Method and system for dispatching forced vehicle end of plane storage

Abstract

The invention provides a method and a system for scheduling a forced vehicle end of a plane warehouse, and solves the technical problem that an existing scheduling mechanism is liable to be interfered by communication quality and cannot guarantee the automatic transfer efficiency. The method comprises the steps that splitting planning of a carrying task is carried out through a cloud scheduling system, and splitting planning data at least comprises the number of equipment ends, the initial state of the equipment ends and the running path of the equipment ends; the equipment end receives the corresponding split planning data to establish a driving process, and feeds back a driving state to the cloud scheduling system regularly; the cloud scheduling system pre-judges equipment ends appearing in a path crossing range in a subsequent time period according to the advancing state of each equipment end, and sends associated data to related equipment ends according to a pre-judgment result, and the associated data at least comprises identification information of the related equipment ends; and the equipment end establishes a communication link between the equipment ends according to the associated data, and adjusts the driving state of the related equipment end according to a preset decision rule. And the scheduling real-time performance and the communication reliability are decoupled. And the automatic transfer efficiency is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic dispatching, and in particular to a method and system for strong vehicle-side dispatching of flat warehousing. Background Art

[0002] In the prior art, the dispatching of transport vehicles in warehouses involves warehouse management systems, automatic transport equipment and cloud dispatching systems. The warehouse management system is used to clarify the quantity of materials allocated and the locations of materials entering and exiting the warehouse station and their locations within the warehouse station, and is usually deployed within the warehouse station. Automatic transport equipment is used to carry quota materials for controlled transfer, and usually uses transport equipment with basic communication capabilities and data processing computing power, such as AGV (Automated Guided Vehicle). The cloud dispatching system is used to allocate transport capacity needs, plan the transfer routes between material transfer starting points, and control the driving status of transport equipment in real time, such as speed and start and stop. Due to the influence of the computing power requirements of the scheduling control scale, it is usually deployed in a remote computer room outside the warehouse station.

[0003] In the existing dispatching process, the cloud dispatching system monitors the automatic transport equipment in real time through the wireless communication link, and actively controls the traffic of each equipment end, which has high requirements for the synchronization of communication between the (automatic transport) equipment end and the cloud end, and the real-time performance of data processing. For example, materials are concentrated in warehouses and stations, and the accessible paths are limited, often forming intersections. When a large number of equipment ends converge at an intersection while moving, the cloud dispatching system needs to form a traffic control strategy in real time to control the traffic flow and diversion direction in the intersection area. Once the communication between the equipment end and the cloud end is out of sync, a state feedback delay will be formed, causing a deadlock problem at the intersection. Summary of the invention

[0004] In view of the above problems, an embodiment of the present invention provides a strong vehicle-side scheduling method and system for planar warehousing, which solves the technical problem that the existing scheduling mechanism is easily affected by communication quality interference and cannot ensure the efficiency of automated transportation.

[0005] The strong vehicle-side dispatching method for plane warehousing of an embodiment of the present invention includes:

[0006] The transport task is split and planned through the cloud scheduling system, and the split planning data includes at least the number of equipment terminals, the initial status of the equipment terminals, and the driving path of the equipment terminals;

[0007] The device receives the corresponding split planning data to establish the driving process and regularly feeds back the driving status to the cloud scheduling system;

[0008] The cloud dispatching system predicts the device terminals that will appear in the path intersection range in the subsequent period according to the travel status of each device terminal, and sends the associated data to the relevant device terminals according to the prediction result, and the associated data at least includes the identification information of the relevant device terminals;

[0009] The device side establishes a communication link between the device sides according to the associated data, and adjusts the driving status of the relevant device sides according to the preset decision rules.

[0010] In one embodiment of the present invention, the splitting plan of the transport task includes:

[0011] The cloud dispatching system splits the transport task to match the number of devices and configures the identification and initial driving status of each device.

[0012] The cloud-based dispatching system uses the A* search algorithm to plan the device-side driving path according to the loading position of the device and the target position of the transport task to form driving path data.

[0013] In one embodiment of the present invention, the process of establishing the driving includes:

[0014] Each device automatically follows the driving path and performs automatic navigation at the specified speed according to the task instructions and split planning data, forming a transfer driving process;

[0015] The feedback progress status includes:

[0016] During the transfer process, each device regularly feeds back the travel status including travel speed and location to the cloud scheduling system.

[0017] In one embodiment of the present invention, the predicting of the device end appearing in the path intersection range in the subsequent time period includes:

[0018] The cloud scheduling system calculates the set of devices that enter the intersection range of each path after the buffer period;

[0019] The sending of the associated data to the relevant device end according to the prediction result includes:

[0020] The cloud scheduling system forms related data shared by related devices based on the device collection and sends it to related devices in batches.

[0021] In one embodiment of the present invention, adjusting the driving state of the relevant device terminal according to the preset decision rule includes:

[0022] The relevant device side establishes a communication link based on the associated data;

[0023] Determine the decision-making device end among the relevant device ends through a priority comparison rule;

[0024] The decision-making device forms a speed-up control parameter of the decision-making device and a speed-down control parameter of other related devices according to the avoidance rule;

[0025] After the decision-making device and other related devices leave the path intersection range, the communication link is released according to the recovery rules, the travel speed is restored, and the travel status feedback is performed.

[0026] The strong vehicle-side dispatching system for plane storage of the embodiment of the present invention includes:

[0027] A memory, used to store the program code of the above-mentioned planar warehousing strong vehicle end scheduling method processing process;

[0028] A processor is used to execute the program code.

[0029] The strong vehicle-side dispatching system for plane storage of the embodiment of the present invention includes:

[0030] A task splitting device, used to split and plan the transport task through the cloud scheduling system, where the splitting planning data at least includes the number of equipment terminals, the initial state of the equipment terminals, and the driving path of the equipment terminals;

[0031] Driving feedback device, used for receiving the corresponding split planning data on the device side to establish the driving process, and regularly feeding back the driving status to the cloud scheduling system;

[0032] A trend prediction device is used for the cloud scheduling system to predict the device terminals that will appear in the path intersection range in the subsequent period according to the travel status of each device terminal, and send related data to the relevant device terminals according to the prediction result, and the related data at least includes the identification information of the relevant device terminals;

[0033] The on-site adjustment device is used for the device end to establish a communication link between device ends according to the associated data, and adjust the driving status of the relevant device end according to the preset decision rules.

[0034] The vehicle-side strong scheduling method and system for planar warehousing of the embodiment of the present invention decouples scheduling real-time performance from communication reliability. The basic computing power of the device side is used to perform efficient calculations of short-term path avoidance between device sides within a limited range, and the abundant computing power of the cloud scheduling system is used to perform efficient calculations of dynamic path conflict areas within the entire warehouse station. The cloud scheduling system timely perceives and coordinates the long-term path optimization between parallel device sides formed by a large number of split tasks. The efficiency of automated transportation is effectively improved by strengthening the control logic of the vehicle device side. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic flow chart of a method for strong vehicle-side dispatching of flat warehousing according to an embodiment of the present invention.

[0036] Figure 2 Shown is a schematic diagram of the architecture of a strong vehicle-side dispatching system for planar warehousing according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention clearer and more understandable, the present invention is further described below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] A method for strong vehicle-side dispatching of planar warehousing according to an embodiment of the present invention is as follows Figure 1 As shown. Figure 1 In this embodiment, the present invention includes:

[0039] Step 100: Split and plan the transport task through the cloud scheduling system, where the split planning data includes at least the number of devices, the initial state of the devices, and the driving path of the devices.

[0040] Those skilled in the art can understand that there is a communication link between the warehouse management system and the cloud scheduling system. The warehouse management system forms a transportation task that clearly defines the material transportation quantity and loading and unloading location based on the material transfer needs of the warehouse station. Batch transportation tasks are split through the cloud scheduling system to clarify the number of equipment terminals corresponding to the material load in each transportation task, the initial state of the equipment terminal driving speed and change rate corresponding to the safe transportation of materials, and the equipment driving path planned in the passable roads of the warehouse station. The split planning data can also include basic data such as equipment terminal identification, task priority, and cargo type.

[0041] Step 200: The device receives the corresponding split planning data to establish the driving process and regularly feeds back the driving status to the cloud scheduling system.

[0042] The split planning data is sent to the corresponding equipment end, and the equipment end establishes the driving process according to the initial state and driving path after the materials are loaded. Regular feedback can be based on the preset feedback frequency, or it can include feedback formed by (unexpected state) trigger conditions. The driving state includes the current position and speed.

[0043] Step 300: The cloud scheduling system predicts the device terminals that will appear in the path intersection range in the subsequent time period according to the travel status of each device terminal, and sends related data to the relevant device terminals according to the prediction result, and the related data at least includes the identification information of the relevant device terminals.

[0044] The device terminals that appear in the path intersection range in the subsequent time period mainly refer to the device terminals including the intersection and the surrounding passable path range. The intersection includes at least three directions. The cloud scheduling system processes data according to the current travel status of each device terminal to form a set of device terminals that may meet in the same intersection range in a certain subsequent period of time. By default, the path intersection range referred to satisfies the establishment of a communication link between the device terminals and can stabilize the distance for data transmission. The identification information of the relevant device terminal includes but is not limited to the communication identification or communication address.

[0045] Step 400: The device side establishes a communication link between the device sides according to the associated data, and adjusts the driving status of the relevant device sides according to the preset decision rules.

[0046] The associated data enables the relevant device to obtain the basic data for establishing a communication link with the communication partner. After the communication link is established between the two device ends, data exchange is formed. The preset decision rules include but are not limited to the rules for determining the dominant device between the device ends, the avoidance rules between the device ends, and the recovery rules after the device end avoids, etc.

[0047] The strong vehicle-side scheduling method for planar warehousing in the embodiment of the present invention decouples scheduling real-time performance from communication reliability. The basic computing power of the device side is used to perform efficient calculations of short-term path avoidance between device sides within a limited range, and the abundant computing power of the cloud scheduling system is used to perform efficient calculations of dynamic path conflict areas within the entire warehouse station. The cloud scheduling system timely perceives and coordinates the long-term path optimization between parallel device sides formed by a large number of split tasks. The efficiency of automated transportation is effectively improved by strengthening the control logic of the vehicle device side.

[0048] like Figure 1 As shown, in one embodiment of the present invention, step 100 includes:

[0049] Step 110: The cloud-based dispatching system splits the transport task to match the number of devices, and configures the identification and initial driving state of each device.

[0050] The identification of each device end includes the device identification, the device network communication identification or the communication address. The initial driving state includes the average speed, the turning speed and the acceleration speed under different road conditions such as the ground slope and the turning arc.

[0051] Step 120: The cloud dispatching system uses the A* search algorithm to plan the device-side driving path according to the loading position of the device and the target position of the transport task to form driving path data.

[0052] The A* search algorithm plans the driving path based on the accessible roads within the warehouse station, forming the driving path data that the device follows.

[0053] like Figure 1 As shown, in one embodiment of the present invention, step 200 includes:

[0054] Step 210: Each device terminal automatically follows the driving path and performs automatic navigation at a specified speed according to the split planning data based on the task instruction, thereby forming a transfer driving process.

[0055] Each device terminal drives in parallel within the warehouse site, and automatically follows the driving path at a specified speed for automatic navigation.

[0056] Step 220: During the transfer process, each device terminal regularly feeds back the travel status including travel speed and position to the cloud scheduling system.

[0057] During the regular feedback process, the cloud-based scheduling system binds the split planning data with the travel status feedback data to form quantitative travel status data for each device.

[0058] like Figure 1 As shown, in one embodiment of the present invention, step 300 includes:

[0059] Step 310: The cloud scheduling system calculates the set of devices that enter the intersection range of each path after the buffer period.

[0060] Each device set means that there is a high probability that a number of device ends exist within a certain range of a certain time range to form a road competition. According to the setting of the probability threshold, the urgency of the existence of road competition can be adjusted, and then the demand for cloud computing power can be adjusted, and then the data link bandwidth and computing power demand between device ends can be adjusted.

[0061] Step 320: The cloud scheduling system forms the associated data shared by the related devices according to the device set and sends it to the related devices in batches.

[0062] The cloud-based scheduling system can utilize point-to-multipoint or broadcast communication technology mechanisms to generate related data and send it to related devices in batches.

[0063] like Figure 1 As shown, in one embodiment of the present invention, step 400 includes:

[0064] Step 410: The relevant device establishes a communication link according to the associated data.

[0065] The communication technology configuration of the device end is consistent. Each related device end forms a link establishment parameter based on the common association data to complete the communication link establishment.

[0066] Step 420: Determine the decision-making device end among the relevant device ends through a priority comparison rule.

[0067] The priority comparison rules may include the priority of the transport task, the order in which the equipment ends enter the path intersection range, the distance between the equipment ends and the path intersection range, etc.

[0068] Step 430: The decision-making device forms a speed-up control parameter of the decision-making device and a speed-down control parameter of other related devices according to the avoidance rule.

[0069] The avoidance rules form temporary speed differences. For example, if the decision-making device speeds up to leave the path intersection range as soon as possible, other related devices will speed up to avoid obstacles and leave the path intersection range. The speed-up control parameters and speed-down control parameters ensure that the related devices are in a stable driving state and do not start or stop.

[0070] Step 440: After the decision-making device and other related device ends leave the path intersection range, the communication link is released according to the recovery rule, the travel speed is restored, and the travel status feedback is performed.

[0071] The recovery rule forms a control process for returning to normal travel status after leaving the path intersection range. Ensure that the state changes on the relevant device side have the ability to recover and avoid excessive consumption of cloud computing power.

[0072] A strong vehicle-side dispatching system for planar warehousing according to an embodiment of the present invention includes:

[0073] A memory, used to store program code of the processing process of the strong vehicle-side scheduling method for plane warehousing in the above embodiment;

[0074] A processor is used to execute the program code of the processing process of the strong vehicle-side scheduling method for flat warehousing in the above-mentioned embodiment.

[0075] The processor may be a DSP (Digital Signal Processor) digital signal processor, an FPGA (Field-Programmable Gate Array) field programmable gate array, an MCU (Microcontroller Unit) system board, a SoC (system on a chip) system board, or a PLC (Programmable Logic Controller) minimum system including I / O.

[0076] A strong vehicle-side dispatching system for plane storage according to an embodiment of the present invention is as follows Figure 2 As shown. Figure 2 In this embodiment, the present invention includes:

[0077] The task splitting device 10 is used to split and plan the transport task through the cloud scheduling system, and the splitting planning data at least includes the number of equipment terminals, the initial state of the equipment terminals, and the driving path of the equipment terminals;

[0078] The driving feedback device 20 is used for receiving the corresponding split planning data on the device side to establish the driving process and regularly feedback the driving status to the cloud scheduling system;

[0079] The trend prediction device 30 is used for the cloud scheduling system to predict the device terminals that will appear in the path intersection range in the subsequent period according to the travel status of each device terminal, and send the associated data to the relevant device terminals according to the prediction result, and the associated data at least includes the identification information of the relevant device terminals;

[0080] The on-site adjustment device 40 is used for the device end to establish a communication link between the device ends according to the associated data, and adjust the driving status of the relevant device ends according to the preset decision rules.

[0081] like Figure 2 As shown, in one embodiment of the present invention, the task splitting device 10 includes:

[0082] The task splitting module 11 is used by the cloud scheduling system to split the transport task to adapt the number of equipment terminals, and configure the identification and initial driving state of each equipment terminal;

[0083] The path planning module 12 is used in the cloud scheduling system to plan the device-side driving path according to the loading position of the device-side and the target position of the transport task using the A* search algorithm to form the driving path data.

[0084] like Figure 2 As shown, in one embodiment of the present invention, the driving feedback device 20 includes:

[0085] The driving establishment module 21 is used for each device end to automatically follow the driving path and perform automatic navigation at a specified speed according to the split planning data according to the task instruction to form a transfer driving process;

[0086] The status feedback module 22 is used for each device to regularly feedback the travel status including travel speed and position to the cloud scheduling system during the transfer process.

[0087] like Figure 2 As shown, in one embodiment of the present invention, the trend prediction device 30 includes:

[0088] The device identification module 31 is used by the cloud scheduling system to calculate the set of device terminals that enter the intersection range of each path after the buffer period;

[0089] The information sharing module 32 is used for the cloud scheduling system to form related data shared by related device terminals according to the device terminal set and send it to the related device terminals in batches.

[0090] like Figure 2 As shown, in one embodiment of the present invention, the field adjustment device 40 includes:

[0091] A communication establishing module 41 is used for the relevant device end to establish a communication link according to the associated data;

[0092] A device selection module 42, used to determine a decision device end among related device ends through a priority comparison rule;

[0093] The speed scheduling module 43 is used for the decision-making device to form a speed-up control parameter of the decision-making device and a speed-down control parameter of other related devices according to the avoidance rule;

[0094] The travel recovery module 44 is used to release the communication link according to the recovery rule, restore the travel speed, and provide travel status feedback after the decision-making device end and other related device ends leave the path intersection range.

[0095] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A strong vehicle-side dispatching method for plane warehousing, characterized in that: include: The transport task is split and planned through the cloud scheduling system, and the split planning data includes at least the number of equipment terminals, the initial status of the equipment terminals, and the driving path of the equipment terminals; The device receives the corresponding split planning data to establish the driving process and regularly feeds back the driving status to the cloud scheduling system; The cloud dispatching system predicts the device terminals that will appear in the path intersection range in the subsequent period according to the travel status of each device terminal, and sends the associated data to the relevant device terminals according to the prediction result, and the associated data at least includes the identification information of the relevant device terminals; The device side establishes a communication link between the device sides according to the associated data, and adjusts the driving status of the relevant device sides according to the preset decision rules.

2. The method for strong vehicle-side dispatching of planar warehousing according to claim 1, characterized in that: The splitting plan of the transport mission includes: The cloud dispatching system splits the transport task to match the number of devices and configures the identification and initial driving status of each device. The cloud-based dispatching system uses the A* search algorithm to plan the device-side driving path according to the loading position of the device and the target position of the transport task to form driving path data.

3. The method for strong vehicle end dispatching of plane storage as claimed in claim 1, characterized in that: The process of establishing the driving includes: Each device automatically follows the driving path and performs automatic navigation at the specified speed according to the task instructions and split planning data, forming a transfer driving process; The feedback progress status includes: During the transfer process, each device regularly feeds back the travel status including travel speed and location to the cloud scheduling system.

4. The method for strong vehicle end dispatching of plane storage as claimed in claim 1, characterized in that: The device terminals predicted to appear in the path intersection range in the subsequent period include: The cloud scheduling system calculates the set of devices that enter the intersection range of each path after the buffer period; The sending of the associated data to the relevant device end according to the prediction result includes: The cloud scheduling system forms related data shared by related devices based on the device collection and sends it to related devices in batches.

5. The method for strong vehicle-side dispatching of planar warehousing according to claim 1, characterized in that: The step of adjusting the driving state of the relevant device terminal according to the preset decision rule includes: The relevant device side establishes a communication link based on the associated data; Determine the decision-making device end among the relevant device ends through a priority comparison rule; The decision-making device forms a speed-up control parameter of the decision-making device and a speed-down control parameter of other related devices according to the avoidance rule; After the decision-making device and other related devices leave the path intersection range, the communication link is released according to the recovery rules, the travel speed is restored, and the travel status feedback is performed.

6. A strong vehicle-side dispatching system for flat warehousing, characterized in that: include: A memory, used to store a program code for a processing process of a method for maneuvering a vehicle end for planar warehousing as claimed in any one of claims 1 to 5; A processor is used to execute the program code.

7. A strong vehicle-side dispatching system for flat warehousing, characterized in that: include: A task splitting device, used to split and plan the transport task through the cloud scheduling system, where the splitting planning data at least includes the number of equipment terminals, the initial state of the equipment terminals, and the driving path of the equipment terminals; Driving feedback device, used for receiving the corresponding split planning data on the device side to establish the driving process, and regularly feeding back the driving status to the cloud scheduling system; A trend prediction device is used for the cloud scheduling system to predict the device terminals that will appear in the path intersection range in the subsequent period according to the travel status of each device terminal, and send related data to the relevant device terminals according to the prediction result, and the related data at least includes the identification information of the relevant device terminals; The on-site adjustment device is used for the device end to establish a communication link between device ends according to the associated data, and adjust the driving status of the relevant device end according to the preset decision rules.

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