CN112000113A

CN112000113A - Multi-AGV storage management system and method based on traditional Chinese medicine pharmacy

Info

Publication number: CN112000113A
Application number: CN202010568909.2A
Authority: CN
Inventors: 郭靖翊; 何新; 李宋顺; 乔心路; 王阳; 张钊浩
Original assignee: Jiangsu Huiyucheng Intelligent Equipment Research Institute Co ltd; Nanjing Rongxin Intelligent Technology Co ltd; Nanjing University of Science and Technology
Current assignee: Jiangsu Huiyucheng Intelligent Equipment Research Institute Co ltd; Nanjing Rongxin Intelligent Technology Co ltd; Nanjing University of Science and Technology
Priority date: 2020-06-19
Filing date: 2020-06-19
Publication date: 2020-11-27

Abstract

The invention discloses a multi-AGV storage management system and method based on a traditional Chinese medicine pharmacy, and particularly relates to the technical field of AGV storage. The invention adopts an improved two-section type multi-AGV path planning control strategy based on a time window, combines the time window principle with an improved A algorithm, plans paths of the multi-AGV in an off-line state, plans reasonable task starting time according to different task priorities, reduces and avoids conflict, analyzes and improves the condition with larger data scale, solves the problem of dynamic conflict possibly existing in on-line process by adopting a priority traffic rule method and a geometric path composite adjustment strategy, and can improve scheduling indexes.

Description

Multi-AGV storage management system and method based on traditional Chinese medicine pharmacy

Technical Field

The invention relates to the technical field of AGV storage, in particular to a multi-AGV storage management system and method based on a traditional Chinese medicine pharmacy.

Background

At present, with the development of medical informatization, more and more automatic devices are connected into a hospital information system, so that medical services are more standard and efficient. The intelligent pharmacy combines the advantages of automation equipment and computer technology in the fields of data analysis, processing and the like, can effectively improve the working efficiency of pharmacy staff, shortens the medicine taking time of patients, and strengthens the information management of hospitals. The storage management of the pharmacy is an important link of an intelligent pharmacy, and the storage management of the pharmacy is mainly used for storing medicines and managing medicine information so as to improve the overall efficiency of medical work. At present, the intelligent traditional Chinese medicine pharmacy replaces manual medicine taking by processing traditional Chinese medicine prescription information and combining automatic equipment, so that the problems of low accuracy rate, low speed and the like of manual medicine taking are solved, and the efficiency of medical service is improved. However, the storage link of the traditional Chinese medicine pharmacy still has the contradiction that the manual carrying efficiency is lower than the system requirement efficiency.

The AGV has the characteristics of low cost, high efficiency, no humanization, easy management and the like. If the AGV system is integrated with the storage system, the efficiency of storage management can be further improved by developing a multi-AGV storage management system, so that the traditional Chinese medicine pharmacy is more effectively standardized in the aspects of storage management, goods transportation, prescription treatment, data collection and the like.

The primary core of the multiple-AGV storage management system is scheduling, that is, a conflict-free and optimal scheduling index path is planned for multiple AGVs through a path planning algorithm according to a corresponding storage map model, and uncertain factors in actual operation such as failure of a trolley can be dealt with, so that the problems of path conflict, deadlock, dynamic failure and the like existing in path planning are urgently needed to be solved.

Disclosure of Invention

In order to overcome the above defects in the prior art, embodiments of the present invention provide a system and a method for multiple AGV warehouse management based on a traditional chinese medicine pharmacy, and the technical problem to be solved by the present invention is: the problems of path conflict, deadlock, dynamic fault and the like exist in path planning.

In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a many AGV storage management system based on well pharmacy, includes host computer management system, host computer management system communication is connected with a plurality of AGV dollies and guide rail route, AGV dolly sliding connection is used for standardizing the line of AGV in the guide rail route, host computer management system still is connected with a plurality of supplementary battery charging outfits.

In a preferred embodiment, the AGV trolley comprises a trolley body structure module, the top of the trolley body structure is fixedly provided with a positioning module, a control module, a communication module and an AGV management module, the AGV management module is in communication connection with an upper computer management system, and the bottom of the trolley body structure is fixedly connected with a driving module and a safety and power module.

In a preferred embodiment, the positioning module is an RFID module using electromagnetic guidance.

The invention also provides a multi-AGV storage management method based on the traditional Chinese medicine pharmacy, which comprises the following specific steps:

step 1: starting the multi-AGV storage management system of the upper computer, initializing the system, judging whether the running state of the system is normal or not, skipping to the step 3 when the system normally runs, otherwise, maintaining the system, and restarting the system after the repair is finished;

step 2: starting the AGV, checking the AGV, judging whether the AGV state is normal or not, if so, jumping to the step 4, and if not, restarting after maintenance;

and step 3: after the upper computer management system confirms that no errors exist, adding a carrying task according to the requirement, and waiting for the AGV to go online;

and 4, step 4: the AGV is in communication connection with an upper computer management system and feeds back current information to the upper computer;

and 5: the upper computer management system performs task route planning and distribution according to the map information, the AGV state information and the operation instruction; if no idle AGV exists in the current system, the task waits to be executed until a certain AGV is in an executable state

In a preferred embodiment, the routing assignment in step 5 includes the following steps:

step one, environment modeling, namely, adopting a topological modeling method, wherein in a directed connection network G (V, E), V represents a set of all nodes in a topological graph, E represents a set of all edges in the topological graph, each edge can be represented as an ordered element pair of two nodes, and a weight W (U, V) is associated;

step two, multiple AGV system scheduling research, establishing a relationship between system tasks and AGV trolleys through reasonable task allocation;

step three, a two-section multi-AGV path planning control strategy based on a time window, and an adopted improved two-section multi-AGV path planning control strategy based on the time window: under the offline condition, based on the time window principle, an improved A-x algorithm is applied to plan the optimal path of each AGV; and under the online condition, the running condition of each AGV is detected in real time, and corresponding processing is carried out according to different running states.

1. Compared with the traditional multi-AGV storage management system, the improved two-section multi-AGV path planning control strategy based on the time window is adopted, the time window principle and the improved A algorithm are combined, the multi-AGV is subjected to path planning in an off-line state, and reasonable task starting time is planned according to different task priorities, so that conflicts are reduced and avoided, analysis and improvement are performed on the condition of larger data scale, and a priority traffic rule method and a geometric path composite adjustment strategy are adopted to solve the problem of dynamic conflicts possibly existing on line, so that the scheduling index can be improved.

Drawings

FIG. 1 is a simplified model of a warehousing environment.

FIG. 2 is a block diagram of a modular AGV design.

Fig. 3 is a plan view of two four-wheel configurations.

FIG. 4 is a schematic diagram of an RFID-based AGV location.

Fig. 5 is an FB164 functional block.

FIG. 6 is a flow chart of S7-1200 reading data from an RFID reader.

Fig. 7 is a flow chart of S7-1200 writing data to an RFID data carrier.

FIG. 8 is a general block diagram of an AGV system based on RFID location technology.

FIG. 9 is a schematic diagram of the overall wiring for the AGV control system.

FIG. 10 is a flow chart of PLC program control for trolley operation.

Fig. 11 is a wiring diagram of a direct current PNP type normally open sensor.

FIG. 12 is a block diagram of a system for multiple AGV warehouse management.

FIG. 13 is a flowchart of the operation of a multiple AGV warehouse management system.

FIG. 14 is an electronic map of topology modeling.

FIG. 15 is a schematic diagram of AGV node collisions.

FIG. 16 is a diagrammatic illustration of an AGV pursuing a conflict.

FIG. 17 is a schematic diagram of AGV opposing collisions.

Figure 18 is a flow chart of a two-stage control strategy.

Fig. 19 is a schematic time window.

FIG. 20 is a Tent diagram.

Fig. 21 is a flow chart of a time window based path planning algorithm.

FIG. 22 is a flow chart of algorithm improvement based on time windows.

FIG. 23 is a flow chart of a multiple AGV dynamic conflict composite adjustment strategy.

Fig. 24 is a schematic diagram of the system architecture of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention provides a multi-AGV storage management system based on a traditional Chinese medicine pharmacy, which comprises an upper computer management system, wherein the upper computer management system is in communication connection with a plurality of AGV trolleys and a guide rail path, the AGV trolleys are connected in the guide rail path in a sliding mode to standardize the moving type of the AGV, and the upper computer management system is also connected with a plurality of auxiliary charging devices.

The AGV dolly includes the body construction module, body construction top fixed mounting has orientation module, control module, communication module and AGV management module, AGV management module is connected with upper computer management system communication, body construction bottom fixedly connected with drive module and safety and electric power module, orientation module is for having adopted the RFID module of electromagnetism guide mode.

The route rule distribution in the step 5 comprises the following steps:

As shown in fig. 1 and fig. 24, the embodiment specifically includes: compared with some current one-way single-channel driving modes, the driving road of the AGV is two-way and multi-channel, the design can effectively improve the transportation efficiency, the goods points are access points of warehouse goods, each goods point stores goods with single specifications, the management and statistics are convenient, the AGV library is an initial stop point of the AGV and provides functions of charging, overhauling and the like, the main content of the AGV module is to design the AGV with navigation capacity, so that the transportation task in the storage environment is completed, in the design process, the driving mode, the guiding mode, the obstacle avoidance mode and the like of the AGV are mainly considered, and the influence of actual environmental factors such as electromagnetic interference and the like can be responded.

As shown in fig. 2, the embodiment specifically includes: in consideration of the design efficiency of the AGV system and the convenience of later maintenance, the AGV system adopts a modular design idea and is divided into a vehicle body structure module, a positioning module, a control module, a driving module, a safety and power module, a communication module, an AGV management module of an upper computer and the like according to different functional requirements.

As shown in fig. 3, the embodiment specifically includes: the AGV is applied to the storage environment of a traditional Chinese medicine house, the requirement on the load capacity determines the mechanical strength requirement of a vehicle body material, the weight of goods in actual storage is considered, an aluminum alloy lean tube is selected as the vehicle body material, the AGV adopts a differential driving mode, an A-type structure consists of two driving wheels in the middle, a universal wheel and a directional wheel, the A-type structure has higher flexibility, but the A-type structure is easy to shake in the transportation process to cause goods omission, a B-type structure consists of two directional wheels and two driving wheels, although the storage is general, the stress of the A-type structure is more uniform, the operation is more stable, the actual requirement is combined, and a B-type four-wheel structure design scheme is adopted.

As shown in fig. 4-7, the embodiment is as follows: in order to meet the transportation requirements under different conditions, the traveling route of the AGV is in a two-way and multi-channel mode, positioning modes such as optical guidance and laser guidance are adopted, meanwhile, the cost problem is considered, the RFID technology of the electromagnetic guidance mode is adopted as the positioning mode of the AGV, an electronic tag with a fixed number is placed on a guide rail path of the AGV, a reader-writer arranged on the AGV is utilized to identify and determine the position of the AGV, an RFID reader is arranged below the AGV trolley, an RFID landmark with a site code is arranged at a rail node on a material conveying route, a control center issues an instruction (a feeding route) to a controller after the material is placed on the AGV trolley, the feeding trolley is controlled to start and start to convey the material according to the instruction after the instruction is received, the RFID reader identifies the position information stored in the RFID landmark and feeds back to a PLC control system module, the method comprises the steps of controlling an AGV to stop according to a route selection station, enabling the AGV to carry out material conveying of the next station according to instructions after the materials are conveyed to the station, waiting for execution of the next task after all feeding instructions are completed, selecting an RF260R ultra-high frequency RFID reader-writer, wherein STMATIC RF260R is a compact low-cost reading-writing device, can effectively bear identification tasks in an HF range (13.56MHz and ISO15693), is suitable for being used in a small assembly line or an internal logistics system in industrial production, connecting an S7-1200PLC and an RS232 module with the RF260R reader-writer through an RS232 cable, and then utilizing an S7-1200 special software library to realize read-write communication between an RF260R data carrier and an MDSDXX data carrier, wherein the communication protocol is a 3964R protocol, control characters and RFID messages in a data sending and receiving process are defined, and an odd check mode is used for response messages, and is shown in Table 1.

Table 13946R protocol messaging

In the process of realizing communication between the S7-1200PLC and the RFID, the FB164 function block of the software library of 'RFID _ serial' is mainly used, wherein the parameter group config is responsible for parameter configuration of the communication between the S7-1200PLC and the RF260R, the parameter group reset is responsible for resetting the RFID reader-writer, the parameter group read is responsible for reading data from the data carrier, and the parameter group write is responsible for writing data on the data carrier. The invention sets the parameters of the RS232 module as follows: 115200bit/s transmission rate, 8 bits of data bits, odd parity, 1 bit stop bit.

Data information is stored in the data carrier, and the data information is subjected to custom coding according to the requirements of the warehousing system, as shown in table 2, wherein the station types take three values: 0000 denotes a cargo spot, 0001 denotes an intersection, 0002 denotes an auxiliary spot, and the cargo spot stores article information (cargo ID).

TABLE 2 warehousing site information custom coding

Data are read from the data carriers using read messages, the command being stored in the RFID reader, and the command being executed when a data carrier enters the identification area of the reader. The "_ address" and "_ length" in the parameter set read determine the data storage area to be read from the data carrier. If the acknowledgement of the read message is accepted, the required user data is unpacked and stored in the global data block "rfid _ serial _ read _ X" to facilitate the subsequent data processing.

Writing data from the S7-1200PLC into the storage area of the data carrier using a write message, which command is also stored in the RFID reader, the write command of the data can arrive in the data carrier immediately or within a certain time when a data carrier enters the area of the reader. Before a write command is sent, data is firstly sent to a global data block 'RFID _ serial _ write _ X', parameters 'address' and 'length' determine a storage area to which a data carrier needs to be written, the byte size of the invention is set to 16, and after a write message is received, an RFID reader-writer returns confirmation information to an RS232 communication module.

As shown in fig. 8 to 11, the embodiment is specifically as follows: the PLC controller has the advantages of no hardware development, flexible structure, difficult influence from external environment, high transmission quality, high speed, stable system, lower cost, high reliability, short development period and the like, the system is widely applied in the field of automation, integrates the advantages of the RFID technology and the PLC technology, combines the PLC with the RFID technology, is applied in the field of AGV navigation positioning of a storage system, improves the automation level of production and management, has the structure of the system, is mainly composed of a controller, a sensor, a motor driver, a power supply, an alarm and the like, the RFID reader-writer is arranged at the bottom of the trolley for reading information to realize the positioning of the AGV, the core of the information processing part is a PLC, the PLC processes the information detected by the RFID reader-writer according to a program and then outputs the processed information to control the advance, the steering, the alarming and the like of the trolley, and the controller of the system uses a Siemens S7-1200 PLC. The trolley adopts a four-wheel structure and is driven by two stepping motors, and each motor is controlled independently. In addition, the AGV is equipped with a "red-yellow-green" warning light with a buzzer to alarm in case of a fault.

The connection relationship between the input signal and the output signal of the system and the PLC is shown in Table 3.

TABLE 3 PLC input/output Allocation Table

The invention uses FL57BYG804022 type two-phase stepping motor to control the turning direction and speed of the trolley, the normal running of the stepping motor needs to be driven by a driver, and the driver is a device which can convert the pulse signal sent by the control system into the angular displacement of the stepping motor. The invention selects SH-20806D type two-phase stepping motor subdivision driver to control the stepping motor, in the case of rated operation, the position and the rotation speed at which the stepping motor is stopped depend only on the number and the frequency of pulses of the pulse signal, are not affected by load variations, therefore, the invention regulates the speed of the stepping motor through a PWM instruction in the PLC, uses a high-speed pulse output instruction (PLS) to respectively generate PTO high-speed pulse string waveforms at addresses of Q0.0 and Q0.1, uses a multi-segment line working mode of the PTO to control the stepping motor in consideration of three links of acceleration, constant speed and deceleration in actual operation, adopts an E3F type photoelectric signal obstacle avoidance sensor, is a PNP type normally open sensor, has an effective distance of 70cm, and provides working voltage for other modules of the AGV system by a power supply module, and the power supply of the AGV system is provided by lead-acid batteries of 48V and 60 Ah. The motor and driver obtain 48V directly from the battery, and the sensor, CPU and RF260R module obtain 24V by voltage division, depending on the voltage requirements of the various modules.

As shown in fig. 12 to 13, the embodiment is specifically as follows: through the demand analysis to many AGV storage management system, system constitution according to the design, to many AGV storage management system's software structure on different aspect, the function is realized, data logic etc. carry out the analysis, many AGV storage management system's constitution can divide into the expression layer, the business layer, the data layer, the supporting layer, the expression layer is many AGV storage management system's human-computer interaction part, be used for each item data in the display system and accept the data of user's input, provide convenient operation interface for the user, convenience of customers is to the management of system, the business layer is entire system's core part, be located between expression layer and the data layer, play the effect of starting and stepping down to data exchange. The layer mainly realizes the service logic of the system, and completes the management function, the path planning function, the monitoring function, the safety verification function and the like through various data of the data layer and user instructions of the presentation layer, the data layer is abstract information flow and is mainly responsible for accessing various information of a database and providing data support for the service layer and the presentation layer, and the support layer is an entity part in the system and comprises an upper computer, an AGV trolley, an RFID label and the like. The supporting layer provides real-time data information for the data layer and receives various operating instructions issued by a user to complete a transportation task, and the multi-AGV storage management system provided by the invention mainly realizes the following functions: the management function, the path planning function, the monitoring function and the safety verification function start the multi-AGV storage management system of the upper computer, the system initialization is carried out, whether the system running state is normal or not is judged, and the normal running of the system jumps to the step 3; otherwise, performing system maintenance, restarting the system after the repair is completed, starting the AGV, performing vehicle inspection, judging whether the AGV state is normal or not, and if so, jumping to the step 4; if the system is abnormal, the system is restarted after maintenance, after the upper computer management system confirms that the system is correct, a carrying task is added according to the requirement, the AGV is waited to come on line, the AGV is in communication connection with the upper computer management system and feeds back the current self information to the upper computer, and the upper computer management system performs task distribution according to map information, AGV state information and an operation instruction; if no idle AGV exists in the current system, the task waits to be executed until a certain AGV is in an executable state.

As shown in fig. 14, the embodiment specifically includes: the invention discloses a multi-AGV storage management system, which is mainly characterized in that scheduling is carried out, namely paths with conflict-free and optimal scheduling indexes are planned for a plurality of AGVs through a path planning algorithm aiming at a corresponding storage map model, uncertain factors such as faults of trolleys and the like in actual operation can be responded, in order to complete task allocation and path planning of the AGV in the storage system, environment modeling is firstly carried out, an electronic map is designed according to a Chinese pharmacy storage environment model, and some ideal hypothesis simulation actual storage environments are provided.

According to the AGV positioning technology based on the RFID and the bidirectional and multichannel AGV road environment, the invention is researched for an AGV system adopting a fixed guiding mode, and is a bidirectional path guiding system.

Wherein, "1" to "36" represent intersections or cargo spots, mainly store RFID tag information and the like at the intersections or the cargo spots, and mainly include: # (ID, roadId), ID is a station number, roadId is a road connected by the intersection or the freight point according to the sequence of "north up-east right-east down-south-west left", if not, the road is marked as-1 "," 101 "to" 130 "and" 201 "to" 230 ", road information is stored, the road information mainly comprises # (ID, length, speed, from, to, isdiplex), ID is a road ID, length is a road length, speed is a maximum speed limited by the road, the channel indicates the number of lanes of the road in one direction, from and to are intersections or freight points connected by the road, isdiplex indicates whether the road is two-way or not, a topological graph is established for a storage environment, station information, path information and the like are stored, and a foundation is provided for subsequent multiple AGV path planning research, in addition, the following points are assumed when the model is established: that is, each AGV only executes one task at a time; all tasks meet the strong constraints of the loading capacity and the like of each AGV; all AGVs in the system are in a good state without considering the charging and random faults of the AGVs; ignoring the time between the AGV exiting the garage and the arrival at the road; the overtaking lane change is not allowed, namely once the AGV enters a certain lane, the AGV must drive from the starting point of the road to the end point of the road in the lane, the lane change is not allowed in the middle, and the overtaking is not allowed.

As shown in fig. 15 to 22, the embodiment specifically is: the scheduling problem of the multiple AGV system is that under a certain constraint condition, a system task is linked with an AGV through reasonable task allocation, the scheduling index of the system is met, and a transportation task is completed. However, in an actual multi-AGV operating environment, there are influences of factors such as road conflicts, vehicle faults, task delays or temporary changes, and a certain AGV or a part of AGVs cannot continue to execute tasks, so that offline task scheduling has certain limitations.

On-line task scheduling means that a reasonable solution is adopted to plan paths of multiple AGVs through real-time monitoring of the system so as to deal with various uncertain factors in actual conditions. One scheme is that after a new task is generated or after an AGV finishes a task, the information of the whole system is updated, and the scheme sacrifices certain efficiency but can ensure the real-time performance of the system; the other scheme is to select a fixed time interval to perform rolling update on the information of the system, which can improve the overall efficiency of the system to a certain extent, but as the time interval increases, the real-time performance of the system becomes worse, and the problems of road conflict and the like generated in the time interval need to be solved, thereby reducing the efficiency of the system.

In a multi-AGV system, the overall performance of the system is generally evaluated by using a scheduling index, and the better the scheduling index is, the higher the overall efficiency of the system is. Currently there are two main types of scheduling indicators: a single type scheduling index and a composite type scheduling index. The single type scheduling index uses a unique index or standard to perform scheduling evaluation on the multiple AGV systems, and the single type scheduling index mainly represents the following steps: maximum-outbound queue-size (MOQS) based on workload, shortest-travel-distance-first (STDF) based on workload, shortest task latency, and the like. The composite type scheduling index performs scheduling evaluation on the multiple AGV systems by setting weights for multiple indexes or standards.

In order to better evaluate the performance of a multi-AGV path planning control strategy, the invention comprehensively considers factors such as AGV priority, AGV driving speed, actual departure time of the AGV, start and stop point distribution of the AGV and the like, and provides a composite scheduling index based on scheduling time, which is respectively system scheduling time T_endAnd total system scheduling time SumT_endAre respectively shown as a formula (5-1) and a formula (5-2).

T_end＝γ₁*T_pri+T (5-1)

SumT_end＝γ₂*SumT_pri+SumT (5-2)

In the formula, T_priThe difference between the time when the last AGV with the first priority reaches the target point and the time when the first AGV actually starts; t is the difference between the time when the last AGV reaches the target point and the system scheduling starting time, namely the system scheduling time; SumT_priThe sum of the differences between the arrival time of all the AGVs with the first priority and the actual departure time is the target point; SumT is the sum of the difference between the time when all vehicles arrive at the target point and the actual departure time; the expression of gamma is shown as the formula (5-3), and the gamma adopted by the invention₁Respectively is gamma_a＝0.1，γ_b＝0.25，γ_c＝0.25，γ_d＝0.4；γ₂Respectively is gamma_a＝0.8，γ_b＝0.05，γ_c＝0.05，γ_d＝0.1。

Wherein Num and Num_priTotal number of vehicles, v, representing total number of vehicles and first priority, respectively_maxAnd v_minRespectively representing the highest and lowest vehicle speeds of all vehicles,

and

respectively representing the highest and lowest vehicle speeds, T, of all vehicles of the first priority_lastAnd T_firstRespectively representing the latest departure time and the earliest departure time among all vehicles,

and

respectively representing the latest departure time and the earliest departure time, C, of all first-priority vehicles_startAnd C_endRespectively representing the distribution of the start points and the target points of all the vehicles,

and

respectively representing the starting point and target point distributions of all the first priority vehicles.

In multiple AGV system scheduling, there are mainly three types of path conflicts:

node collision, in which a plurality of AGVs arrive at a certain node at the same time during the traveling of the AGVs, occurs, as shown in fig. 15.

Chase collisions, where AGVs traveling on the same road have a greater speed than the preceding AGV, will occur at some later time, as shown in fig. 16. The present invention sets all AGV speeds to be the same and therefore does not take such conflicts into account.

And in the process of multiple AGV operation, two AGVs may run in opposite directions, so that opposite conflict occurs.

The path planning of a single AGV belongs to the path planning under a static environment, and only whether the planned path from the starting node to the target node is optimal or not needs to be considered. In the multiple-AGV path planning, the problems of AGV path conflict, deadlock, dynamic obstacle and the like in a dynamic environment need to be considered, and a reasonable running path is planned for each AGV trolley, so that the running efficiency of the whole system is optimal.

The method adopts a two-stage scheduling strategy, namely under the offline condition, an improved A-x algorithm is applied based on the time window principle to plan the optimal path of each AGV; and then, under the online condition, the running condition of each AGV is detected in real time, and corresponding processing is carried out according to different running states.

The time window is a model for planning the running time and space of the AGVs, and the running paths of the AGVs are optimized by recording the time from the time when each AGV enters a certain node to the time when each AGV leaves the certain node [62 ]. Each node has two attributes, a retention time window and an idle time window. The reserved time window is the time occupied by an AGV at a certain time by the node, and the idle time window is the time period from when the node is released to when the next AGV enters. A schematic diagram of the time window is shown in fig. 19.

The invention defines the retention time window of a certain node as an H set, as shown in formula (5-4):

in the formula (I), the compound is shown in the specification,

representing the retention time window of the node n,

the starting time of the retention time window of the node n is shown, namely the time when the AGV enters the node;

indicating the end of the retention time window for node n, i.e., the time when the AGV cart leaves node n.

The idle time window is defined as F set, as shown in equations 5-5:

where f represents the idle time window of node n,

indicating the starting moment of the idle time window of the node n, namely the moment when the AGV leaves the node;

indicating the end of the idle time window for node n, i.e., the time when the next AGV enters node n.

t_nThe time a single AGV passes a node.

The time window is a model combining space and time, so that the continuity of the time window, i.e. the continuity of space and time, is guaranteed. The method ensures the continuity in space by improving the A-path planning algorithm, and the continuity in time is mainly realized by reasonably planning the time of each AGV entering and leaving each node through calculating the time window of the node. Assuming the AGV travels from node m to node n, two variables are introduced:

represents the time from node m to node n, as shown in equation (5-6); t is_entRepresentation based on time windows

The time from node m to node n is shown in equation (5-7).

In the formula (I), the compound is shown in the specification,

for the time the AGV arrives at the n node from the m node,

for AGV in time window

Time of internal arrival at node m, t_mnTime spent by AGV on path composed of nodes m, n, t_mThe time the AGV passes node m.

AGV is in time window

The formula for the inner entry node n is as follows:

in the formula, T_entIs based on

The time to reach the n-node from the m-node,

is composed of

In (1)

As shown in fig. 20.

In order to ensure the operation efficiency of the algorithm, the time window calculation needs some preprocessing on the algorithm before optimizing the running path of the multiple AGVs:

firstly, planning a path for an AGV currently executing a task by using an improved A-x algorithm, then judging whether the running path is overlapped with a time window of the AGV with a scheduled time window, and if the running path is not overlapped with the time window, determining the time window of the AGV according to the task execution time; if the overlapped time windows exist, whether the conflict type is node conflict or opposite conflict is judged, if the conflict type is node conflict, a time window algorithm is used for optimization, and if the conflict type is opposite conflict, path planning is carried out on the AGV again.

The basic idea of the time window algorithm is to perform time window-based sequential path planning for multiple AGVs, i.e.: assuming that k tasks are distributed, each trolley finishes one task, the priority of the AGV is firstly sequenced according to the priority of the tasks, and the AGV₁＞AGV₂＞…＞AGV_kThen, the AGV with the highest priority is processed by the improved A-star algorithm₁Planning the path to obtain the AGV₁The entry and exit times at each node, i.e., the retention time window. Then in the AGV₁Planning AGV on idle time window₂Ensure AGV₁And AGV₂No collision occurs. And repeating the steps until the k-th path is planned, so as to ensure that the k-1 path does not collide with the front k-1 path, and finishing off-line path planning of all the AGVs.

In order to ensure that the planned path at each time does not conflict with the planned path before, the path planning steps of the specific ith AGV are as follows:

first, several sets are defined: o represents the set of time windows obtained by the first i-1 planned AGVs; p representation available to AGV_iSet of idle time windows for path planning, K denotes AGV_iA set of idle time windows occupied by a preceding node corresponding to a certain node in the path, e.g.

Indicating the idle time window occupied by the front node 2 of node 3.

AGV with improved A-algorithm_iThe task of (1) performs path planning, a set of planned path nodes is R ═ s, j, …, e }, a start node is s, a target node is e, it is assumed that M is a node set to which a time window is allocated on the path, and N is a node set to which no time window is allocated on the path, and the algorithm is preprocessed.

Initialization, S ═ M, N },

m only comprisesA starting node s occupying a time window of

N contains other nodes, and K is an empty set.

Finding out the nearest idle time window to the adjacent node j in P

Calculating to node j

And

judging whether to use

If the condition is satisfied, then handle

Moving the P-containing material into the O,

shifting j from N into M, and skipping to execute the step v; otherwise handle

Deleting from P, and jumping to step vi.

Judging whether j is a target node e, if so, successfully performing the algorithm, and if not, turning to the step 6;

judging whether P is an empty set, if P is an empty set, the time window optimization cannot be continuously carried out, and the algorithm fails; if not, skipping to execute step 3.

An algorithmic flow chart for time window based multiple AGV path planning is shown in FIG. 21.

The analysis is performed by taking the task number 10005 (start node 27, end node 7), the number 10011 (start node 34, end node 1), and the number 10013 (start node 19, end node 16) as an example. Through the improved a-algorithm, three paths are obtained: 10005: 27-26-25-19-13-7; 10011: 34-33-32-31-25-19-13-7-1; 10013: 19-13-14-15-16. Assuming that the task 10005 and the task 10011 start at the same time (t ═ 2), it takes 2s for each node, and the node entry and exit schedules on the paths of the task 10005 and the task 10011 can be obtained by calculation.

TABLE 4 node ingress and egress schedules on task 10005 path

Table 4 (continuation)

13	19	21
			7	22

Table 5 node entry and exit schedules on task 10011 path

As can be seen from tables 4 and 5, although the same node is included in both paths, path collision does not occur because the time when both paths enter the node is different. Now, suppose that the task 10013 starts at time t equal to 16s, and the entry and exit schedules of its path nodes are shown in table 6.

Table 6 node entry and exit schedules on task 10013 path

As can be seen from tables 4 and 6, task 10005 and task 10013 collide at node 13, and therefore the path node entry and exit time of task 10013 is modified by the time window planning, as shown in table 7.

Table 7 node entry and exit schedule on task 10013 path after time window planning

In order to avoid the path conflict, it is known that the departure time of the task 10013 is t ═ 19s after the time window planning, that is, the task execution is delayed for 3s, so that the time window-based path planning is reasonable time arrangement for the multiple AGV path planning, so that the AGVs avoid the conflict in the operation process, and the scheme has feasibility.

Aiming at algorithm improvement under the condition of large data scale, a time window plans time continuity of multiple AGVs, and space continuity is guaranteed by an A-path planning algorithm. However, with the development of science and technology, it is more necessary to perform reasonable path planning for the situation of large map scale and large number of AGVs. Therefore, the method and the device perform further optimization according to the space-time characteristics of the path planning so as to meet the conditions of high map scale and large AGV number. The basic idea is as follows:

firstly, classifying according to the difference of the space running directions of the AGVs: obtaining the starting node and the ending node of the same batch of tasks, and classifying the tasks into four types according to the relative positions of the ending node and the starting node: from north to south (i.e. the angle between the termination node and the start node and the north to south is less than or equal to 45 degrees), from south to north, from east to west and from west to east.

The priority is set according to the length of the total path, i.e. the longer the total path length, the higher the priority.

And planning time windows of the tasks according to the spatial classification sequence-priority sequence, adjusting and improving a road congestion degree coefficient beta in an A-algorithm, and determining the actual departure time of each task.

Due to the increase of the data scale, the AGV may have deadlock condition in the operation, the deadlock is solved by adopting a backtracking method aiming at the deadlock, namely backtracking to an upper time segment, calibrating one or more AGV (the AGV is selected from the intersection) with deadlock positions, and planning a path to avoid a deadlock lane so as to unlock. The flow chart is shown in figure 22.

The invention carries out path planning aiming at different data scales and obtains a scheduling index T through simulation calculation_endAnd SumT_endAs shown in table 8.

TABLE 8 scheduling indices for different data sizes

The above table shows that under the condition of the same number of AGVs, the scheduling index of the improved multiple AGV path planning algorithm is obviously smaller than that of the non-improved multiple AGVs, and the scheduling time is better, which indicates that the congestion degree of the map at a certain moment can be effectively relieved through the shunting in the spatial direction and the priority setting of the total path length, and the total scheduling time of the system is reduced. Meanwhile, the experimental result shows that the system scheduling time T is increased along with the increase of the number of the priority AGV_endThe influence of the AGV priority on the system scheduling time is reflected; in addition, the total scheduling time SumT of the system_endThe method is in direct proportion to the number of the AGVs, and effectively verifies the rationality of the composite scheduling index based on the scheduling time. As the number of AGVs increases, the unmodified algorithm will yieldUnder the condition of deadlock, the improved algorithm can be effectively unlocked by backtracking and adjusting the road congestion degree coefficient beta, so that the success of the algorithm is ensured.

Many AGV dynamic conflict online solution strategy research has adopted the strategy of time window to solve different conflict types under the condition of off-line, but at actual operation in-process, if AGV breaks down or meets abnormal conditions such as dyskinesia, AGV's operational aspect will change, leads to AGV unable normal completion task, to online conflict problem, and present solution decision is slightly two kinds: one is a traffic rule method based on priority, namely different priorities are set for different AGVs, when node conflict occurs, the AGVs are enabled to continue to operate according to the priority order, and the collision probability among the AGVs is reduced; the other is a geometric path adjustment strategy, namely when a dynamic obstacle is encountered, the path is re-planned for the AGV, and the obstacle is avoided to complete the transportation task.

As shown in fig. 23, the real-time mode specifically includes: the invention adopts a method of combining a traffic rule method based on priority and a geometric path adjustment strategy to solve the problem of dynamic conflict of multiple AGVs, and the basic idea is as follows:

step 1, monitoring the AGV in a running state in real time, determining an initial node s and a target node e of the AGV, and updating a current node in real time.

Step 2, starting from the current node of the AGV operation, periodically scanning a task path behind the AGV, judging whether a conflict is generated, and if not, jumping to the step 6; and if the conflict is generated, jumping to the step 3.

Step 3, judging the current conflict type, and if the current conflict type is a node conflict, skipping to step 4; if the obstacle is fixed, etc., the process jumps to step 5.

Step 4, using a traffic rule method based on priority to allow the AGV with high priority to pass through, waiting for the rest in sequence, then judging whether conflict is solved, and if not, skipping to the step 5; conflict resolution jumps to step 6.

Step 5, performing path re-planning on the AGV, continuously driving to judge whether the conflict is solved, and if not, skipping to the step 4 to wait; conflict resolution jumps to step 6.

Step 6, judging whether the current node is a target node e, if so, the task is successful; if not, jumping to step 2.

The points to be finally explained are: first, in the description of the present application, it should be noted that, unless otherwise specified and limited, the terms "mounted," "connected," and "connected" should be understood broadly, and may be a mechanical connection or an electrical connection, or a communication between two elements, and may be a direct connection, and "upper," "lower," "left," and "right" are only used to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed;

secondly, the method comprises the following steps: in the drawings of the disclosed embodiments of the invention, only the structures related to the disclosed embodiments are referred to, other structures can refer to common designs, and the same embodiment and different embodiments of the invention can be combined with each other without conflict;

and finally: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention are intended to be included in the scope of the present invention.

Claims

1. The utility model provides a many AGV storage management system based on well pharmacy, includes host computer management system, its characterized in that: host computer management system communication is connected with a plurality of AGV dollies and guide rail path, AGV dolly sliding connection is used for standardizing the line of AGV in the guide rail path, host computer management system still is connected with a plurality of auxiliary charging equipment.

2. The system of claim 1, wherein the AGV warehouse management system comprises: the AGV dolly includes the body construction module, body construction top fixed mounting has orientation module, control module, communication module and AGV management module, AGV management module is connected with the communication of upper computer management system, body construction bottom fixedly connected with drive module and safety and electric power module.

3. The system of claim 1, wherein the AGV warehouse management system comprises: the positioning module is an RFID module adopting an electromagnetic guiding mode.

4. The system of any one of claims 1-3, wherein the AGV warehouse comprises: the method also comprises a multi-AGV storage management method based on the traditional Chinese medicine pharmacy, and the method comprises the following specific steps:

and 5: the upper computer management system performs task route planning and distribution according to the map information, the AGV state information and the operation instruction; if no idle AGV exists in the current system, the task waits to be executed until a certain AGV is in an executable state.

5. The multi-AGV storage management method based on traditional Chinese medicine pharmacy according to claim 4, wherein: the route rule distribution in the step 5 comprises the following steps: