CA3153599A1

CA3153599A1 - Multi-agv routing method and system thereof

Info

Publication number: CA3153599A1
Application number: CA3153599A
Authority: CA
Inventors: Xiaocheng DONG; Peilie LIN
Original assignee: 10353744 Canada Ltd
Current assignee: 10353744 Canada Ltd
Priority date: 2019-09-05
Filing date: 2020-06-24
Publication date: 2021-03-11
Also published as: CN110530388A; CN110530388B; WO2021042827A1

Abstract

A multi-AGV path planning method and system. The method comprises: initializing a map model, determining all barrier-free roads, and setting an initial density factor a0 of each road; planning a path for an ith AGV on the basis of current density factors a of all roads and selecting a path having a minimum total driving duration Ti as a selected path Li of the ith AGV; and updating the density factor a of the road in real time according to the selected path Li. According to the multi-AGV path planning system using the multi-AGV path planning method, an AGV path can be selected according to the vehicle density on the road, thereby effectively dispersing vehicles and avoiding road congestion, and enabling a site to be fully utilized.

Description

MULTI-AGV ROUTING METHOD AND SYSTEM THEREOF
BACKGROUND OF THE INVENTION
Technical Field [0001] The present invention relates to the technical field of AGV routing, and more particularly to a multi-AGV routing method and a system thereof.
Description of Related Art

[0002] With the rapid development of e-commerce, warehouse logistics has faced new challenges. The traditional manual warehouse logistics is relatively restricted and unadaptable to new requirements, making AGV-based automated warehousing technologies emerging. Routing is one of the major securities for proper AGV
performance. Routing refers to assigning an AGV with a route from its origin to its destination according to a certain rule, wherein the route should be as short as possible and should be free of any obstacle. The routing process of AGVs primarily includes two parts. The first step is to develop an environmental model as the basis of AGV
navigation and positioning, and the second is to search for routes to identify routes meeting restrictions from the origin to the destination.

[0003] The methods usually used for routing AGVs include: the Dijkstra algorithm, the A*
search algorithm, the simulated annealing algorithm, the ant colony algorithm, the genetic algorithm, the particle swarm algorithm, the Floyd algorithm, and the Fallback algorithm.
However, all of these algorithms only focus on individual vehicles, without considering interaction between vehicles, and only support static planning, without the ability to amend planned routes according to current situations. Besides, these known routing methods can only be used to cases where AGVs are free to move in all directions, and are unable to direct AGVs to move in regular patterns and in roads having various directional Date Recue/Date Received 2022-03-07 restrictions.

[0004] For multiple AGVs working coordinately, while the existing shortest route method can plan a superior route, the planned route does not taken influence from other vehicles working coordinately. If plural vehicles have their optimal routes passing the same road, it is likely that high streets have high vehicle densities and other roads have low densities, making high streets have greater traffic and longer stopping duration.
Additionally, when the existing routing method chooses the shortest route for a multi-AGV
application, acceleration and/or deceleration of the serially moving vehicles can cause the road jammed, and the known method is unable to shunt some of the vehicle to other roads to decrease the vehicle density in the current road by amending the planned route and in a rea-time manner according to current traffic conditions.
SUMMARY OF THE INVENTION

[0005] One objective of the present invention is to overcome the problem about road congestion as seen in the prior-art multi-AGV routing schemes that only focus on individual vehicles without considering interaction between the vehicles working collaboratively, and therefore the present invention provides a multi-AGV routing method. The method of the present invention chooses routes for AGVs according to vehicle densities on roads, thereby effectively distributing vehicles and preventing road congestion so as to make full use of sites. To achieve the foregoing objective, the present invention provides the following technical schemes:

[0006] A multi-AGV routing method, comprising steps of:

[0007] initializing a map model, identifying all obstacle-free roads, and for each of the roads setting an initial density factor ao;

[0008] planning routes for an 11h AGV based on the current density factors a of all the roads, and selecting the route having a minimum total driving duration Ti as a selected route Li of the 11h AGV; and

[0009] according to the selected route Li, updating the density factors a of the roads in a real-Date Recue/Date Received 2022-03-07 time manner;

[0010] where, i > ], and the density factors a of the roads on which the step of planning routes for a Pt AGV are based are equal to ao.

[0011] Preferably, the step of initializing a map model comprises:

[0012] performing an environmental modeling process through a gridded-map method, establishing a plane rectangular coordinate system x0y on a gridded map, and setting an initial density factor /30 for each of grids in the gridded map at the same time; and

[0013] identifying all the roads that are passable by finding the grids free of obstacles through screening, in which each said road is composed of at least two grids that extend in an x-axis direction or in ay-axis direction, and selecting a maximum value of the initial density factors /30 among the grids in each said road as the initial density factor ac, of that road.

[0014] Specifically, the grid has a size corresponding to a small AGV in itself.

[0015] Preferably, the total driving duration Ti of the ith AGV includes a runtime duration T11 and a congestion-incurred waiting duration T12, in which

[0016] the runtime duration T11 of the Pi AGV is estimated according to a running speed of the ith AGV and a length of the route; and

[0017] the congestion-incurred waiting duration T12 of the Pi AGV is estimated according to the density factors a of the roads in the route.

[0018] Further, the current density factors a of all the roads are taken as cost parameters or weight parameters, and the routes are planned for the ith AGV by means of a Dijkstra algorithm, an A*search algorithm, a simulated annealing algorithm, an ant colony algorithm, a genetic algorithm, a particle swarm algorithm, a Floyd algorithm or a Fallback algorithm, in which the runtime duration T11 and the congestion-incurred waiting duration T12 are estimated during the planning, respectively, and the route having the minimum total driving duration Ti is taken as the selected route Li of the ith AGV.

[0019] More preferably, the step of according to the selected route Li, updating the density factor a of the roads in a real-time manner comprises:

[0020] according to the selected route Li of the ith AGV, for each said road in the map, Date Recue/Date Received 2022-03-07 accumulating a number of the routes passing therethrough, so as to obtain the road passed by the largest number of the routes in the x-axis direction and a corresponding route number Cxrnax, as well as the road passed by the largest number of the routes in the y-axis direction and a corresponding route number Cy,,,,x;

[0021] selecting one of the grids in the map, accumulating a route number D, of the selected grid in the x-axis direction and a route number Dy of the selected grid in the y-axis direction, respectively, and selecting the grid having D, or Dy, whichever is greater, as a maximum route number Dnax of the selected grid;

[0022] developing a mathematical model for computing density factors of the grids, and updating the density factor /3 of the selected grid using the mathematical model for computing density factors of the grids according to and a current density factor 13 of the selected grid; and

[0023] sequentially looping and selecting all the grids, cyclically updating all the current density factors 13 of the grids, thereby updating the density factors a of the roads.

[0024] Specifically, the mathematical model for computing the density factors of the grids is:

[0025] when D, is selected as the maximum route number Dnax of the selected grid, the density factor /3 of the selected grid is = /3 x Drnax¨; and cxmax

[0026] when Dy is selected as the maximum route number Dnax of the selected grid, the Dmax density factor /3 of the selected grid is = /3 x Cymax

[0027] Preferably, the multi-AGV routing method further comprises:

[0028] setting a vehicle density threshold for each said grid; and

[0029] during driving of the AGVs, according to the density factors a of the roads, computing vehicle densities p of the ahead roads in the routes in a real-time manner, and when any of the vehicle densities p exceed the vehicle density threshold, rerouting the AGVs, and selecting a route having the minimum total driving duration.

[0030] Further, each said AGV computes the vehicle density p of the ahead road in the route as a x ¨1 ER M where, a is the density factor of the road, R is a number of grid cells in the road, Mp is a number of the AGVs in the pill grid cell, and Mp is of a value of 0 or 1, Date Recue/Date Received 2022-03-07 where l< p R.

[0031] Another objective of the present invention is to overcome the problem about road congestion as seen in the prior-art multi-AGV routing schemes that only focus on individual vehicles without considering interaction between the vehicles working collaboratively, and therefore the present invention provides a multi-AGV
routing method. The method of the present invention chooses routes for AGVs according to vehicle densities on roads, thereby effectively distributing vehicles and preventing road congestion so as to make full use of sites. To achieve the foregoing objective, the present invention provides the following technical schemes:

[0032] A multi-AGV routing system, comprising a map modeling unit, a route selecting unit, and a map updating unit,

[0033] the map modeling unit, for initializing a map model, identifying all obstacle-free roads, and for each of the roads setting an initial density factor a();

[0034] the route selecting unit, for planning routes for an 11h AGV based on the current density factors a of all the roads, and selecting the route having a minimum total driving duration Ti as a selected route Li of the 11h AGV; and

[0035] the map updating unit, for according to the selected route Li, updating the density factors a of the roads in a real-time manner;

[0036] where, i >1, and the density factors a of the roads on which the step of planning routes for a 1st AGV are based are equal to ao.

[0037] As compared to the prior art, the multi-AGV routing method and system of the present invention have the following beneficial effects:

[0038] In the multi-AGV routing method provided by the present invention, the first step is to initialize a map model and identify all obstacle-free roads, and for each of the roads, an initial density factor ac, is set. This is for providing an environmental map basis for the AGV routing process. Based on current density factors a of all the roads, the ifh AGV is routed. Therein, for routing the first AGV, a total driving duration T1 is computed with reference to the basic initial density factor ac, of every road, and the route corresponding to the minimum Ti is selected as the selected route Li for the 11h AGV. In the process of Date Recue/Date Received 2022-03-07 searching routes using a routing algorithm, the density factors a of all the roads current are taken as cost parameters or weight parameters for the shortest route algorithm, so that the total driving durations Ti of the 11h when different routes are selected can be estimated, and the route having the minimum total driving duration Ti can be selected as the selected route Li of the 11h AGV. This helps prevent the problem of the traditional AGV
routing method that simply selects the route shortest in distance and tends to cause road congestion, thereby making full use of sites while improving working efficiency of the AGVs. Additionally, since the density factor a of the road is updated in a real-time manner according to the selected route Li, real-timeliness of the parameters of the map can be ensured to provide a reliable basis for good real-timeliness of the AGV-routing results.

[0039] The multi-AGV routing system provided by the present invention adopts the foregoing multi-AGV routing method, and can such select routes for AGVs according to the vehicle density in the road that vehicles can be effectively distributed, thereby preventing congestion and making full use of sites while improving working efficiency of AGVs.
BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are provided herein for better understanding of the present invention and form a part of this disclosure. The illustrative embodiments and their descriptions are for explaining the present invention and by no means form any improper limitation to the present invention, wherein:

[0041] FIG. 1 is a schematic flowchart of a multi-AGV routing method according to one embodiment of the present invention; and

[0042] FIG. 2 is a detailed flowchart of the multi-AGV routing method according to the embodiment of the present invention.
DETAILED DESCRIPTION OF THE INVENTION

[0043] To make the foregoing objectives, features, and advantages of the present invention Date Recue/Date Received 2022-03-07 clearer and more understandable, the following description will be directed to some embodiments as depicted in the accompanying drawings to detail the technical schemes disclosed in these embodiments. It is, however, to be understood that the embodiments referred herein are only a part of all possible embodiments and thus not exhaustive. Based on the embodiments of the present invention, all the other embodiments can be conceived without creative labor by people of ordinary skill in the art, and all these and other embodiments shall be embraced in the scope of the present invention.

[0044] Embodiment 1

[0045] Referring to FIG. I or FIG. 2, a multi-AGV routing method provided by the present embodiment comprises the following steps:

[0046] initializing a map model, identifying all obstacle-free roads, and for each of the roads setting an initial density factor ao;

[0047] planning routes for an ith AGV based on the current density factors a of all the roads, and selecting the route having a minimum total driving duration Ti as a selected route Li of the ith AGV; and

[0048] according to the selected route Li, updating the density factors a of the roads in a real-time manner;

[0049] where, i > /, and the density factors a of the roads on which the step of planning routes for a Pt AGV are based are equal to ao.

[0050] In the multi-AGV routing method of the embodiment of the present invention, the first step is to initialize a map model and identify all obstacle-free roads, and for each of the roads, an initial density factor ac, is set. This is for providing an environmental map basis for the AGV routing process. Based on current density factors a of all the roads, the Pi AGV is routed. Therein, for routing the first AGV, a total driving duration T1 is computed with reference to the basic initial density factor ac, of every road, and the route corresponding to the minimum Ti is selected as the selected route Li for the ith AGV.
In the process of searching routes using a routing algorithm, the density factors a of all the roads current are taken as cost parameters or weight parameters for the shortest route algorithm, so that the total driving durations Ti of the ith when different routes are Date Recue/Date Received 2022-03-07 selected can be estimated, and the route having the minimum total driving duration Ti can be selected as the selected route Li of the 11h AGV. This helps prevent the problem of the traditional AGV routing method that simply selects the route shortest in distance and tends to cause road congestion, thereby making full use of sites while improving working efficiency of the AGVs. Additionally, since the density factor a of the road is updated in a real-time manner according to the selected route Li, real-timeliness of the parameters of the map can be ensured to provide a reliable basis for good real-timeliness of the AGV-routing results.

[0051] In the multi-AGV routing method of the embodiment of the present invention, the step of initializing a map model comprises: first performing an environmental modeling process through a gridded-map method, establishing a plane rectangular coordinate system x0y on a gridded map, and setting an initial density factor /30 for each of grids in the gridded map at the same time; and then identifying the roads that are passable by finding the grids free of obstacles through screening, in which each said road is composed of at least two grids that extend in an x-axis direction or in ay-axis direction, and selecting a maximum value of the initial density factors /30 among the grids in each said road as the initial density factor ac, of that road.

[0052] Specifically, the grids defined according to an actual warehouse scene may be preferably sized equally to the size of a small AGV in itself. Selecting a proper size for each of the grids in the map is of great importance. Small grids lead to high environmental resolution and slow decision-making. Large grids lead to low environmental resolution and fast decision-making, yet details of routes may be compromised. Sizing the grids with reference to a small AGV facilitates gathering, computing, and updating the vehicle density p of the road, and is also favorable to determining of the next grid in the route for an AGV. In addition, it ensures that a road only having only one row of grids can be passed through by AGVs, so that passable roads can be directly identified by observing these grids.

[0053] Moreover, in specific implementations, every grid in the map is assigned with a value according to whether there is any obstacle in that grid. For example, all the roads in which Date Recue/Date Received 2022-03-07 one or more obstacle exist are set to be 1, and all obstacle-free grids are set to be 0. This allows convenient identification of all obstacle-free roads through determining whether there is any obstacle in a grid.

[0054] In the multi-AGV routing method of the embodiment of the present invention, the total driving duration Ti of the 11h AGV includes a runtime duration T11 and a congestion-incurred waiting duration T12 in which the runtime duration T11 of the 11h AGV
is estimated according to a running speed of the 11h AGV and a length of the route; and the congestion-incurred waiting duration T12 of the ifh AGV is estimated according to the density factors a of the roads in the route. For example, in the routing process, the runtime duration T11 of the 11h AGV without road congestion is estimated in a real-time manner according to the length of the planned route and the running speeds of AGVs. A
relationship table between the density factor a and the congestion-incurred waiting duration T12 is made and stored in advance. The table may divide the density factor a in to plural density factor intervals, and a congestion-incurred waiting duration T12 set for every density factor interval. By doing so, a user can conveniently use the density factors a of the roads included in every step of the planned route to look up the congestion-incurred waiting duration T12 from the table.

[0055] Further, the current density factors a of all the roads are taken as cost parameters or weight parameters and any method that can route individual AGVs can be used to route the 11h AGV, such as the Dijkstra algorithm, the A*search algorithm, the simulated annealing algorithm, the ant colony algorithm, the genetic algorithm, the particle swarm algorithm, the Floyd algorithm and the Fallback algorithm. In the route process, the runtime duration T11 and congestion-incurred waiting duration 7712 are estimated, respectively, and the route having the minimum total driving duration Ti is selected as the selected route Li of the 11h AGV. This prevents the problems of road congestion as seen in the traditional AGV routing approaches where the shortest route is always selected, so as to make full use of sites and improve working efficiency of the AGVs.

[0056] In the multi-AGV routing method of the embodiment of the present invention, to select a route Li for the 11h AGV, the total driving durations Ti are taken as the cost parameters Date Recue/Date Received 2022-03-07 or weight parameters for the shortest routing algorithm, so as to prevent the problems of road congestion when the shortest route is always selected, thereby effectively distributing vehicles, preventing road congestion, and improving working efficiency of the AGVs.

[0057] In the multi-AGV routing method of the embodiment of the present invention, the step of according to the selected route Li, updating the density factors a of the roads in a real-time manner comprises:

[0058] according to the selected route Li of the 11h AGV, for each said road in the map, accumulating a number of the routes passing therethrough, so as to obtain the road passed by the largest number of the routes in the x-axis direction and a corresponding route number Cxrnax, as well as the road passed by the largest number of the routes in the y-axis direction and a corresponding route number Cy,,,,x;

[0059] selecting one of the grids in the map, accumulating a route number D, of the selected grid in the x-axis direction and a route number Dy of the selected grid in the y-axis direction, respectively, and selecting the grid having D, or Dy, whichever is greater, as a maximum route number Dnax of the selected grid;

[0060] developing a mathematical model for computing density factors of the grids, and updating the density factor /3 of the selected grid using the mathematical model for computing density factors of the grids according to rnax,and a current density factor 13 of the selected grid; and

[0061] sequentially looping and selecting all the grids, cyclically updating all the current density factors 13 of the grids, thereby updating the density factors a of the roads.

[0062] By updating the density factors a of the roads according to the selected route Li in a real-time manner, real-timeliness of the parameters of the map can be ensured to provide a reliable basis for good real-timeliness of the AGV-routing results. This enables effective distribution of vehicles, so as to prevent road congestion and improve working efficiency of the AGVs.

[0063] Still referring to FIG. 2, the multi-AGV routing method of the embodiment of the present invention further comprises the following steps:
Date Recue/Date Received 2022-03-07

[0064] setting a vehicle density threshold for each said grid; and

[0065] during driving of the AGVs, according to the density factors a of the roads, computing vehicle densities p of the ahead roads in the routes in a real-time manner, and when any of the vehicle densities p exceed the vehicle density threshold, rerouting the AGVs, and selecting a route having the minimum total driving duration;

[0066] wherein each said AGV computes the vehicle density p of the ahead road in the route as a x ¨1 M
where, a is the density factor of the road, R is a number of grid cells in the road, Mp is a number of the AGVs in the pill grid cell, and Mp is of a value of 0 or 1, where l< p R.

[0067] It is to be noted that, when the vehicle density p of the current road exceeds the vehicle density threshold, but the total driving durations Ti of the alternative routes obtained through the rerouting computation are even greater, the current road remines to be the selected route Li for the AGV.

[0068] The multi-AGV routing method provided by the embodiment of the present invention mainly features the consideration of collaborative operation of multiple AGVs.
By increasing the current density factor a of the road according to the real-time routes of other AGVs, the AGVs can be distributed better and the selected route Li can be changed or amended in a real-time manner according to the real-time vehicle density p of the road ahead, thereby reducing congestion in roads and preventing road congestion to a certain extent. This in turn contributes to shortened congestion-incurred waiting durations T12 of vehicles, and effectively improves operational efficiency of the AGVs.

[0069] Embodiment 2

[0070] The embodiment of the present invention provides a multi-AGV routing system, comprising a map modeling unit, a route selecting unit, and a map updating unit, the map modeling unit, for initializing a map model, identifying all obstacle-free roads, and for each of the roads setting an initial density factor cco; the route selecting unit, for planning routes for an ifh AGV based on the current density factors a of all the roads, and selecting the route having a minimum total driving duration Ti as a selected route Li of the ifh Date Recue/Date Received 2022-03-07 AGV; and the map updating unit, for according to the selected route Li, updating the density factors a of the roads in a real-time manner; where, i >1, and the density factors a of the roads on which the step of planning routes for a Pt AGV are based are equal to ao.

[0071] The multi-AGV routing system provided by the present invention adopts the multi-AGV
routing method as described in the previous embodiment, and is capable of choosing routes for AGVs according to vehicle densities on roads, thereby effectively distributing vehicles and preventing road congestion, so as to make full use of sites and improve working efficiency of the AGVs.

[0072] In the description of the foregoing implementations, the specific features, structures, or characteristics may be combined in any suitable way in any one or more embodiments or examples.

[0073] The present invention has been described with reference to the preferred embodiments and it is understood that the embodiments are not intended to limit the scope of the present invention. Moreover, as the contents disclosed herein should be readily understood and can be implemented by a person skilled in the art, all equivalent changes or modifications which do not depart from the concept of the present invention should be encompassed by the appended claims. Hence, the scope of the present invention shall only be defined by the appended claims.

Date Recue/Date Received 2022-03-07

Claims

What is claimed is:

1. A multi-AGV routing planning method, wherein comprising:
initializing a map model, identifying all obstacle-free roads, and for each of the roads setting an initial density factor ac, at the same time;
setting a vehicle density threshold for each said grid; and during driving of the AGVs, according to the density factors a of the roads, computing vehicle densities p of the ahead roads in the routes in a real-time manner, and when any of the vehicle densities p exceed the vehicle density threshold, re-planning routes for the AGVs, and selecting a route having the minimum total driving duration;
where, i > /, and the density factors a of the roads on which the step of planning routes for a 1st AGV are based are equal to ao, wherein where, R is a number of grid cells in the road, Mp is a number of the AGVs in the pth grid cell, and Mp is of a value of 0 or 1, where /< p <R.

2. The multi-AGV routing method of claim 1, wherein the step of initializing a map model comprises:
performing an environmental modeling process through a gridded-map method, establishing a plane rectangular coordinate system x0y on a gridded map, and setting an initial density factor /30 for each of grids in the gridded map at the same time; and identifying the roads that are passable by finding the grids free of obstacles through screening, in which each said road is composed of at least two grids that extend in an x-axis direction or in a y-axis direction, and selecting a maximum value of the initial density factors /30 among the grids in each said road as the initial density factor ac, of that road.

3. The multi-AGV routing method of claim 2, wherein each of the grids has a size corresponding to a small AGV in itself.

4. The multi-AGV routing method of claim 2, wherein the total driving duration T1 of the AGV includes a runtime duration T and a congestion-incurred waiting duration T12, in which the runtime duration T11 of the ith AGV is estimated according to a running speed of the ill' AGV
and a length of the route; and the congestion-incurred waiting duration T 12 of the ith AGV is estimated according to the density factors a of the roads in the route.

5. The multi-AGV routing method of claim 4, wherein the current density factors a of all the roads are taken as cost parameters or weight parameters, and the routes are planned for the ith AGV by means of a Dijkstra algorithm, an A*search algorithm, a simulated annealing algorithm, an ant colony algorithm, a genetic algorithm, a particle swarm algorithm, a Floyd algorithm or a Fallback algorithm, in which the runtime duration T11 and the congestion-incurred waiting duration T 12 are estimated during the planning, respectively, and the route having the minimum total driving duration Ti is taken as the selected route Li of the ith AGV.

6. The multi-AGV routing method of claim 2, wherein the step of according to the selected route Li, updating the density factors a of the roads in a real-time manner comprises:
according to the selected route Li of the ith AGV, for each said road in the map, accumulating a number of the routes passing therethrough, so as to obtain the road passed by the largest number of the routes in the x-axis direction and a corresponding route number Cxrnax, as well as the road passed by the largest number of the routes in the y-axis direction and a corresponding route number Cymax;
selecting one of the grids in the map, accumulating a route number D, of the selected grid in the x-axis direction and a route number Dy of the selected grid in the y-axis direction, respectively, and selecting the grid having D, or Dy, whichever is greater, as a maximum route number Dma, of the selected grid;
developing a mathematical model for computing density factors of the grids, and updating the density factor /3 of the selected grid using the mathematical model for computing density factors of the grids according to Cxrnax, Cymax, Dmax, and a current density factor /3 of the selected grid; and sequentially looping and selecting all the grids, cyclically updating all the current density factors /3 of the grids, thereby updating the density factors a of the roads.

7. The multi-AGV routing method of claim 6, wherein the mathematical model for computing the density factors of the grids is:
when D, is selected as the maximum route number Dina, of the selected grid, the density factor /3 of the selected grid is <BIG> and when Dy is selected as the maximum route number Apa, of the selected grid, the density factor /3 of the selected grid is

8. A multi-AGV routing planning system, wherein comprising a map modeling unit, a route selecting unit, and a map updating unit, wherein the map modeling unit, for initializing a map model, identifying all obstacle-free roads, and for each of the roads setting an initial density factor ac, at the same time;
the route selecting unit, for planning routes for an AGV based on the current density factors a of all the roads, and selecting the route having a minimum total driving duration Ti as a selected route Li of the ith AGV; and further for setting a vehicle density threshold for each said grid; and during driving of the AGVs, according to the density factors a of the roads, computing vehicle densities p of the ahead roads in the routes in a real-time manner, and when any of the vehicle densities p exceed the vehicle density threshold, re-planning routes for the AGVs, and selecting a route having the minimum total driving duration;
and the map updating unit, for according to the selected route Li, updating the density factors a of the roads in a real-time manner;
where, i >1, and the density factors a of the roads on which the step of planning routes for a 1st AGV are based are equal to ao, wherein where, R is a number of grid cells in the road, Mp is a number of the AGVs in the pill grid cell, and Mp is of a value of 0 or 1, where ]<p <R..