CN-122022395-A - AGV group control dispatching optimization method based on multi-mode distribution instruction fusion

CN122022395ACN 122022395 ACN122022395 ACN 122022395ACN-122022395-A

Abstract

The invention discloses an AGV group control dispatching optimization method based on multi-mode dispatching instruction fusion, and relates to the technical field of AGV group control dispatching. The method provides a unified data base by generating a standardized digital mapping ledger, generates a to-be-processed instruction set by multi-mode distribution instruction set and state feedback data and performing source marking, time stamp calibration and validity verification, ensures the validity of instructions, obtains an executable task queue by analyzing and checking the to-be-processed instruction set, calibrating priority and converting task elements, ensures the compliance and the order of tasks, realizes the matching of tasks and AGV resources and the cooperative management and control of cluster traffic by generating a task execution list and a cluster traffic control time sequence list, and ensures the safety, the timeliness and the scheduling flexibility of task execution by issuing the task execution instruction and path parameters, executing collision avoidance management and task progress monitoring and supporting new high priority instruction triggering executable task queue updating.

Inventors

ZHANG ZHONGJUN
KANG HAIJUN
YAN JIE
AN SIYU
LIAN PENG
XUE XIAOMENG

Assignees

陕西通汇汽车物流有限公司

Dates

Publication Date: 20260512
Application Date: 20260410

Claims (10)

1. The AGV group control scheduling optimization method based on the multi-mode distribution instruction fusion is characterized by comprising the following steps of: performing basic information pre-configuration and initial state acquisition to generate a standardized digital mapping ledger; Collecting a multi-mode distribution instruction set and state feedback data, and marking a data source and calibrating a time stamp by combining a standardized digital mapping ledger to generate an instruction set to be processed; Performing instruction analysis and verification on an instruction set to be processed, and performing priority calibration and task element conversion to obtain an executable task queue; based on the standardized digital mapping ledger and the state feedback data, generating a task execution list and cluster traffic control time schedule of a single AGV by combining an executable task queue; Issuing a task execution instruction and path parameters based on a task execution list and a cluster traffic control time sequence list, executing collision avoidance management and task progress monitoring, and triggering executable task queue updating if a new high-priority instruction is acquired; and receiving task completion information reported by the target AGV, and updating the standardized digital mapping ledger.
2. The method for optimizing group control scheduling of an AGV based on multi-modal distribution instruction fusion according to claim 1, wherein the process of performing basic information pre-configuration and initial state collection to generate a standardized digital mapping ledger is as follows: The method comprises the steps of performing basic information pre-configuration on material and station basic information, AGV equipment basic parameters, path and navigation basic information, supporting facility basic information and production beat management and control parameters to obtain full-element basic information; setting up a wireless local area network through a wireless AP, and acquiring the following initial state data to obtain initial state data: all AGVs are in initial positions, working states, battery electric quantity, voltage information, online communication states and fault alarm states; the button box and the PAD panel are in an online communication state and an instruction triggering initial state; the method comprises the following steps of (1) initial working state and signal state of a traffic light, initial working state and occupied state of a charging station, and initial working state of a control cabinet and a matched power supply system; The initial empty state of the loading level and the line side loading level corresponding to all the front plate springs, the front axle and the middle and rear axles, the initial position and the in-place state of all the carriers, and the initial working state of the carrier positioning mechanism; and carrying out point location level one-to-one correspondence on the full-element basic information and the initial state data, and carrying out classification structural storage according to the material and station dimension, the AGV equipment dimension, the path navigation dimension, the supporting facility dimension, the production management and control dimension and the safety management and control dimension to generate the standardized digital mapping ledger.
3. The method for optimizing group control scheduling of an AGV based on multi-modal distribution instruction fusion according to claim 1, wherein the process of generating the set of instructions to be processed by combining the standardized digital mapping ledger to perform data source marking and time stamp calibration is as follows: Carrying out data source matching marking on each distribution instruction in the multi-mode distribution instruction set and pre-configuration information of material and station dimensions, supporting facility dimensions and production control dimensions in the standardized digital mapping ledger in sequence; After the data source is matched and marked, performing time stamp calibration at the acquisition time to obtain a packaged instruction; and checking the packaged instruction based on the checking rules, and deleting the packaged instruction which does not meet any checking rule to obtain an instruction set to be processed.
4. The multi-modal delivery order fusion-based AGV group control schedule optimization method as set forth in claim 3, wherein the verification rule includes: Checking whether the data source mark of the packaged instruction is in the pre-configuration range of the standardized digital mapping ledger; checking whether the associated station corresponding to the packaged instruction exists or not; and carrying out the following verification on the material calling instruction, the material loading confirmation instruction and the production and distribution planning instruction in the packaged instruction: checking whether line edge material positions corresponding to the material calling instruction meet the preset vacancy requirement, checking whether loading positions corresponding to the material loading confirmation instruction are in place or not, and checking whether the production distribution planning instruction meets the production line beat management and control parameters or not.
5. The multi-mode delivery instruction fusion-based AGV group control scheduling optimization method according to claim 1, wherein the process of performing instruction analysis and verification on the instruction set to be processed is as follows: carrying out structural analysis on each execution in the instruction set to be processed to obtain a structural analysis data packet corresponding to a single instruction; performing dimension compliance verification and multidimensional conflict verification on the structured analysis data packet, and reserving valid instruction analysis data packet passing verification, wherein: The dimension compliance verification comprises verifying whether the corresponding material type and station number are in the pre-configuration range of the standardized digital mapping ledger, verifying whether the corresponding distribution requirement meets the maximum production takt of a production line pre-configured in the standardized digital mapping ledger and the requirement of a single-turn time-consuming management and control threshold value of the corresponding material; for a material calling instruction, checking whether the corresponding line edge material position accords with an operation rule of reserving at least 1 empty position in the production process; for checking the feeding confirmation instructions, checking whether the corresponding feeding positions have the full-material carriers with the prepared materials or not; the multi-dimensional conflict verification comprises the steps of verifying whether simultaneous operation conflicts of the same loading bit and the same line edge bit exist in the instructions corresponding to the structured analysis data packets; checking whether the commands corresponding to the structured analysis data packets have simultaneous passing conflicts for the same section of magnetic stripe navigation path and the same intersection traffic control area; And checking whether the load conflict exists between the instruction task requirement corresponding to the structured analysis data packet and the available resources of the current AGV cluster.
6. The method for optimizing group control scheduling of an AGV based on multi-modal distribution instruction fusion according to claim 5, wherein the process of performing priority calibration and task element conversion to obtain an executable task queue is as follows: performing priority matching on the instruction corresponding to the effective instruction analysis data packet according to a set priority matching rule to obtain an effective instruction data packet with a priority mark, wherein the set priority matching rule is as follows: the first priority is a material calling instruction affecting the production line for 4.8 minutes per production beat; the second priority is a production distribution planning instruction triggered by the completion of the feeding; The third priority is an empty carrier recovery instruction triggered by a line edge; The fourth priority is an autonomous charging instruction triggered by the AGV with low electric quantity; performing standardized conversion on the valid instruction data packet with the priority mark to generate an executable task queue, wherein the standardized conversion process is as follows: Matching the corresponding material types, the upper material level numbers and the lower material level numbers with magnetic stripe navigation paths and RFID landmark point location information preconfigured in path navigation dimensions in a standardized digital mapping ledger to generate task path nodes; matching a corresponding material single-turn time-consuming control threshold value preconfigured in a production control dimension in a standardized digital mapping ledger, and generating a task time-consuming control requirement; the method comprises the steps of matching equipment action parameters of AGV equipment dimension pre-configuration in a standardized digital mapping ledger, and determining action sequences of lifting carriers, path driving, line edge discharging, empty carrier lifting recovery and empty device returning, which are required to be executed by the AGV; and matching a security management and control rule pre-configured in a security management and control dimension in the standardized digital mapping ledger, and generating a security management and control requirement in task execution.
7. The method for optimizing group control scheduling of an AGV based on multi-modal distribution instruction fusion according to claim 1, wherein the process of generating the task execution list and the group control schedule of a single AGV by combining the executable task queue based on standardized digital mapping ledgers and state feedback data is as follows: screening AGVs which are in an online idle state, have battery power meeting the power consumption requirement of a single round of round trip of corresponding materials and have rated load 3500kg meeting the task load requirement; Carrying out state comprehensive evaluation on the selected candidate AGVs, and calculating the AGV state comprehensive evaluation score; Selecting AGVs with highest AGV state comprehensive evaluation score, shortest magnetic stripe navigation path distance from the starting loading position of the task and less than 2 accumulated tasks to be executed as target execution AGVs, and establishing a binding relation with task units in an executable task queue to generate a task package to be executed of a single AGV; aiming at each single AGV to-be-executed task package for completing task binding, generating a task execution list corresponding to the target execution AGV by combining the pre-configuration information of the standardized digital mapping ledger; Based on the task execution list, the cluster traffic control time sequence list is generated by combining the pre-configuration information of the path navigation dimension, the supporting facility dimension and the safety control dimension in the standardized digital mapping ledger.
8. The method for optimizing group control scheduling of AGVs based on multi-mode delivery instruction fusion according to claim 7, wherein the group traffic control time schedule comprises a number of each intersection, a traffic light number corresponding to control, an AGV number and a task priority passing through the intersection, a time interval of each AGV passing through the intersection, a triggering condition and time sequence of traffic light signal switching, a driving sequence and a safety interval control requirement of a plurality of AGVs in the same path section, and an exclusive control rule of intersection passing authority.
9. The method for optimizing group control scheduling of an AGV based on multi-mode delivery instruction fusion according to claim 1, wherein the task execution instruction and path parameter are issued based on a task execution list and a group delivery management timing schedule, and the processes of performing collision avoidance management and task progress monitoring are as follows: Issuing corresponding task execution lists and matched path parameters to each target execution AGV through a wireless local area network built by a wireless AP, and issuing coordinated control parameters in a cluster traffic control time sequence table to traffic lights; receiving the real-time position reported by the AGV, and if an obstacle is detected, adjusting the speed of the AGV; and if the real-time execution time of the AGV approaches to the single-turn time consumption control threshold, issuing a speed optimization instruction to the AGV.
10. The multi-modal delivery instruction fusion-based AGV group control dispatch optimization method of claim 1 wherein the process of triggering an update of an executable task queue upon acquisition of a new high priority instruction is: marking data sources and time stamps of a newly acquired multi-mode distribution instruction set, and determining the priority of a new instruction; Comparing the priority of the new instruction with the priority of the unexecuted task in the current executable task queue, and triggering the executable task queue to update if the new instruction is the first priority.

Description

AGV group control dispatching optimization method based on multi-mode distribution instruction fusion Technical Field The invention relates to the technical field of AGV group control scheduling, in particular to an AGV group control scheduling optimization method based on multi-mode distribution instruction fusion. Background In an unmanned distribution scene of a large material AGV in an automobile production workshop, the prior art has the following defects that firstly, a unified source marking, time stamp calibration and standardized verification system is not established in the prior art, and the traceability of instruction sources is poor. Then, in the prior art, AGV single task allocation and cluster traffic control are split into two independent links, and the cooperative linkage of task matching, path planning and traffic time sequence control is not realized based on unified field full-element data standard, so that the cooperative performance of task allocation and traffic control is extremely poor. Moreover, in the prior art, batch instruction processing and task scheduling modes are adopted, and scheduling strategies cannot be synchronously adjusted based on the real-time running state of the AGV, the real-time working condition of the station and the real-time state of the field facility. Finally, most of task queue generation and scheduling execution in the prior art are in a static curing mode, and when an emergency material calling demand occurs on a production line, risks of production line material breakage and production beat interruption are prone to occurring. Therefore, there is a need for an AGV group control scheduling optimization method based on multi-mode distribution instruction fusion, which can realize multi-mode distribution instruction standardization fusion, task distribution and traffic control cooperative linkage, full-flow real-time scheduling response and high-priority instruction dynamic adaptation Disclosure of Invention Aiming at the defects of the prior art, the invention provides an AGV group control dispatching optimization method based on multi-mode dispatching instruction fusion, which solves the problems that the multi-mode dispatching instruction fusion is not standard, the task allocation and the traffic control coordination are poor, the dispatching response is not timely, and the high-priority instruction cannot be dynamically adapted in the AGV group control dispatching in the prior art. The AGV group control dispatching optimization method based on the multi-mode distribution instruction fusion comprises the following steps: performing basic information pre-configuration and initial state acquisition to generate a standardized digital mapping ledger; Collecting a multi-mode distribution instruction set and state feedback data, and marking a data source and calibrating a time stamp by combining a standardized digital mapping ledger to generate an instruction set to be processed; Performing instruction analysis and verification on an instruction set to be processed, and performing priority calibration and task element conversion to obtain an executable task queue; based on the standardized digital mapping ledger and the state feedback data, generating a task execution list and cluster traffic control time schedule of a single AGV by combining an executable task queue; Issuing a task execution instruction and path parameters based on a task execution list and a cluster traffic control time sequence list, executing collision avoidance management and task progress monitoring, and triggering executable task queue updating if a new high-priority instruction is acquired; and receiving task completion information reported by the target AGV, and updating the standardized digital mapping ledger. The invention has the following beneficial effects: The method comprises the steps of pre-configuring basic information and collecting initial states, generating a standardized digital mapping account, providing a unified data base, avoiding scheduling deviation caused by information confusion, generating a to-be-processed instruction set by collecting a multi-mode distribution instruction set and state feedback data, marking a source, marking a time stamp and checking validity, ensuring traceability and validity of the instruction, reducing interference of invalid instructions on scheduling, analyzing the to-be-processed instruction set, checking, marking priority and converting task elements to obtain an executable task queue, guaranteeing compliance and order of tasks, determining task priority, generating a single AGV task execution list and a cluster traffic control time sequence table by combining the standardized digital mapping account, state feedback data and the executable task queue, realizing matching of task and resources and collaborative management and control of cluster traffic, and finally realizing standardization and high efficiency of group control sched