a still image camera and / or a video camera), a flashlight (e.g., a light-emitting diode flash), and a keyboard.

[0129] In some embodiments, the peripheral component interface may include, but is not limited to, a non-volatile memory port, an audio jack, and a power interface.

[0130] In some embodiments, the sensor may include, but is not limited to, a gyroscope sensor, an accelerometer, a proximity sensor, an ambient light sensor, and a positioning unit. The positioning unit may also be part of or interact with the network interface 410 to communicate with components of the positioning network, such as Global Positioning System (GPS) satellites.

[0131] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the electronic device 400. In other embodiments of the present invention, the electronic device 400 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0132] An embodiment of the present invention also provides a computer-readable storage medium that can be disposed in an electronic device to store at least one instruction or at least one program related to implementing a method, wherein the at least one instruction or the at least one program is loaded and executed by the processor to implement the intelligent yard unpacking method provided in the above-described method embodiment.

[0133] Optionally, in embodiments of the present invention, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0134] One embodiment of the present invention also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the intelligent yard pre-unpacking turning method provided in the various optional implementations described above.

[0135] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0136] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0137] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for turning a container before unloading in an intelligent yard, characterized by, The method comprises: acquiring an initial stacking state of a bay, the initial stacking state comprising a number of stacks, a height of each stack, a container number of each position, and a departure priority of each container; according to the departure priority of a target container to be departed, traversing containers above the target container to identify a blocking container, finding a candidate stack allowing the blocking container to be stacked, and setting a container flipping rule; taking the stacking state of the bay as a state node, taking moving the blocking container once as an edge between two state nodes, constructing a state space graph, and exploring an optimal path from the initial stacking state to a target stacking state by using a heuristic search algorithm, the target stacking state being a stacking state in which all target containers are departed at one time according to the departure priority; converting the optimal path into a moving sequence of all blocking containers to perform container flipping operation.

2. The smart yard pre-depalletizing method according to claim 1, characterized in that, The determination of the departure priority corresponding to each container comprises: acquiring a departure order of the target containers, and assigning a unique departure priority to each container, the numerical value of the departure priority being arranged from small to large according to the departure order.

3. The smart yard pre-depalletizing method according to claim 2, characterized in that, The candidate stacks comprise a first type of candidate stack, a second type of candidate stack, and an empty stack; all containers in the first type of candidate stack have a departure priority greater than or equal to the departure priority of the blocking container; all containers in the second type of candidate stack have a departure priority less than the departure priority of the blocking container; the empty stack is empty in the initial stacking state and the target stacking state.

4. The smart yard pre-depalletizing method according to claim 3, characterized in that, The container flipping rule comprises: when selecting a candidate stack of the blocking container, the empty stack is preferentially selected as the candidate stack; if the empty stack does not exist, the first type of candidate stack is selected as a suboptimal selection; if the first type of candidate stack does not exist, the second type of candidate stack is selected; if the same type of candidate stack is not unique, a candidate stack in which all containers have a departure priority least affecting the blocking container is selected.

5. The smart yard pre-deconsolidation method of turning containers before outbound shipment according to claim 1, wherein, The heuristic search algorithm adopts an A-star search algorithm; the A-star search algorithm uses a cost function to evaluate a feasible state node, and guides the direction of exploring the optimal path; the cost function is defined as: F(q)=g(q)+h(q); wherein g(q) represents the number of container flipping operations performed under the current state node, and h(q) represents an estimated number of incorrectly stacked blocking containers under the current state node; during the exploration of the optimal path, when multiple state nodes have the same numerical value of f(q), a branch with a smaller numerical value of h(q) is preferentially selected; when h(q) is 0, the exploration is terminated, and the optimal path is obtained.

6. The smart yard pre-depalletizing case flipping method of claim 5, wherein, During the exploration of the optimal path by the heuristic search algorithm, branches of a backtracking structure are discarded, and the state nodes that have appeared are recorded to avoid repeated state nodes.

7. The smart yard pre-deconsolidation method of turning containers before outbound, according to claim 1, wherein, The moving sequence of all blocking containers comprises: a moving sequence of container numbers corresponding to all blocking containers, a starting stack number corresponding to each blocking container, and a target stack number corresponding to each blocking container.

8. A turning device before the case out of the intelligent yard, characterized in that, The container flipping device comprises: The bay state modeling module is configured to obtain an initial stacking state of the bay, the stacking state including a number of stacks, a height of each stack, a container number of each position, and a departure priority corresponding to each container; The box flipping rule constraint module is configured to, according to the departure priority corresponding to the target box to be departed, traverse the containers above the target box to identify a blocking box, find a candidate stack allowing the blocking box to be stacked, and set a box flipping rule; The optimal path searching module is configured to take the stacking state of the bay as a state node, take moving the blocking box once as an edge between two state nodes, construct a state space graph, and explore an optimal path from the initial stacking state to a target stacking state by using a heuristic search algorithm, the target stacking state being that all target boxes are stacked according to the departure priority; The scheduling output module is configured to convert the optimal path into a moving sequence of all blocking boxes, and issue a box flipping operation instruction.

9. An electronic device, comprising: The electronic device includes a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the box flipping method before departure of the intelligent yard as claimed in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the box flipping method before departure of the intelligent yard as claimed in any one of claims 1-7.

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