CN109782757A - A kind of path dispatching method of more AGV systems based on subsection scheduling - Google Patents
A kind of path dispatching method of more AGV systems based on subsection scheduling Download PDFInfo
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Abstract
The path dispatching method of the invention discloses a kind of more AGV systems based on subsection scheduling, include the following steps: offline scheduling steps: each node in AGV running environment carries out segregation reasons, plan that the optimal path of every other node, each path is stored in the form of chained list into path library for each node using genetic algorithm；On-line scheduling step: in the transport task for receiving upper computer control system, the corresponding optimal path of transport task is searched from the library of path；Judge whether to have in AGV operational process and conflicts and the conflict avoided between AGV is adjusted according to the type of conflict.The present invention has the advantages that being stored in the library of path after the optimal path that off-line phase first reaches other all nodes to each node is planned, after receiving transport instruction, directly optimal path is selected from the library of path, optional path is provided for online task schedule, reduces the calculation amount of online task schedule.
Description
Technical field
It stores in a warehouse the present invention relates to automatic intelligent and dispatches systems technology field, in particular to it is a kind of based on the more of subsection scheduling
The path dispatching method of AGV system.
Background technique
With the fast development of Intelligent logistics and automatic technology, AGV is obtained as the core equipment of modern logistics systems
It is widely applied.Path planning problem is as most basic, most one of good problem to study, increasingly by scholar and work
The attention of Cheng Shi.Good driving path can guarantee the total tune of system, improve the flexibility and efficiency of system.It is right
In the selection of more AGV system optimal paths, not only need to meet shortest distance and least time cost simultaneously, it is also necessary to solve
Interaction and information sharing between certainly more AGV are to avoid collision and deadlock.Therefore, Modern Mathematical Methods and computer technology are utilized
Rapid solving Optimal Scheduling is an extremely important project.
The path AGV scheduling planning is exactly to avoid various barriers in the motion process of AGV, reaches target from starting point
Point, and meet various optimizing index, if path length is most short, runing time is most short etc..
It is varied to the method for AGV path planning utilization at present, with the extensive use of genetic algorithm, path is advised
It draws and constantly obtains new progress.Genetic algorithm is resulted from earliest in the 1960s, started by professor Holland in the U.S., it
It is referred from Darwinian theory of biological evolution, by the analysis to practical problem, establishes corresponding biological evolution model, and to population
In individual a series of genetic manipulations such as selected, intersect and make a variation, so that the individual in population is evolved to advantageous direction, directly
To generating or close to optimum individual.
With the research dispatched to more AGV systems, the task schedule of more AGV systems can be described as follows: in Intelligent logistics
In system, there are multiple AGV, multiple request sites, multiple feasible transportation routes and multiple commodity supplement website, need in task
Certain correlation is established between AGV.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of more AGV systems based on subsection scheduling
Path dispatching method first carries out the planning of optimal path in off-line phase, online to adjust then after host computer issues mission bit stream
Degree system carries out on-line scheduling after finding the optimal path in offline, solves the problems, such as node conflict by on-line scheduling.
To achieve the goals above, the technical solution adopted by the present invention are as follows: a kind of more AGV systems based on subsection scheduling
Path dispatching method, includes the following steps:
Offline scheduling steps: each node in AGV running environment carries out segregation reasons, is planned using genetic algorithm each
Node is stored in each path in the form of chained list into path library to the optimal path of every other node
On-line scheduling step: in the transport task for receiving upper computer control system, transport is searched from the library of path and is appointed
It is engaged in corresponding optimal path；Judge whether to have in AGV operational process conflict and be adjusted according to the type of conflict avoid AGV it
Between conflict.
In on-line scheduling step, calculate in each AGV optimal path AGV with pre-set velocity reach each node it is corresponding when
Between, to form the routing information table with time window of each AGV, identical section is reached in each path AGV by comparing
The time of point is to determine whether generate conflict in the same node point, if same node point and corresponding in the different road AGV
Time up to the node is identical, then is judged as node conflict.
In node conflict, priority is arranged according to the time of the transport task received, morning time priority is high, is connecing
When nearly node conflict, the low AGV of priority reduces speed.
The low AGV of priority updates the routing information table with time window according to the variation of speed after reducing speed,
Then node conflict judgement is carried out according to the routing information table circulation after update with time window in real time by scheduling system.
Selection has the node chain of consecutive identical node in all paths AGV, has in this section of node chain and pursues and attacks conflict,
For having the AGV for pursuing and attacking conflict, avoid conflicting by adjusting the speed of front truck, rear car, while updating in routing information table
Time window, reselect the node chain with same node point, loop to determine with the presence or absence of conflict.
The present invention has the advantages that being carried out in the optimal path that off-line phase first reaches other all nodes to each node
It is stored in after planning in the library of path, after receiving transport instruction, directly selects optimal path from the library of path, be online task
Scheduling provides optional path, reduces the calculation amount of online task schedule.When upper computer control system issues detailed transport task
When, on-line scheduling judges node conflict by calculating the time window in each node in the process, finally solves node conflict
Problem.
Detailed description of the invention
Below to each width attached drawing of description of the invention expression content and figure in label be briefly described:
Fig. 1 is the path network schematic diagram of more AGV systems；
Fig. 2 is the possible conflict type of more AGV；
Fig. 3 is dispatching method flow diagram of the present invention；
Fig. 4 is the more AGV driving path network diagrams for including AGV1, AGV2.
Specific embodiment
A specific embodiment of the invention is made further detailed below against attached drawing by the description to optimum embodiment
Thin explanation.
As shown, Fig. 1 is the simple plan that AGV system more than one executes task.In Fig. 1, there are 3 in network simultaneously
AGV executes task, and each AGV has 12 dispatching websites to provide cargo to each AGV.AGV is adjusted in the unified of upper-level control system
Under degree, task is completed according to task order.Upper computer control system needs to plan optimal road for each AGV in scheduling process
Diameter, and calculated in real time, to determine whether multiple AGV while occur.If there is the collision of AGV and upper control system,
It needs reasonably to handle.Mainly there are two major classes for the algorithms of more AGV system path plannings at present: offline task schedule and online
Task schedule.
In more AGV systems, different operating status when being encountered according to AGV, conflict is broadly divided into node conflict, pursues and attacks punching
Prominent and opposite conflict.
Node conflict, as shown in Fig. 2, the two different traffic directions of AGV1 and AGV2 reach node A in same road network.
It, can be in node A collision conflict if the operating status of one of them does not change.
Pursue and attack conflict, as shown in Fig. 2, the AGV1 and AGV2 of the same direction due to the speed of service difference, in some of road network
Place can collide, and be known as pursuing and attacking conflict.
Reversed conflict, as shown in Fig. 2, the AGV1 and AGV2 of different traffic directions are run on same path；Because every
Path only allows an AGV to pass through, and then will collide, this is referred to as reversed conflict.
Offline task schedule refers to the dispatching method under AGV known task demand and ambient environmental conditions；AGV is being run
It is preceding that its operating path is calculated by optimization algorithm.In AGV running environment, for dispatching only static-obstacle barrier offline, and hinder object
The coordinate of position is known.It is being run simultaneously there are also multiple AGV.The purpose of scheduling be it is in office it is pragmatic it is existing under the premise of make it is each
AGV is not clashed, and the optimal path for meeting objective function is found from starting point to destination for each AGV.Offline task tune
It spends weaker to the adaptability of environment；In general, it is unavailable all to may cause whole system for any subtle environmental change, thus
The flexibility decline for causing AGV to run.Therefore, offline method for scheduling task does not have good versatility, but due to not considering
Influence of some enchancement factors to system, and there is relatively simple operation process.
Due to the rhythm in intelligent logistics system there is production, task is preferential, whether home-delivery center's cargo is sufficient, with
And the operating status (such as electric power) and failure etc. of AGV influence, it is dynamic, unknown for leading to the running environment of AGV.More AGV
Speed and direction be real-time change in the process of running.AGV needs sensor to carry out online real-time map to ambient enviroment
Scanning, whether there are obstacles and the position of barrier, size and shape for detection sweep radius.Wherein, obstacle includes static state
AGV under obstacle and other operating statuses.AGV path planning is known as online task schedule under dynamic environment.
Online task schedule is a kind of sensor-based active path planning, does not need to create map in advance.Sensor
For local paths planning, barrier is avoided, prevents the collision between AGV；A series of continuous local paths plannings form
The global path planning of AGV.
Two stage scheduling strategy modeling, basic principle are that the offline path of AGV is generated using offline task schedule, then
The real-time route under dynamic environment is carried out using online task scheduling strategy to plan.Offline scheduling phase be under static environment,
The optimal path of every other node is generated to from each node.The step can use genetic algorithm and carry out path planning, will
Each path is stored in the form of chained list into path library.The purpose is to provide optional path for online task schedule, reduce
The calculation amount of line task schedule.When upper computer control system issues detailed transport task, chained list in passage path library and
The status information of each AGV plans the path optimizing avoided collision.Flow chart is as shown in Figure 3.
In offline task schedule, first major issue is to establish road net model under the static environment for having barrier.
One general route map includes tangent line figure and Voronoi diagram.Tangent line figure indicates the road of AGV operation using the profile of barrier
Path portion, it is more likely to run AGV on the node close to barrier.Voronoi diagram model simple, intuitive, can make AGV
Running precision is high, may cause the collision between AGV and barrier when being greater than range accuracy.In contrast, Voronoi diagram is made
For road network model it can guarantee that AGV collisionless is run, the edge of its Use barriers object as far as possible indicates the path portion of AGV
Point.Detailed scheme is that the contour edge of barrier is extended outwardly into a certain distance, forms new contour line as AGV's
Secure path.In general, outwardly extending distance is not less than the largest contours size of AGV.
Online task schedule is the core of more AGV path plannings, and the supplement and extension of offline task schedule.This
The basic thought of offline task schedule used by invention is to be passed the online information in offline path library and AGV based on time window
Sensor combines.According to the priority of AGV, parking and waiting, operating speed variation and path change solve conflict.It is constrained
Condition is arranged such as according to actual needs can be set the constraint that node does not conflict, and be planned.Path is carried out to more AGV simultaneously
Planning, calculates the Lothrus apterus optimal path of each AGV.The hypothesis of more AGV system on-line scheduling strategies is as follows:
1, this road is one-way road；
2, on the same node of road network, only an AGV is allowed to execute turning.
3, it is instantaneous for setting the speed regulation process of AGV (accelerate, slow down or stop).
4, before every subtask, it should be ensured that AGV has enough electricity.
5, each AGV can only execute a task.
Before each task, by the priority of task is manually arranged, task is more early, and priority is higher.
It is main below that the AGV routing information table for having time window is discussed, that is, operate in the AGV in planning path section when
Between segment information table.Assuming that system starting is zero moment 00:00:00, then the time that AGV reaches each node can be by with lower class
Type determines
Wherein n indicates the interstitial content of path network, t0It is the time that master system distributes to AGV, tiIt is that AGV is reached
The time of node, vagvIndicate the travel speed of AGV, L(i-1)iIndicate that node i -1 arrives the distance between node i.
AGV path network is shown in Fig. 4, it is assumed that the task that host computer scheduling system is sent be AGV1 from node b to
Node n, the optimal path inquired are b → c → e → g → l → n.AGV2 drives to node n from node a, and what is inquired is optimal
Path is a → d → e → g → l → n.Therefore the collision of AGV may occur in e → g → section i → n.The traveling of two AGV
Speed is different, and the routing information table based on time window is as shown in table 1.
Conclusion as can be drawn from Table 1,0 moment AGV1 set out in starting point, and AGV2 sets out after 35s, may send out in node e
Raw node conflict, since the speed of AGV1, AGV2 are different, in g, l, o node, two cars can be reached successively.
Due to not considering that other AGV dynamically influence system in offline scheduling phase, the conflict between AGV is in practical fortune
Can obviously it occur in row.During path planning, it is important to handle node conflict, pursue and attack conflict and reversed conflict.More
In AGV system, collision detection, which mainly detects the time and space on AGV execution route, whether there is intersection；That is, if
Same path node has multiple AGV to gather simultaneously, then may determine that as collision.It can be according to the traffic direction of AGV, speed and each
From routing information table come judge conflict type.
For node conflict, according to routing information check each AGV same node in road network arrival time whether one
It causes；If consistent, node conflict will occur.Priority ratio relatively can be used for solving node conflict.When low priority AGV is close
When conflicting nodes, speed or parking can be reduced, makes high priority AGV leading.AGV with velocity variations needs real-time update road
Diameter information table.
For pursuing and attacking conflict, selection has continuous and same node point node chain from all paths AGV.These are by node
The part of composition is the part there may be conflict.Compare the time value that AGV reaches these nodes after the selection of same paths chain.
From first node to the next node of same path chain, the operating result between AGV get ahead arrive first, get ahead after arrive, after
It walks to arrive first, for the last two cases, conflict can be pursued and attacked between AGV.We can pass through the speed or reduction of AGV before improving
The speed of AGV avoids the conflict between two AGV afterwards.
For reversely conflicting, the AGV of opposite direction should be found in the same section of routing information table, and find path sections
Number of nodes.Opposite conflict can be solved to later by path planning again and time window, but two kinds of strategies all may cause newly
Path conflict, conflict can be embodied in routing information table, need repeatedly to calculate and be just able to achieve optimal path.
The invention proposes a kind of more AGV system optimum path planning methods based on two stages scheduling controlling strategy.I.e.
Offline scheduling phase optimizes best obstacle-avoiding route planning of the AGV under static environment using genetic algorithm, solves
The calculation amount that line gauge is drawn improves the efficiency transferred avoid conflict online.The early convergence problem of genetic algorithm is not only solved, and
Solves the problems, such as the obstacle avoidance of AGV path planning.The on-line scheduling stage mainly passes through three kinds of typical conflicts between detection AGV
Type simultaneously solves these conflicts to realize the online avoidance scheduling of AGV.
Obviously present invention specific implementation is not subject to the restrictions described above, as long as using method concept and skill of the invention
The improvement for the various unsubstantialities that art scheme carries out, it is within the scope of the present invention.
Claims (5)
1. a kind of path dispatching method of more AGV systems based on subsection scheduling, characterized by the following steps:
Offline scheduling steps: each node in AGV running environment carries out segregation reasons, plans each node using genetic algorithm
To the optimal path of every other node, each path is stored in the form of chained list into path library；
On-line scheduling step: in the transport task for receiving upper computer control system, transport task pair is searched from the library of path
The optimal path answered；Judge whether to have in AGV operational process to conflict and be adjusted according to the type of conflict and avoid between AGV
Conflict.
2. a kind of path dispatching method of more AGV systems based on subsection scheduling as described in claim 1, it is characterised in that:
In on-line scheduling step, AGV is calculated in each AGV optimal path with pre-set velocity and reaches each node corresponding time, thus
The routing information table with time window of each AGV is formed, by comparing the time for reaching same node point in each path AGV
To determine whether conflict is generated in the same node point, if same node point and corresponding arrival node in the different road AGV
Time it is identical, then be judged as node conflict.
3. a kind of path dispatching method of more AGV systems based on subsection scheduling as claimed in claim 2, it is characterised in that:
In node conflict, priority is arranged according to the time of the transport task received, morning time priority is high, rushes close to node
When prominent, the low AGV of priority reduces speed.
4. a kind of path dispatching method of more AGV systems based on subsection scheduling as claimed in claim 2, it is characterised in that:
The low AGV of priority updates the routing information table with time window according to the variation of speed after reducing speed, then by adjusting
Degree system carries out node conflict judgement according to the routing information table circulation after update with time window in real time.
5. a kind of path dispatching method of more AGV systems based on subsection scheduling as claimed in claim 1 or 2, feature exist
In: selection has the node chain of consecutive identical node in all paths AGV, has in this section of node chain and pursues and attacks conflict, for
With the AGV for pursuing and attacking conflict, avoid conflicting by adjusting the speed of front truck, rear car, at the same update in routing information table when
Between window, reselect the node chain with same node point, loop to determine with the presence or absence of conflict.
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| CN113780633A (en) * | 2021-08-20 | 2021-12-10 | 西安电子科技大学广州研究院 | Complex environment-oriented multi-AGV intelligent cooperative scheduling method with real-time conflict resolution function |
| CN114115259A (en) * | 2021-11-18 | 2022-03-01 | 青晨(广州)电子商务科技有限公司 | AGV real-time path gauge and collision avoidance method and system |
| CN114115259B (en) * | 2021-11-18 | 2024-04-16 | 青晨(广州)电子商务科技有限公司 | AGV real-time path gauge and anti-collision method and system |
| CN114170844A (en) * | 2021-12-03 | 2022-03-11 | 广东嘉腾机器人自动化有限公司 | Anti-collision method under condition of same-field operation of multiple AGV |
| CN114692939A (en) * | 2021-12-06 | 2022-07-01 | 西安电子科技大学广州研究院 | Multi-AGV task scheduling method based on double-layer strategy |
| CN114757591A (en) * | 2022-06-14 | 2022-07-15 | 湖南大学 | Multi-vehicle type collaborative sorting scheduling method based on behavior dependency graph |
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