Port automation field bridge path planning method and system

Abstract

The invention discloses a port automation field bridge path planning method and system, and the method comprises the steps: splitting an operation instruction distributed by a TOS system, and reading the position information of a site where the operation instruction is located; acquiring position information of all available automatic field bridges in the wharf; distributing the operation instructions to available automatic field bridges according to a preset priority distribution method, and enabling each automatic field bridge to be matched and corresponding to the corresponding operation instruction; and based on the corresponding relationship between the automatic field bridge and the operation instruction, planning a walking route of the automatic field bridge by using a particle swarm optimal path planning algorithm, so that the automatic field bridge reaches a specified position for operation in a safe, shortest-path and shortest-time-consumption manner. According to the method, the automatic path planning of the port automatic field bridge is realized, so that the automatic field bridge can reach a specified position for operation in a safe, shortest-path and shortest-time-consumption manner.

Description

Technical Field

[0001] The present invention relates to the technical field of port operation, and in particular to a port automated yard bridge path planning method and system. Background Art

[0002] With the rapid development of the port logistics industry, the role of automated yard cranes in port operations has become increasingly prominent. During the process of port automated operations, how to complete efficient and accurate automated operations under the premise of safety is a key issue that smart ports are concerned about. The automated release of operation instructions is issued by the TOS (Total Operating System) system to the port operation system, and the instructions are distributed to each yard crane for automated instruction operations according to sequential logic, replacing manual labor with automation, reducing manual intervention and saving labor costs. However, the existing instruction distribution and yard crane travel routes affect the dispatching and operation of the yard crane and the efficiency of automated operations.

[0003] The command distribution and path planning issues of automated yard cranes have always been the key factors restricting their efficiency improvement. Traditional command distribution and path planning methods often have problems such as low efficiency and poor optimization effect, and cannot meet the efficient and intelligent requirements of automated port operations. Therefore, it is necessary to design a command distribution method to improve the efficiency of yard crane use and select the optimal path for the yard crane during the operation process, which is of great significance to improve the overall efficiency of port automation operations. Summary of the invention

[0004] The purpose of the present invention is to overcome the problems of low utilization rate and low operating efficiency of the current automated operation yard bridges in port terminals, and to provide a port automated yard bridge path planning method, which is an automated yard bridge instruction dispatching method that comprehensively considers the operation, and combines the particle swarm path planning algorithm to achieve efficient dispatching of automated yard bridge instructions and mobile path optimization, which can significantly improve the operating efficiency and overall performance of the yard bridge.

[0005] One aspect of the present invention provides a port automation bridge path planning method, comprising the steps of:

[0006] Split the work instructions distributed by the TOS system and interpret the site location information of the work instructions;

[0007] Obtain the location information of all available automated yard cranes in the terminal;

[0008] Allocate the operation instructions to the available automation field bridges according to the preset priority dispatching and allocation method, so that each automation field bridge is matched with the corresponding operation instructions;

[0009] Based on the corresponding relationship between the automated field bridge and the operation instructions, the particle swarm optimal path planning algorithm is used to plan the walking route of the automated field bridge, so that the automated field bridge can reach the designated location for operation in a safe, shortest path and shortest time manner;

[0010] The preset priority dispatching allocation method includes dispatching the operation instructions by operation type and / or bay position priority;

[0011] Dispatch work instructions by priority, including:

[0012] Sort the bays by size. When dispatching job instructions, give priority to the larger bays and the smaller bays last. Dispatch the job instructions in order of bay size. For job instructions of the same bay, dispatch them in order of job type priority.

[0013] Among them, the operation instructions are distributed and assigned according to the operation type in priority, including:

[0014] Different operation types are set according to the different types of terminal operations, and then the different operation types are sorted according to the operation priority; when distributing operation instructions, the operation instructions of the operation type with high priority are given priority to the nearest automated yard bridge.

[0015] Among them, different operation types include loading, unloading, container loading, container picking, container shifting, and container unloading at the same location.

[0016] Among them, the job instructions of different job types and different levels are first sorted by job type, and the job instructions of different levels of the same job type are dispatched in order of priority of the largest level.

[0017] Among them, the operation instructions for unloading boxes at the same bay position are sorted according to the principle of giving priority to the larger bay position.

[0018] Among them, there are multiple operation instructions for the same bay of the same container truck, and the multiple operation instructions are arranged consecutively in order of priority.

[0019] Among them, in the same operation type and the same bay level operation instructions, the operation instructions of the bay with a higher level are arranged in front of the operation instructions of the bay with a lower level.

[0020] Another aspect of the present invention provides a port automated field bridge path planning system, including a memory and a processor, the memory is used to store a method program that supports the execution of the processor, and the processor is configured to execute the program stored in the memory to implement the port automated field bridge path planning method.

[0021] The automated operation instruction dispatching method proposed in the present invention, after receiving the operation instruction issued by the terminal operating system TOS, performs a preset instruction priority dispatching method or strategy, performs secondary optimization dispatching of the operation instruction, and then plans the optimal moving path for the automated yard crane to execute the operation instruction in combination with the particle swarm path optimization algorithm. After the optimal path planning is completed, the yard crane is controlled to arrive at the designated location by the optimal path and the fastest time after receiving the optimally dispatched operation instruction, thereby improving the terminal operation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of the port automation yard bridge path planning method of the present invention.

[0023] Figure 2 It is a schematic diagram of the processing flow of the particle swarm path optimization algorithm of the present invention.

[0024] Figure 3 It is a structural schematic diagram of the port automation yard bridge path planning of the present invention. DETAILED DESCRIPTION

[0025] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0026] The automated operation instruction dispatching method proposed in the present invention is based on the terminal automated operation process, designs an optimization method, reduces redundant operation time, and improves operation efficiency.

[0027] See also Figure 1 As shown, the automatic operation instruction dispatching method proposed by the present invention adopts the following steps:

[0028] S1. Split the operation instructions distributed by the TOS system and interpret the location information of the site where the operation instructions are located;

[0029] S2. Obtain the location information of all available automated yard bridges in the terminal;

[0030] S3. Assign the job instructions to the available automation field bridges according to the preset priority distribution method, so that each automation field bridge matches the corresponding job instructions;

[0031] S4. Based on the corresponding relationship between the automated field bridge and the operation instructions, the particle swarm optimal path planning algorithm is used to plan the walking route of the automated field bridge, so that the automated field bridge can reach the designated location for operation in a safe, shortest path and shortest time.

[0032] In an embodiment of the present application, in a preferred implementation, the preset priority dispatching and allocating method includes dispatching and allocating job instructions by job type and / or bay position, that is, when job instructions are dispatched to an automated field bridge, they can be dispatched and allocated by job type and / or by bay position. Generally, the instructions are dispatched to the corresponding automated field bridge at a safe distance based on the position signal of the automated field bridge and the field bay position information contained in the job instructions.

[0033] In the embodiment of the present application, the priority distribution of job instructions by job type includes setting different job types according to the different types of terminal operations, and then sorting the different job types according to job priorities; when distributing job instructions, priority is given to distributing job instructions of job types with high priority to the nearest automated yard bridge, that is, the job instructions are distributed in the order of sorting priority. By using the different priorities of job types, high-priority instructions are preferentially distributed to the nearest automated yard bridge, so that high-priority instructions can be completed faster. Distributing job instructions by job type alone may result in "jumping" operations. The lanes in some areas inside the terminal site are narrow, and the movement of the yard bridge lanes and container trucks must be included. It has a greater impact on the site without borrowing lanes and may cause congestion. Therefore, the embodiment of the present application also proposes to supplement the priority distribution of job instructions by bay.

[0034] In one embodiment, the different operation types may include loading, unloading, loading containers, picking up containers, moving containers, unloading containers at the same bay, etc., or other operation types, but are not limited to these. In this order, loading operations have the highest priority, followed by unloading, and unloading containers at the same bay is the last operation.

[0035] In one embodiment, the above-mentioned dispatching of the job instructions by rank priority includes sorting the rank by size, and when dispatching the job instructions, the large rank is given priority and the small rank is ranked last, and the job instructions are dispatched in order of the rank size; the job instructions of the same rank are dispatched in the order of the job type priority. By dispatching the job instructions by rank priority, it can be achieved that the large rank is done first and the small rank is done later, and the same rank is sorted according to the priority of the instruction type. This sorting can ensure that all instructions are completed in order, reducing the possibility of traffic jams and large vehicles running back and forth.

[0036] Due to the large number of port terminal operations, the rules for sorting operation instructions will also be changed due to different factors, such as first-come-first-served, first-served, first-served, central control-designated, weighted, etc. Therefore, in the embodiment of the present application, on the basis of priority distribution by operation type and / or priority distribution by bay position, the following distribution strategies are further included:

[0037] Among them, the job instructions of different job types and different levels are first sorted by job type, and the job instructions of different levels of the same job type are dispatched in order of priority of the largest level.

[0038] Among them, the operation instructions for unloading boxes at the same bay position are sorted according to the principle of giving priority to the larger bay position.

[0039] Among them, there are multiple operation instructions for the same bay of the same container truck, and the multiple operation instructions are arranged consecutively in order of priority.

[0040] Among them, in the same operation type and the same bay level operation instructions, the operation instructions of the bay with a higher level are arranged in front of the operation instructions of the bay with a lower level.

[0041] Specifically, in the priority by operation type, the loading priority shall be based on that given by the terminal operating system TOS terminal.

[0042] In the embodiment of the present application, after the operation instruction is matched with the automated field bridge in the site, the operation instruction, the automated field bridge and the corresponding control terminal will be further matched. When matching, the terminal management system will allocate the operation instruction to the control station with the least operation according to the number of online operations of the control terminal. Among them, the control terminal with operation authority can only see the operation instruction related to the automated field bridge to which it is connected, and the control terminal with management authority can not only see the operation instruction related to the connected automated field bridge, but also see all the assigned and unassigned operation instructions, and can manually allocate the operation instruction.

[0043] In an embodiment of the present application, after the automated field bridge receives the optimal operating instruction assigned to it, it plans the moving path of the field bridge based on the particle swarm algorithm and according to the site road conditions, so that the field bridge can reach the designated location for operation in the safest, shortest and shortest time, including constructing a fitness function with the moving time, moving distance, etc. of the automated field bridge as the objective function, and selecting the optimal moving path according to the constructed fitness function.

[0044] The particle swarm algorithm described above is derived from the regularity of bird group activities, and then a simplified model is established using group intelligence. The optimal solution is found by simulating the movement of particles in the group in the search space. The core idea is to simulate the behavior of particles in the group. In the algorithm, each particle represents a feasible solution to the problem. Particles have a certain speed and position. They adjust their own speed and position according to the current position and speed, as well as information such as the historical optimal position and the global optimal position, in the hope of finding a better solution. Specifically, the position of each particle can be represented as an n-dimensional vector, representing a solution vector, and its speed is an n-dimensional vector. Each particle needs to update its speed and position so that it gradually approaches the optimal solution.

[0045] like Figure 2As shown, the steps of the particle swarm optimization algorithm include

[0046] Step 1: Initialize the particle swarm: According to the working environment, task requirements and other factors of the automated field bridge, randomly initialize the particle position xi, speed vi and other parameters to generate the initial particle swarm N, where each particle represents a moving path.

[0047] Step 2: Construct fitness function: Calculate the fitness value of each particle. According to the characteristics of the field bridge transportation task, construct a fitness function with moving time, moving distance, etc. as the objective function to evaluate the quality of each particle in the particle swarm. Update the individual historical optimal position and the global optimal position. The optimal position searched by the i-th particle so far is called the individual extreme value, denoted by P best , the optimal position searched by the entire particle swarm so far is the global extreme value, denoted as g best In order to preserve individuals with high fitness, the fitness fitvalue is defined as:

[0048] ;

[0049] Where, distance is the distance of each particle (path), and collision is the collision coefficient, which is 0 if the path collides with the obstacle and 0.1 if it does not collide.

[0050] Step 3: Particle swarm update: According to the fitness value of each particle in the particle swarm, according to the rules of the particle swarm optimization algorithm, according to the formulas of speed update and position update, the position, speed and other parameters of the particle swarm are updated to generate a new generation of particle swarm.

[0051] Speed ​​Update: ;

[0052] Where W is the weight coefficient, For speed, , is the learning factor, , is the individual optimal position and the global optimal position, is the current location, , A random number used to increase the randomness of the search.

[0053] Location Update: ;

[0054] in For speed, For location.

[0055] Step 4: Local search: During the particle swarm update process, a local search strategy is used to locally optimize the excellent particles in the particle swarm to improve the optimization effect. If the termination condition is met, the current optimal solution is output, otherwise return to step 2:

[0056] Step 5: Path planning: Based on the optimal solution obtained by the particle swarm optimization algorithm, the path planning of the automated field bridge is carried out as the path of the automated field bridge to achieve efficient completion of the transportation task.

[0057] The particle swarm algorithm adopted in the present invention has few parameters, is easy to implement, and has strong global search capability. The present invention combines the field bridge moving route with the particle swarm algorithm, and can quickly and efficiently plan the field bridge moving route.

[0058] In an embodiment of the present application, a port automated field bridge path planning system is also provided, including a memory and a processor, the memory is used to store a method program that supports the execution of the processor, and the processor is configured to execute the program stored in the memory to implement the port automated field bridge path planning method. For the content that is not detailed in this section, please refer to the technical content of the port automated field bridge path planning method of the present invention and the content of the specific implementation method.

[0059] The port automation bridge path planning system can be a terminal device. The port automation bridge path planning system can be implemented by a computer device. Its internal structure is as follows: Figure 3 As shown, it includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the port automation field bridge path planning system is used to provide computing and control capabilities.

[0060] The memory of the port automation field bridge path planning system includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the port automation field bridge path planning system is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies.

[0061] When the computer program is executed by the processor, a method for port automation bridge path planning is implemented. The display screen of the port automation bridge path planning system device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the port automation bridge path planning system can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0062] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the port automation yard bridge path planning system to which the solution of the present application is applied. The specific port automation yard bridge path planning system may include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0063] The port automated yard bridge path planning method and system of the present invention, after receiving the operation instruction from the terminal operating system TOS, automatically distributes the operation instruction according to the preset design instruction sorting rules to avoid operation confusion, and distributes the optimal operation instruction to the most suitable automated yard bridge. Then, combined with the particle swarm path planning algorithm, through iterative calculation, the position and speed of the particle swarm are gradually optimized, thereby obtaining the optimal path planning scheme for the automated yard bridge.

[0064] Compared with traditional methods, the port automated gantry crane path planning method and system of the present invention have the advantages of small calculation amount, good optimization effect, strong adaptability, etc., which can significantly improve the transportation efficiency of the automated gantry crane and reduce operating costs.

[0065] The basic principles and main features of the present invention and the advantages of the present invention are shown and described above. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention.

[0066] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the claims are included in the present invention.

[0067] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A port automation bridge path planning method, characterized in that: Includes steps: Split the work instructions distributed by the TOS system and interpret the site location information of the work instructions; Obtain the location information of all available automated yard cranes in the terminal; Allocate the operation instructions to the available automation field bridges according to the preset priority dispatching and allocation method, so that each automation field bridge is matched with the corresponding operation instructions; Based on the corresponding relationship between the automated field bridge and the operation instructions, the particle swarm optimal path planning algorithm is used to plan the walking route of the automated field bridge, so that the automated field bridge can reach the designated location for operation in a safe, shortest path and shortest time manner; The preset priority dispatching allocation method includes dispatching the operation instructions by operation type and / or bay position priority; Dispatch work instructions by priority, including: Sort the bays by size. When dispatching job instructions, give priority to the larger bays and the smaller bays last. Dispatch the job instructions in order of bay size. For job instructions of the same bay, dispatch them in order of job type priority.

2. The port automation bridge path planning method according to claim 1 is characterized in that: Prioritize the distribution of work instructions by work type, including: Different operation types are set according to the different types of terminal operations, and then the different operation types are sorted according to the operation priority; when distributing operation instructions, the operation instructions of the operation type with high priority are given priority to the nearest automated yard bridge.

3. The port automation bridge path planning method according to claim 2 is characterized in that: Different types of operations include loading, unloading, loading containers, picking up containers, transferring containers, and unloading containers at the same location.

4. The port automation bridge path planning method according to claim 1 is characterized in that: Job instructions of different job types and different levels are first sorted by job type, and job instructions of the same job type and different levels are dispatched in order of priority of the largest level.

5. The port automation bridge path planning method according to claim 1 is characterized in that: For the operation instructions of unloading boxes at the same bay position, they shall be sorted according to the principle of giving priority to the larger bay position.

6. The port automation bridge path planning method according to claim 1 is characterized in that: There are multiple operation instructions for the same container truck and the same bay, and the multiple operation instructions are arranged consecutively in order of priority.

7. The port automation bridge path planning method according to claim 1 is characterized in that: In the same operation type and the same bay job instructions, the job instructions of the higher bay are placed before the job instructions of the lower bay.

8. Port automation bridge path planning system, characterized by: It comprises a memory and a processor, wherein the memory is used to store a method program that supports execution by the processor, and the processor is configured to execute the program stored in the memory to implement the port automation yard bridge path planning method according to any one of claims 1 to 7.

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