Automatic guided vehicle dispatching method, device, electronic equipment and storage medium

Abstract

The present application belongs to the technical field of automatic guided vehicle scheduling, and discloses an automatic guided vehicle scheduling method, device, electronic device and storage medium. The method comprises: obtaining task information and the running state and position information of the automatic guided vehicle, and assigning the target task in the task information to the automatic guided vehicle in an idle state with the shortest distance according to the position information, and generating a corresponding running path, and generating a priority control scheme according to the relationship between the number of automatic guided vehicles in motion in the neighborhood and the preset minimum density and the priority ranking of each target task through a density-based clustering algorithm, and designing a local obstacle avoidance route through an A-star search algorithm when there are occupied route points in the running path; and generating a running path and designing a priority control scheme and a local obstacle avoidance route through a density-based clustering algorithm and an A-star search algorithm to schedule the automatic guided vehicle, thereby improving the scheduling efficiency of the automatic guided vehicle.

Description

Technical Field

[0001] The present application relates to the technical field of automatic guided vehicle scheduling, and in particular to an automatic guided vehicle scheduling method, device, electronic equipment and storage medium. Background Art

[0002] At present, in order to solve the problem of collision caused by the intersection of multiple automated guided vehicles, the time and space occupancy method is generally used. In the process of using the above method, it is necessary to define the occupied space of each automated guided vehicle and ensure that the time and space between each automated guided vehicle do not overlap. This method requires defining the surrounding space of the automated guided vehicle and calculating the space-time diagram in real time, which is more complicated.

[0003] Therefore, in order to solve the technical problem that the existing automatic guided vehicle scheduling method has complex calculations when avoiding collisions between automatic guided vehicles, resulting in excessive scheduling time, an automatic guided vehicle scheduling method, device, electronic device and storage medium are urgently needed. Summary of the invention

[0004] The purpose of the present application is to provide an automated guided vehicle scheduling method, device, electronic device and storage medium. Through a density-based clustering algorithm and an A-star search algorithm, an operation path is generated and a corresponding priority control scheme and a corresponding local obstacle avoidance route are designed according to the operation status and position information of the automated guided vehicle to schedule the automated guided vehicle, thereby solving the problem that the existing automated guided vehicle scheduling method has complex calculations when avoiding collisions of the automated guided vehicle, resulting in excessive scheduling time. The automated guided vehicle is scheduled through a priority control scheme and a local obstacle avoidance route, thereby avoiding collisions of the automated guided vehicle and improving the scheduling efficiency of the automated guided vehicle.

[0005] In a first aspect, the present application provides an automatic guided vehicle scheduling method, comprising:

[0006] Acquire task information, and acquire the operation status and position information of all automatic guided vehicles in the node path map; the task information includes a target task node of at least one target task and a priority ranking of each target task; the operation status includes an idle state, a moving state, and a working state;

[0007] According to the position information, each target task in the task information is assigned to an automatic guided vehicle in the idle state whose straight-line distance to the target task node corresponding to each target task is the smallest, and a corresponding running path is generated to guide the automatic guided vehicle assigned to the target task to enter the moving state and move toward the corresponding target task node based on the running path;

[0008] Taking the preset first time as a period, using a density-based clustering algorithm, according to the relative size relationship between the number of automatic guided vehicles in the moving state in the neighborhood of any automatic guided vehicle in the moving state and a preset minimum density, combined with the priority ranking of each of the target tasks, periodically generating a priority control scheme for the neighborhood;

[0009] periodically detecting whether there are any occupied route points in the running paths of the automatic guided vehicles in the moving state with a preset second time as a period, and when it is detected that there are any occupied route points in the running paths of any automatic guided vehicles in the moving state, designing a local obstacle avoidance route at a corresponding position by using an A-star search algorithm;

[0010] Based on the priority control scheme and / or the local obstacle avoidance route, all automatic guided vehicles in the node path map are scheduled.

[0011] The automatic guided vehicle scheduling method provided in the present application can realize the scheduling of automatic guided vehicles. Through the density-based clustering algorithm and the A-star search algorithm, according to the operating status and position information of the automatic guided vehicle, an operating path is generated and a corresponding priority control scheme and a corresponding local obstacle avoidance route are designed to schedule the automatic guided vehicle. The problem that the existing automatic guided vehicle scheduling method has complex calculations when avoiding collisions of automatic guided vehicles, resulting in excessive scheduling time, is solved. Automatic guided vehicles are scheduled by priority control schemes and local obstacle avoidance routes, which avoids collisions of automatic guided vehicles and improves the scheduling efficiency of automatic guided vehicles.

[0012] Optionally, the node path map includes multiple nodes and paths formed by connecting adjacent nodes; wherein the nodes include path nodes and task nodes, and the task nodes include inbound nodes and outbound nodes.

[0013] Optionally, taking the preset first time as a period, using a density-based clustering algorithm, according to the relative size relationship between the number of automatic guided vehicles in the moving state in the neighborhood of any automatic guided vehicle in the moving state and a preset minimum density, combined with the priority ranking of each of the target tasks, a priority control scheme for the neighborhood is periodically generated, including periodically performing the following steps:

[0014] Calculating the number of automatic guided vehicles in the motion state in the neighborhood of any automatic guided vehicle in the motion state by using the density-based clustering algorithm;

[0015] When the number is greater than or equal to the preset minimum density, the automatic guided vehicles in the neighborhood in the moving state are sorted in descending order according to the priority ranking of the target tasks assigned to the automatic guided vehicles in the moving state in the neighborhood to obtain a priority control sorting;

[0016] According to the priority control ranking, a priority control scheme for the neighborhood is generated.

[0017] The automatic guided vehicle scheduling method provided in the present application can realize the scheduling of automatic guided vehicles. Through the density-based clustering algorithm, when the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion is greater than or equal to a preset minimum density, the automatic guided vehicles in motion in the neighborhood are sorted in descending order according to the priority ranking of the target task, and a priority control sorting is obtained to generate a priority control scheme. Through the priority control scheme, collisions of automatic guided vehicles are avoided, which is conducive to improving the scheduling efficiency of automatic guided vehicles.

[0018] Optionally, the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion is calculated by a density-based clustering algorithm, including:

[0019] Taking any automatic guided vehicle in the motion state as the center and a preset distance as the radius, a circle area with any automatic guided vehicle in the motion state as the core point is obtained;

[0020] Traversing all the circle areas, when there are other core points in the circle area of ​​any core point, merging the circle areas of the other core points into the circle area of ​​any core point to obtain the neighborhood of any core point;

[0021] The number of automatic guided vehicles in the motion state in the neighborhood of any core point is obtained by counting.

[0022] Optionally, generating a priority control scheme for the neighborhood according to the priority control ranking includes:

[0023] Based on the priority control ranking, the automatic guided vehicles in the motion state are selected as control objects in order of ranking;

[0024] The control criterion is to control the automatic guided vehicles other than the control objects in the neighborhood to stop moving while the driven control objects continue to run, and the control target is to drive the controlled objects to leave the area corresponding to the neighborhood. Combined with the priority control sorting, a priority control scheme for the neighborhood is generated.

[0025] Optionally, with a preset second time as a period, periodically detecting whether there are occupied route points in the running paths of the automatic guided vehicles in the moving state, when it is detected that there are occupied route points in the running paths of any automatic guided vehicle in the moving state, designing a local obstacle avoidance route at a corresponding position by using an A-star search algorithm, including:

[0026] According to a preset interval length, dividing the running path of any automatic guided vehicle in the moving state into a plurality of route points;

[0027] Taking the preset second time as a period, according to the preset route point traversal order, it is periodically determined whether there is an automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point between the current route point and the target task node for each automatic guided vehicle in the moving state; if so, the route point where there is an automatic guided vehicle in a stopped moving state within the preset obstacle range is determined to be an occupied route point, and a local obstacle avoidance route is designed at the location of the occupied route point through the A-star search algorithm; if not, it is determined that there is no occupied route point in the running path, and the running path does not need to be adjusted.

[0028] The automatic guided vehicle scheduling method provided in the present application can realize the scheduling of automatic guided vehicles. When any automatic guided vehicle in motion has an automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point between the current route point and the target task node, the route point is determined to be an occupied route point, and a local obstacle avoidance route is designed at the location of the occupied route point through the A-star search algorithm. The local obstacle avoidance route is used to avoid collisions between automatic guided vehicles, thereby improving the scheduling efficiency of automatic guided vehicles.

[0029] Optionally, designing a local obstacle avoidance route at the location of the occupied route point by using the A-star search algorithm includes:

[0030] Taking the occupied route point as the center and a preset obstacle avoidance radius, a circle is drawn to obtain an obstacle avoidance area;

[0031] Selecting a route point closest to the obstacle avoidance area at each of the upstream and downstream locations of the obstacle avoidance area on the running path to which the occupied route point belongs;

[0032] The two selected route points are used as the starting point and the end point of the local obstacle avoidance route, and the local obstacle avoidance route at the location of the occupied route point is calculated through the A-star search algorithm.

[0033] In a second aspect, the present application provides an automatic guided vehicle scheduling device, comprising:

[0034] An acquisition module, used to acquire task information, and to acquire the operating status and position information of all automatic guided vehicles in the node path map; the task information includes a target task node of at least one target task and a priority ranking of each target task; the operating status includes an idle state, a moving state, and a working state;

[0035] an allocation module, configured to allocate each target task in the task information to an automatic guided vehicle in the idle state whose straight-line distance to a target task node corresponding to each target task is the smallest according to the position information, and generate a corresponding running path to guide the automatic guided vehicle allocated to the target task to enter the moving state and move toward the corresponding target task node based on the running path;

[0036] A generation module is used to periodically generate a priority control scheme for the neighborhood by using a density-based clustering algorithm based on a preset first time period, according to a relative size relationship between the number of automatic guided vehicles in the motion state in the neighborhood of any automatic guided vehicle in the motion state and a preset minimum density, combined with a priority ranking of each of the target tasks;

[0037] A design module is used to periodically detect whether there are occupied route points in the running paths of the automatic guided vehicles in the moving state with a preset second time as a period, and when it is detected that there are occupied route points in the running paths of any automatic guided vehicles in the moving state, a local obstacle avoidance route is designed at a corresponding position by using an A-star search algorithm;

[0038] A scheduling module is used to schedule all automatic guided vehicles in the node path map based on the priority control scheme and / or the local obstacle avoidance route.

[0039] The automatic guided vehicle scheduling device generates an operation path and designs a corresponding priority control scheme and a corresponding local obstacle avoidance route according to the operation status and position information of the automatic guided vehicle through a density-based clustering algorithm and an A-star search algorithm, so as to schedule the automatic guided vehicle, thereby solving the problem that the existing automatic guided vehicle scheduling method has a relatively complex calculation when avoiding collisions of the automatic guided vehicle, resulting in a long scheduling time. The automatic guided vehicle is scheduled through a priority control scheme and a local obstacle avoidance route, thereby avoiding collisions of the automatic guided vehicle and improving the scheduling efficiency of the automatic guided vehicle.

[0040] In a third aspect, the present application provides an electronic device, including a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the automatic guided vehicle scheduling method described above.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the automatic guided vehicle scheduling method described above are executed.

[0042] Beneficial effects: The automated guided vehicle scheduling method, device, electronic device and storage medium provided in the present application generate an operation path and design a corresponding priority control scheme and a corresponding local obstacle avoidance route according to the operation status and position information of the automated guided vehicle through a density-based clustering algorithm and an A-star search algorithm to schedule the automated guided vehicle, thereby solving the problem that the existing automated guided vehicle scheduling method has complex calculations when avoiding collisions of automated guided vehicles, resulting in excessive scheduling time. Automatic guided vehicles are scheduled through priority control schemes and local obstacle avoidance routes, thereby avoiding collisions of automated guided vehicles and improving the scheduling efficiency of automated guided vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flowchart of an automated guided vehicle scheduling method provided in an embodiment of the present application.

[0044] Figure 2 A schematic diagram of the structure of an automatic guided vehicle dispatching device provided in an embodiment of the present application.

[0045] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0046] Figure 4 This is a schematic diagram of the structure of the node path map.

[0047] Figure 5 Schematic diagram of the local obstacle avoidance route.

[0048] Explanation of reference numerals: 1. Acquisition module; 2. Allocation module; 3. Generation module; 4. Design module; 5. Scheduling module; 301. Processor; 302. Memory; 303. Communication bus. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0050] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0051] Please refer to Figure 1 , Figure 1 An automatic guided vehicle scheduling method in some embodiments of the present application is used to schedule an automatic guided vehicle, comprising the steps of:

[0052] Step S101, obtaining task information, and obtaining the operating status and position information of all automatic guided vehicles in the node path map; the task information includes a target task node of at least one target task and a priority ranking of each target task; the operating status includes an idle state, a moving state, and a working state;

[0053] Step S102, according to the position information, each target task in the task information is assigned to an AGV in an idle state that has the smallest straight-line distance to a target task node corresponding to each target task, and a corresponding running path is generated to guide the AGV assigned to the target task to enter a moving state and move toward the corresponding target task node based on the running path;

[0054] Step S103, taking the preset first time as a period, using a density-based clustering algorithm, according to the relative size relationship between the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion and the preset minimum density, combined with the priority ranking of each target task, periodically generating a neighborhood priority control plan;

[0055] Step S104, periodically detecting whether there are any occupied route points in the running paths of the moving automated guided vehicles with a preset second time as a period, and when it is detected that there are any occupied route points in the running paths of any moving automated guided vehicles, designing a local obstacle avoidance route at the corresponding position by using an A-star search algorithm;

[0056] Step S105: scheduling all automatic guided vehicles in the node path map based on the priority control scheme and / or the local obstacle avoidance route.

[0057] The automatic guided vehicle scheduling method generates an operation path and designs a corresponding priority control scheme and a corresponding local obstacle avoidance route according to the operation status and position information of the automatic guided vehicle through a density-based clustering algorithm and an A-star search algorithm, so as to schedule the automatic guided vehicle, thereby solving the problem that the existing automatic guided vehicle scheduling method has a relatively complex calculation when avoiding collisions of the automatic guided vehicle, resulting in a long scheduling time. The automatic guided vehicle is scheduled through a priority control scheme and a local obstacle avoidance route, thereby avoiding collisions of the automatic guided vehicle and improving the scheduling efficiency of the automatic guided vehicle.

[0058] Specifically, the node path map includes several workstations, multiple nodes, and paths formed by connecting adjacent nodes; wherein, nodes include path nodes and task nodes, and task nodes include entry nodes and exit nodes. Before task allocation, task nodes are not divided into entry nodes and exit nodes. Then, for the node path map itself, each workstation is set with two task nodes, which are used as entry nodes and exit nodes respectively (the functions of the two task nodes are not fixed, but are related to the movement direction of the automatic guided vehicle. When the automatic guided vehicle drives to the workstation, the task node that it reaches first is the entry node, and the other task node is used as the exit node).

[0059] like Figure 4 As shown, Figure 4 It is a structural diagram of the node path map, where A1, A2, A3, B1, B2, B3, C1, C2, and C3 are path nodes, D1, D2, D3, D4, D5, D6, D7, and D8 are task nodes, and N1, N2, N3, and N4 are workstations. When the automatic guided vehicle drives towards the workstation, the first task node that the automatic guided vehicle enters is determined as the entry node, and the other task node is determined as the exit node.

[0060] Specifically, in step S101, task information is obtained, and the operating status and position information of all automated guided vehicles in the node path map are obtained. The task information includes the task content, quantity, priority ranking, target task station (i.e., the station corresponding to the target task) and the corresponding target task node (i.e., the task node corresponding to the target task station); the operating status includes idle state, moving state and working state, wherein the idle state is the stop moving state of the automated guided vehicle when no task is assigned, the moving state is the moving state of the automated guided vehicle when it is moving, and the working state is the stop moving state of the automated guided vehicle when it is waiting at the task node or working at the task node.

[0061] Specifically, in step S102, based on the position information of each automated guided vehicle, all target tasks in the task information are assigned to an idle automated guided vehicle that has the shortest straight-line distance to the target task node corresponding to the target task (since each target task has two target task nodes, the target task node with the smaller straight-line distance is used, that is, the smaller value of the straight-line distances from the automated guided vehicle to the two target task nodes corresponding to the same target task is used as the effective straight-line distance from the automated guided vehicle to the target task node corresponding to the target task, which is used for comparison with the effective straight-line distances from other automated guided vehicles to the target task), and a corresponding running path is generated according to a minimum path generation method (existing technologies such as A-star search algorithm, ant colony algorithm, etc. may be used), and after the automated guided vehicle assigned to the target task enters a motion state based on the running path, it moves with the target task node as the target.

[0062] Specifically, in step S103, with the preset first time as a period, a density-based clustering algorithm is used, according to the relative size relationship between the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion and the preset minimum density, combined with the priority ranking of each target task, to periodically generate a priority control scheme for the neighborhood, including periodically executing the following steps:

[0063] The number of moving AGVs in the neighborhood of any moving AGV is calculated by using a density-based clustering algorithm.

[0064] When the number is greater than or equal to the preset minimum density, the automatic guided vehicles in motion in the neighborhood are sorted in descending order according to the priority ranking of the target tasks assigned to the automatic guided vehicles in motion in the neighborhood to obtain a priority control sorting;

[0065] Based on the priority control ranking, a priority control plan for the neighborhood is generated.

[0066] In step S103, all the automatic guided vehicles in motion are traversed by a density-based clustering algorithm with a preset first time as a period to control the automatic guided vehicles. The preset first time can be set according to actual needs.

[0067] Specifically, in step S103, the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion is calculated by using a density-based clustering algorithm, including:

[0068] Taking any moving automated guided vehicle as the center and a preset distance as the radius, a circle area with the moving automated guided vehicle as the core point is obtained;

[0069] Traverse all the circle areas, and when there are other core points in the circle area of ​​any core point, merge the circle areas of other core points into the circle area of ​​any core point to obtain the neighborhood of any core point;

[0070] The number of automatic guided vehicles in motion within the neighborhood of any core point is counted.

[0071] In step S103, all the automatic guided vehicles in motion are traversed with a preset first time as a period, and circles are drawn with the automatic guided vehicle in motion as the center and a preset distance as the radius to obtain a circle area of ​​the automatic guided vehicle in motion. The automatic guided vehicle in motion is the core point of the circle area. After each circle area is formed, if there are other core points in the circle area except the core point corresponding to the circle area, the circle areas of the other core points are merged into the circle area to obtain a neighborhood of the core point corresponding to the circle area, and the number of automatic guided vehicles in motion in the neighborhood is calculated.

[0072] In step S103, after calculating the number of automatic guided vehicles in motion in the neighborhood, the relative size relationship between the number of automatic guided vehicles in motion in the neighborhood and the preset minimum density is compared. When the number of automatic guided vehicles in motion in any neighborhood is greater than or equal to the preset minimum density, the automatic guided vehicles in motion in the neighborhood are sorted in descending order according to the priority ranking of the target task to obtain a priority control sorting. Among them, the preset minimum density can be set according to actual needs, and is generally set to 2.

[0073] When the number of the automatic guided vehicles in motion in any neighborhood is less than a preset minimum density, the automatic guided vehicles in motion in the neighborhood operate normally according to the corresponding operation path.

[0074] Specifically, in step S103, a priority control scheme for the neighborhood is generated according to the priority control ranking, including:

[0075] Based on the priority control ranking, the automatic guided vehicles in motion are selected as control objects in order of ranking;

[0076] The control criterion is to stop the automatic guided vehicles other than the control objects in the neighborhood when the driving control object continues to run, and the control target is to drive the control object to leave the area corresponding to the neighborhood. Combined with the priority control sorting, a priority control scheme for the neighborhood is generated (that is, the priority control scheme for the neighborhood includes priority control sorting, control criteria and control targets).

[0077] In step S103, according to the ranking order of the priority control sorting, the automatic guided vehicles in motion are selected as the control objects in turn, and the automatic guided vehicles other than the control objects in the neighborhood are controlled to stop moving while the driving control objects continue to run as the control criterion, and the area corresponding to the driving control objects to leave the neighborhood (the area corresponding to the neighborhood is the area connected by all the circle areas in the neighborhood) is the control target (after the traversal is completed, the neighborhood is fixed in the corresponding area until the number of automatic guided vehicles in motion in the neighborhood is less than the preset minimum density). Combined with the priority control sorting, a priority control scheme for the neighborhood is generated to control the automatic guided vehicles in motion to leave the area where the corresponding neighborhood is located in turn, so as to avoid collisions between the automatic guided vehicles when moving. After the number of automatic guided vehicles in motion in the neighborhood is less than the preset minimum density, the neighborhood is no longer retained.

[0078] In some embodiments, when an automated guided vehicle in motion in any neighborhood operates according to a priority control scheme, if other automated guided vehicles enter the area where the neighborhood is located, it is necessary to recalculate the priority control ranking of the neighborhood after the current controlled object leaves, and adjust the priority control scheme according to the recalculated priority control ranking, so that the adjusted priority control scheme is executed after the current controlled object leaves the area where the neighborhood is located.

[0079] Specifically, in step S104, whether there are occupied route points in the running paths of the various moving automatic guided vehicles is periodically detected with the preset second time as a period. When it is detected that there are occupied route points in the running paths of any moving automatic guided vehicle, a local obstacle avoidance route is designed at the corresponding position by using the A-star search algorithm, including:

[0080] According to a preset interval length, the running path of any automatic guided vehicle in motion is divided into a plurality of route points;

[0081] Taking the preset second time as a period, according to the preset route point traversal order, it is periodically determined whether there is an automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point between the current route point and the target task node of each automatic guided vehicle in motion; if so, the route point of the automatic guided vehicle in a stopped moving state within the preset obstacle range is determined to be an occupied route point, and a local obstacle avoidance route is designed at the location of the occupied route point through the A-star search algorithm; if not, it is determined that there is no occupied route point in the running path, and there is no need to adjust the running path.

[0082] In step S104, the running path of the automatic guided vehicle in motion is divided into a plurality of route points according to a preset interval length (the route points may be directly divided after the running path is formed). The preset interval length may be set according to actual conditions.

[0083] Taking the preset second time as a cycle (the preset second time can be set according to actual needs and can be equal to the preset first time), according to the preset route point traversal order (such as according to the traversal order from the target task node to the current route point or according to the traversal order from the current route point to the target task node), periodically determine whether there is an automatic guided vehicle in a stopped moving state within the preset obstacle range at each route point between the current route point and the target task node on the running path of the automatic guided vehicle in motion, so as to determine whether it is necessary to generate a local obstacle avoidance route. Among them, the preset obstacle range can be set according to actual conditions. The automatic guided vehicle in a stopped moving state includes an automatic guided vehicle in an idle state, an automatic guided vehicle in a working state, and an automatic guided vehicle in a stopped moving state. The position of the automatic guided vehicle in a stopped moving state will not change within a certain period of time.

[0084] When there is an automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point on the running path of the automatic guided vehicle in motion from the current route point to the target task node, the route point of the automatic guided vehicle in the stopped moving state within the preset obstacle range is determined to be an occupied route point, and a local obstacle avoidance route is designed at the location of the occupied route point through the A-star search algorithm, so that the automatic guided vehicle in motion avoids the automatic guided vehicle in the stopped moving state, thereby preventing the automatic guided vehicle from colliding.

[0085] When there is no automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point on the running path of the automatic guided vehicle in motion from the current route point to the target task node, it is determined that there is no occupied route point in the running path of the automatic guided vehicle in motion, and there is no need to adjust the running path.

[0086] Specifically, in step S104, a local obstacle avoidance route is designed at the location of the occupied route point by using the A-star search algorithm, including:

[0087] Take the occupied route point as the center and draw a circle with the preset obstacle avoidance radius to obtain the obstacle avoidance area;

[0088] On the running path to which the occupied route point belongs, a route point closest to the obstacle avoidance area is selected at the upstream and downstream of the obstacle avoidance area;

[0089] The two selected route points are used as the starting point and end point of the local obstacle avoidance route, and the local obstacle avoidance route at the location of the occupied route point is calculated through the A-star search algorithm.

[0090] In step S104, a circle is drawn with a preset obstacle avoidance radius at the occupied route point on the running path (the preset obstacle avoidance radius can be set according to actual needs) to obtain an obstacle avoidance area, and a route point closest to the obstacle avoidance area is selected at the upstream and downstream of the obstacle avoidance area on the running path to which the occupied route point belongs (that is, a route point closest to the obstacle avoidance area is selected between the occupied route point and the current route point of the automatic guided vehicle, and a route point closest to the obstacle avoidance area is selected between the occupied route point and the target task node, to obtain two selected route points), and the two selected route points are used as the starting point and end point of the local obstacle avoidance route, and a local obstacle avoidance route is designed from the starting point to the end point through the A-star search algorithm, so that the automatic guided vehicle in motion moves around the automatic guided vehicle in the stopped moving state to avoid collision of the automatic guided vehicle. Among them, the process of designing a local obstacle avoidance route through the A-star search algorithm is a prior art and will not be described in detail here.

[0091] When an AGV enters a task node, the corresponding entry and exit nodes will be marked as occupied, and all subsequent AGVs that want to enter the task node (entry and exit nodes) will wait at a node outside the task node. When an AGV leaves a task node, the entry and exit nodes of the task node will automatically be unoccupied. Therefore, the AGV waiting to enter the task node will be in a stopped state, and the AGV in motion will move through a local obstacle avoidance route to bypass the AGV waiting to enter the task node and avoid collisions between AGVs.

[0092] like Figure 5 As shown, Figure 5 The schematic diagram of the local obstacle avoidance route is shown in Figure 1, where rectangles P1, P2, and P3 are automatic guided vehicles, curve M is the local obstacle avoidance route, and dotted line L is the running path. Figure 5 As can be seen from the figure, the automatic guided vehicle P1 moves around the automatic guided vehicle P2 which is in a stopped moving state via the local obstacle avoidance route M.

[0093] Specifically, in step S105, after generating the priority control scheme and / or the local obstacle avoidance route, all the automatic guided vehicles in the node path map need to be scheduled immediately. After executing the priority control scheme and / or leaving the local obstacle avoidance route, the automatic guided vehicle moves according to the original operating path.

[0094] In specific applications, a fixed parking position or parking area can be set according to actual conditions, so that the automatic guided vehicle can automatically navigate to the corresponding parking position or parking area after completing the target task according to the task content; or, no fixed parking position or parking area is set, and after the automatic guided vehicle completes the target task according to the task content, it can select any position to park in the nearest path node, the path formed by the nearest node, and the free area next to the nearest path.

[0095] As can be seen from the above, the automatic guided vehicle scheduling method obtains task information and the operating status and position information of all automatic guided vehicles in the node path map, and according to the position information, assigns each target task in the task information to the automatic guided vehicle in an idle state with the smallest straight-line distance to the target task node corresponding to each target task, and generates a corresponding operating path to guide the automatic guided vehicle assigned to the target task to enter a moving state and move toward the corresponding target task node based on the operating path. With a preset first time as a period, a density-based clustering algorithm is used, and according to the relative size relationship between the number of automatic guided vehicles in a moving state and a preset minimum density in the neighborhood of any automatic guided vehicle in a moving state, combined with the priority ranking of each target task, a priority control scheme for the neighborhood is periodically generated, and with a preset second time as a period, each automatic guided vehicle in a moving state is periodically detected. Whether there is an occupied route point in the running path of the automatic guided vehicle, when it is detected that there is an occupied route point in the running path of any automatic guided vehicle in motion, a local obstacle avoidance route is designed at the corresponding position through the A-star search algorithm, and all automatic guided vehicles in the node path map are scheduled based on the priority control scheme and / or the local obstacle avoidance route; thereby, through the density-based clustering algorithm and the A-star search algorithm, according to the running status and position information of the automatic guided vehicle, the running path is generated and the corresponding priority control scheme and the corresponding local obstacle avoidance route are designed to schedule the automatic guided vehicle, so as to solve the problem that the existing automatic guided vehicle scheduling method is more complicated in calculation when avoiding collision of the automatic guided vehicle, resulting in too long scheduling time, and the automatic guided vehicle is scheduled through the priority control scheme and the local obstacle avoidance route, so as to avoid the collision of the automatic guided vehicle and improve the scheduling efficiency of the automatic guided vehicle.

[0096] refer to Figure 2 The present application provides an automatic guided vehicle scheduling device for scheduling an automatic guided vehicle, comprising:

[0097] Acquisition module 1 is used to acquire task information, and to acquire the operation status and position information of all automatic guided vehicles in the node path map; the task information includes the target task node of at least one target task and the priority ranking of each target task; the operation status includes the idle state, the moving state and the working state;

[0098] The allocation module 2 is used to allocate each target task in the task information to an idle automatic guided vehicle with the smallest straight-line distance to the target task node corresponding to each target task according to the position information, and generate a corresponding running path to guide the automatic guided vehicle assigned to the target task to enter a moving state and move toward the corresponding target task node based on the running path;

[0099] A generation module 3 is used to periodically generate a priority control scheme for a neighborhood by using a density-based clustering algorithm based on a preset first time period, according to a relative size relationship between the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion and a preset minimum density, combined with a priority ranking of each target task;

[0100] Design module 4, used for periodically detecting whether there are occupied route points in the running paths of the various automatic guided vehicles in motion with a preset second time as a period, and when it is detected that there are occupied route points in the running paths of any automatic guided vehicle in motion, designing a local obstacle avoidance route at a corresponding position by using an A-star search algorithm;

[0101] The scheduling module 5 is used to schedule all automatic guided vehicles in the node path map based on the priority control scheme and / or the local obstacle avoidance route.

[0102] The automatic guided vehicle scheduling device generates an operation path and designs a corresponding priority control scheme and a corresponding local obstacle avoidance route according to the operation status and position information of the automatic guided vehicle through a density-based clustering algorithm and an A-star search algorithm, so as to schedule the automatic guided vehicle, thereby solving the problem that the existing automatic guided vehicle scheduling method has a relatively complex calculation when avoiding collisions of the automatic guided vehicle, resulting in a long scheduling time. The automatic guided vehicle is scheduled through a priority control scheme and a local obstacle avoidance route, thereby avoiding collisions of the automatic guided vehicle and improving the scheduling efficiency of the automatic guided vehicle.

[0103] Specifically, the node path map includes several workstations, multiple nodes, and paths formed by connecting adjacent nodes; wherein, nodes include path nodes and task nodes, and task nodes include entry nodes and exit nodes. Before task allocation, task nodes are not divided into entry nodes and exit nodes. Then, for the node path map itself, each workstation is set with two task nodes, which are used as entry nodes and exit nodes respectively (the functions of the two task nodes are not fixed, but are related to the movement direction of the automatic guided vehicle. When the automatic guided vehicle drives to the workstation, the task node that it reaches first is the entry node, and the other task node is used as the exit node).

[0104] like Figure 4 As shown, Figure 4It is a structural diagram of the node path map, where A1, A2, A3, B1, B2, B3, C1, C2, and C3 are path nodes, D1, D2, D3, D4, D5, D6, D7, and D8 are task nodes, and N1, N2, N3, and N4 are workstations. When the automatic guided vehicle drives towards the workstation, the first task node that the automatic guided vehicle enters is determined as the entry node, and the other task node is determined as the exit node.

[0105] Specifically, when the acquisition module 1 is executed, it acquires the task information, and acquires the operation status and position information of all the automatic guided vehicles in the node path map. Among them, the task information includes the task content, quantity, priority ranking, target task station (i.e., the station corresponding to the target task) and the corresponding target task node (i.e., the task node corresponding to the target task station); the operation status includes the idle state, the moving state and the working state, among which the idle state is the stop moving state of the automatic guided vehicle when it is not assigned a task, the moving state is the moving state of the automatic guided vehicle when it is moving, and the working state is the stop moving state of the automatic guided vehicle when it is waiting at the task node or working at the task node.

[0106] Specifically, when the allocation module 2 is executed, it allocates all target tasks in the task information to the idle automated guided vehicle that has the shortest straight-line distance to the target task node corresponding to the target task according to the position information of each automated guided vehicle (since each target task has two target task nodes corresponding to the target task, the target task node with the smaller straight-line distance is used, that is, the smaller value of the straight-line distances from the automated guided vehicle to the two target task nodes corresponding to the same target task is used as the effective straight-line distance from the automated guided vehicle to the target task node corresponding to the target task, which is used for comparison with the effective straight-line distances from other automated guided vehicles to the target task), and generates a corresponding running path according to the minimum path generation method (existing technologies such as A-star search algorithm, ant colony algorithm, etc. can be used), and after the automated guided vehicle assigned to the target task enters a motion state based on the running path, it moves with the target task node as the target.

[0107] Specifically, the generation module 3 periodically performs the following steps when periodically generating a priority control scheme for a neighborhood based on a density-based clustering algorithm according to the relative size relationship between the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion and a preset minimum density, combined with the priority ranking of each target task, with the preset first time as a period:

[0108] The number of moving AGVs in the neighborhood of any moving AGV is calculated by using a density-based clustering algorithm.

[0109] When the number is greater than or equal to the preset minimum density, the automatic guided vehicles in motion in the neighborhood are sorted in descending order according to the priority ranking of the target tasks assigned to the automatic guided vehicles in motion in the neighborhood to obtain a priority control sorting;

[0110] Based on the priority control ranking, a priority control plan for the neighborhood is generated.

[0111] When the generation module 3 is executed, it takes the preset first time as a period, and traverses all the automatic guided vehicles in motion through a density-based clustering algorithm to control the automatic guided vehicles. The preset first time can be set according to actual needs.

[0112] Specifically, when the generation module 3 calculates the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion by using a density-based clustering algorithm, it executes:

[0113] Taking any moving automated guided vehicle as the center and a preset distance as the radius, a circle area with the moving automated guided vehicle as the core point is obtained;

[0114] Traverse all the circle areas, and when there are other core points in the circle area of ​​any core point, merge the circle areas of other core points into the circle area of ​​any core point to obtain the neighborhood of any core point;

[0115] The number of automatic guided vehicles in motion within the neighborhood of any core point is counted.

[0116] When the generation module 3 is executed, it takes the preset first time as a period, traverses all the automatic guided vehicles in motion, and draws a circle with the automatic guided vehicle in motion as the center and the preset distance as the radius to obtain the circle area of ​​the automatic guided vehicle in motion. The automatic guided vehicle in motion is the core point of the circle area. After each circle area is formed, if there are other core points in the circle area except the core point corresponding to the circle area, the circle areas of other core points are merged into the circle area to obtain the neighborhood of the core point corresponding to the circle area, and the number of automatic guided vehicles in motion in the neighborhood is calculated.

[0117] When the generation module 3 is executed, after calculating the number of automatic guided vehicles in motion in the neighborhood, the relative size relationship between the number of automatic guided vehicles in motion in the neighborhood and the preset minimum density is compared. When the number of automatic guided vehicles in motion in any neighborhood is greater than or equal to the preset minimum density, the automatic guided vehicles in motion in the neighborhood are sorted in descending order according to the priority ranking of the target task to obtain a priority control sorting. Among them, the preset minimum density can be set according to actual needs, and is generally set to 2.

[0118] When the number of the automatic guided vehicles in motion in any neighborhood is less than a preset minimum density, the automatic guided vehicles in motion in the neighborhood operate normally according to the corresponding operation path.

[0119] Specifically, when the generation module 3 generates the priority control scheme of the neighborhood according to the priority control sorting, it executes:

[0120] Based on the priority control ranking, the automatic guided vehicles in motion are selected as control objects in order of ranking;

[0121] The control criterion is to stop the automatic guided vehicles other than the control objects in the neighborhood when the driving control object continues to run, and the control target is to drive the control object to leave the area corresponding to the neighborhood. Combined with the priority control sorting, a priority control scheme for the neighborhood is generated (that is, the priority control scheme for the neighborhood includes priority control sorting, control criteria and control targets).

[0122] When the generation module 3 is executed, according to the ranking order of the priority control sorting, the automatic guided vehicles in motion are selected as the control objects in turn, and the automatic guided vehicles other than the control objects in the neighborhood are controlled to stop moving when the driving control objects continue to run as the control criterion, and the area corresponding to the driving control objects to leave the neighborhood (the area corresponding to the neighborhood is the area connected by all the circle areas in the neighborhood) is used as the control target (after the traversal is completed, the neighborhood is fixed in the corresponding area until the number of automatic guided vehicles in motion in the neighborhood is less than the preset minimum density). Combined with the priority control sorting, a priority control scheme for the neighborhood is generated to control the automatic guided vehicles in motion to leave the area where the corresponding neighborhood is located in turn, so as to avoid collisions between the automatic guided vehicles when moving. After the number of automatic guided vehicles in motion in the neighborhood is less than the preset minimum density, the neighborhood is no longer retained.

[0123] In some embodiments, when an automated guided vehicle in motion in any neighborhood operates according to a priority control scheme, if other automated guided vehicles enter the area where the neighborhood is located, it is necessary to recalculate the priority control ranking of the neighborhood after the current controlled object leaves, and adjust the priority control scheme according to the recalculated priority control ranking, so that the adjusted priority control scheme is executed after the current controlled object leaves the area where the neighborhood is located.

[0124] Specifically, the design module 4 periodically detects whether there are occupied route points in the running paths of the automatic guided vehicles in motion at a preset second time period. When it is detected that there are occupied route points in the running paths of any automatic guided vehicle in motion, the local obstacle avoidance route is designed at the corresponding position by the A-star search algorithm, and the following is executed:

[0125] According to a preset interval length, the running path of any automatic guided vehicle in motion is divided into a plurality of route points;

[0126] Taking the preset second time as a period, according to the preset route point traversal order, it is periodically determined whether there is an automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point between the current route point and the target task node of each automatic guided vehicle in motion; if so, the route point of the automatic guided vehicle in a stopped moving state within the preset obstacle range is determined to be an occupied route point, and a local obstacle avoidance route is designed at the location of the occupied route point through the A-star search algorithm; if not, it is determined that there is no occupied route point in the running path, and there is no need to adjust the running path.

[0127] When the design module 4 is executed, the running path of the automatic guided vehicle in motion is divided into a plurality of route points according to a preset interval length (the route points can be directly divided after the running path is formed). The preset interval length can be set according to actual conditions.

[0128] Taking the preset second time as a cycle (the preset second time can be set according to actual needs and can be equal to the preset first time), according to the preset route point traversal order (such as according to the traversal order from the target task node to the current route point or according to the traversal order from the current route point to the target task node), periodically determine whether there is an automatic guided vehicle in a stopped moving state within the preset obstacle range at each route point between the current route point and the target task node on the running path of the automatic guided vehicle in motion, so as to determine whether it is necessary to generate a local obstacle avoidance route. Among them, the preset obstacle range can be set according to actual conditions. The automatic guided vehicle in a stopped moving state includes an automatic guided vehicle in an idle state, an automatic guided vehicle in a working state, and an automatic guided vehicle in a stopped moving state. The position of the automatic guided vehicle in a stopped moving state will not change within a certain period of time.

[0129] When there is an automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point on the running path of the automatic guided vehicle in motion from the current route point to the target task node, the route point of the automatic guided vehicle in the stopped moving state within the preset obstacle range is determined to be an occupied route point, and a local obstacle avoidance route is designed at the location of the occupied route point through the A-star search algorithm, so that the automatic guided vehicle in motion avoids the automatic guided vehicle in the stopped moving state, thereby preventing the automatic guided vehicle from colliding.

[0130] When there is no automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point on the running path of the automatic guided vehicle in motion from the current route point to the target task node, it is determined that there is no occupied route point in the running path of the automatic guided vehicle in motion, and there is no need to adjust the running path.

[0131] Specifically, when the design module 4 designs a local obstacle avoidance route at the location of the occupied route point through the A-star search algorithm, it executes:

[0132] Take the occupied route point as the center and draw a circle with the preset obstacle avoidance radius to obtain the obstacle avoidance area;

[0133] On the running path to which the occupied route point belongs, a route point closest to the obstacle avoidance area is selected at the upstream and downstream of the obstacle avoidance area;

[0134] The two selected route points are used as the starting point and end point of the local obstacle avoidance route, and the local obstacle avoidance route at the location of the occupied route point is calculated through the A-star search algorithm.

[0135] When the design module 4 is executed, a circle is drawn with a preset obstacle avoidance radius at the occupied route point on the running path (the preset obstacle avoidance radius can be set according to actual needs) to obtain an obstacle avoidance area, and a route point closest to the obstacle avoidance area is selected at the upstream and downstream of the obstacle avoidance area on the running path to which the occupied route point belongs (that is, a route point closest to the obstacle avoidance area is selected between the occupied route point and the current route point of the automatic guided vehicle, and a route point closest to the obstacle avoidance area is selected between the occupied route point and the target task node, to obtain two selected route points), and the two selected route points are used as the starting point and end point of the local obstacle avoidance route. Through the A-star search algorithm, a local obstacle avoidance route is designed from the starting point to the end point, so that the automatic guided vehicle in motion moves around the automatic guided vehicle in the stopped moving state to avoid collisions between the automatic guided vehicles. Among them, the process of designing a local obstacle avoidance route through the A-star search algorithm is a prior art and will not be described in detail here.

[0136] When an AGV enters a task node, the corresponding entry and exit nodes will be marked as occupied, and all subsequent AGVs that want to enter the task node (entry and exit nodes) will wait at a node outside the task node. When an AGV leaves a task node, the entry and exit nodes of the task node will automatically be unoccupied. Therefore, the AGV waiting to enter the task node will be in a stopped state, and the AGV in motion will move through a local obstacle avoidance route to bypass the AGV waiting to enter the task node and avoid collisions between AGVs.

[0137] like Figure 5 As shown, Figure 5 The schematic diagram of the local obstacle avoidance route is shown in Figure 1, where rectangles P1, P2, and P3 are automatic guided vehicles, curve M is the local obstacle avoidance route, and dotted line L is the running path. Figure 5 As can be seen from the figure, the automatic guided vehicle P1 moves around the automatic guided vehicle P2 which is in a stopped moving state via the local obstacle avoidance route M.

[0138] Specifically, when the scheduling module 5 is executed, after generating the priority control plan and / or the local obstacle avoidance route, it is necessary to immediately schedule all the automatic guided vehicles in the node path map. After executing the priority control plan and / or leaving the local obstacle avoidance route, the automatic guided vehicle moves according to the original operating path.

[0139] In specific applications, a fixed parking position or parking area can be set according to actual conditions, so that the automatic guided vehicle can automatically navigate to the corresponding parking position or parking area after completing the target task according to the task content; or, no fixed parking position or parking area is set, and after the automatic guided vehicle completes the target task according to the task content, it can select any position to park in the nearest path node, the path formed by the nearest node, and the free area next to the nearest path.

[0140] As can be seen from the above, the automatic guided vehicle scheduling device obtains task information and the operating status and position information of all automatic guided vehicles in the node path map, and according to the position information, assigns each target task in the task information to the automatic guided vehicle in an idle state with the smallest straight-line distance to the target task node corresponding to each target task, and generates a corresponding operating path to guide the automatic guided vehicle assigned to the target task to enter a moving state and move toward the corresponding target task node based on the operating path. With a preset first time as a period, a density-based clustering algorithm is used, and according to the relative size relationship between the number of automatic guided vehicles in a moving state and a preset minimum density in the neighborhood of any automatic guided vehicle in a moving state, combined with the priority ranking of each target task, a priority control scheme for the neighborhood is periodically generated, and with a preset second time as a period, each automatic guided vehicle in a moving state is periodically detected. Whether there is an occupied route point in the running path of the automatic guided vehicle, when it is detected that there is an occupied route point in the running path of any automatic guided vehicle in motion, a local obstacle avoidance route is designed at the corresponding position through the A-star search algorithm, and all automatic guided vehicles in the node path map are scheduled based on the priority control scheme and / or the local obstacle avoidance route; thereby, through the density-based clustering algorithm and the A-star search algorithm, according to the running status and position information of the automatic guided vehicle, the running path is generated and the corresponding priority control scheme and the corresponding local obstacle avoidance route are designed to schedule the automatic guided vehicle, so as to solve the problem that the existing automatic guided vehicle scheduling method is more complicated in calculation when avoiding collision of the automatic guided vehicle, resulting in too long scheduling time, and the automatic guided vehicle is scheduled through the priority control scheme and the local obstacle avoidance route, so as to avoid the collision of the automatic guided vehicle and improve the scheduling efficiency of the automatic guided vehicle.

[0141] Please refer to Figure 3 , Figure 3A schematic diagram of the structure of an electronic device provided in an embodiment of the present application, the present application provides an electronic device, including: a processor 301 and a memory 302, the processor 301 and the memory 302 are interconnected and communicate with each other through a communication bus 303 and / or other forms of connection mechanisms (not shown), the memory 302 stores a computer program executable by the processor 301, when the electronic device is running, the processor 301 executes the computer program to execute the automatic guided vehicle scheduling method in any optional implementation of the above embodiment, to achieve the following functions: obtaining task information, and obtaining the operating status and position information of all automatic guided vehicles in the node path map, according to the position information, assigning each target task in the task information to the automatic guided vehicle in an idle state with the smallest straight-line distance to the target task node corresponding to each target task, and generating a corresponding operation path for guiding The automatic guided vehicle assigned to the target task enters a moving state and moves toward the corresponding target task node based on the running path. With a preset first time as a period, a density-based clustering algorithm is used. According to the relative size relationship between the number of automatic guided vehicles in a moving state and a preset minimum density in the neighborhood of any automatic guided vehicle in a moving state, combined with the priority ranking of each target task, a priority control scheme for the neighborhood is periodically generated. With a preset second time as a period, it is periodically detected whether there are occupied route points in the running path of each automatic guided vehicle in a moving state. When it is detected that there are occupied route points in the running path of any automatic guided vehicle in a moving state, a local obstacle avoidance route is designed at the corresponding position through the A-star search algorithm. Based on the priority control scheme and / or the local obstacle avoidance route, all automatic guided vehicles in the node path map are scheduled.

[0142] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the automatic guided vehicle scheduling method in any optional implementation of the above embodiment is executed to achieve the following functions: obtaining task information, and obtaining the operating status and position information of all automatic guided vehicles in a node path map, and assigning each target task in the task information to an automatic guided vehicle in an idle state with the smallest straight-line distance to a target task node corresponding to each target task according to the position information, and generating a corresponding operating path to guide the automatic guided vehicle assigned to the target task to enter a motion state and move toward the corresponding target task node based on the operating path, with a preset first time as a period. , through a density-based clustering algorithm, according to the relative size relationship between the number of automatic guided vehicles in motion in the neighborhood of any automatic guided vehicle in motion and a preset minimum density, combined with the priority ranking of each target task, a priority control scheme for the neighborhood is periodically generated, and with a preset second time as a period, whether there are occupied route points in the running path of each automatic guided vehicle in motion is periodically detected. When it is detected that there are occupied route points in the running path of any automatic guided vehicle in motion, a local obstacle avoidance route is designed at the corresponding position through the A-star search algorithm, and all automatic guided vehicles in the node path map are scheduled based on the priority control scheme and / or the local obstacle avoidance route. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0143] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0144] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0145] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0146] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0147] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An automatic guided vehicle scheduling method for scheduling an automatic guided vehicle, characterized in that: Includes steps: Acquire task information, and acquire the operation status and position information of all automatic guided vehicles in the node path map; the task information includes a target task node of at least one target task and a priority ranking of each target task; the operation status includes an idle state, a moving state, and a working state; According to the position information, each target task in the task information is assigned to an automatic guided vehicle in the idle state whose straight-line distance to the target task node corresponding to each target task is the smallest, and a corresponding running path is generated to guide the automatic guided vehicle assigned to the target task to enter the moving state and move toward the corresponding target task node based on the running path; Taking the preset first time as a period, using a density-based clustering algorithm, according to the relative size relationship between the number of automatic guided vehicles in the moving state in the neighborhood of any automatic guided vehicle in the moving state and a preset minimum density, combined with the priority ranking of each of the target tasks, periodically generating a priority control scheme for the neighborhood; periodically detecting whether there are any occupied route points in the running paths of the automatic guided vehicles in the moving state with a preset second time as a period, and when it is detected that there are any occupied route points in the running paths of any automatic guided vehicles in the moving state, designing a local obstacle avoidance route at a corresponding position by using an A-star search algorithm; Based on the priority control scheme and / or the local obstacle avoidance route, all automatic guided vehicles in the node path map are scheduled; Taking the preset first time as a period, using a density-based clustering algorithm, according to the relative size relationship between the number of automatic guided vehicles in the moving state in the neighborhood of any automatic guided vehicle in the moving state and the preset minimum density, combined with the priority ranking of each of the target tasks, a priority control scheme for the neighborhood is periodically generated, including periodically performing the following steps: Calculating the number of automatic guided vehicles in the motion state in the neighborhood of any automatic guided vehicle in the motion state by using the density-based clustering algorithm; When the number is greater than or equal to the preset minimum density, the automatic guided vehicles in the neighborhood in the moving state are sorted in descending order according to the priority ranking of the target tasks assigned to the automatic guided vehicles in the moving state in the neighborhood to obtain a priority control sorting; Generating a priority control scheme for the neighborhood according to the priority control ranking; The number of moving AGVs in the neighborhood of any moving AGV is calculated using a density-based clustering algorithm, including: Taking any automatic guided vehicle in the motion state as the center and a preset distance as the radius, a circle area with any automatic guided vehicle in the motion state as the core point is obtained; Traversing all the circle areas, when there are other core points in the circle area of ​​any core point, merging the circle areas of the other core points into the circle area of ​​any core point to obtain the neighborhood of any core point; The number of automatic guided vehicles in the motion state in the neighborhood of any core point is obtained by counting.

2. The automatic guided vehicle dispatching method according to claim 1, characterized in that: The node path map includes multiple nodes and paths formed by connecting adjacent nodes; wherein the nodes include path nodes and task nodes, and the task nodes include inbound nodes and outbound nodes.

3. The automatic guided vehicle dispatching method according to claim 1, characterized in that: According to the priority control ranking, a priority control scheme for the neighborhood is generated, including: Based on the priority control ranking, the automatic guided vehicles in the motion state are selected as control objects in order of ranking; The control criterion is to control the automatic guided vehicles other than the control objects in the neighborhood to stop moving while the driven control objects continue to run, and the control target is to drive the controlled objects to leave the area corresponding to the neighborhood. Combined with the priority control sorting, a priority control scheme for the neighborhood is generated.

4. The automatic guided vehicle dispatching method according to claim 1, characterized in that: Taking a preset second time as a period, periodically detecting whether there are occupied route points in the running paths of the automatic guided vehicles in the moving state, and when it is detected that there are occupied route points in the running paths of any automatic guided vehicle in the moving state, designing a local obstacle avoidance route at a corresponding position through an A-star search algorithm, including: According to a preset interval length, dividing the running path of any automatic guided vehicle in the moving state into a plurality of route points; Taking the preset second time as a period, according to the preset route point traversal order, it is periodically determined whether there is an automatic guided vehicle in a stopped moving state within a preset obstacle range at each route point between the current route point and the target task node for each automatic guided vehicle in the moving state; if so, the route point where there is an automatic guided vehicle in a stopped moving state within the preset obstacle range is determined to be an occupied route point, and a local obstacle avoidance route is designed at the location of the occupied route point through the A-star search algorithm; if not, it is determined that there is no occupied route point in the running path, and the running path does not need to be adjusted.

5. The automatic guided vehicle dispatching method according to claim 4, characterized in that: By using the A-star search algorithm, a local obstacle avoidance route is designed at the location of the occupied route point, including: Taking the occupied route point as the center and a preset obstacle avoidance radius, a circle is drawn to obtain an obstacle avoidance area; Selecting a route point closest to the obstacle avoidance area at each of the upstream and downstream locations of the obstacle avoidance area on the running path to which the occupied route point belongs; The two selected route points are used as the starting point and the end point of the local obstacle avoidance route, and the local obstacle avoidance route at the location of the occupied route point is calculated through the A-star search algorithm.

6. An automatic guided vehicle dispatching device, used for dispatching an automatic guided vehicle, characterized in that: include: The acquisition module is used to obtain task information and the operating status and location information of all automatic guided vehicles in the node path map; The task information includes a target task node of at least one target task and a priority ranking of each target task; the running state includes an idle state, a moving state and a working state; an allocation module, configured to allocate each target task in the task information to an automatic guided vehicle in the idle state whose straight-line distance to a target task node corresponding to each target task is the smallest according to the position information, and generate a corresponding running path to guide the automatic guided vehicle allocated to the target task to enter the moving state and move toward the corresponding target task node based on the running path; A generation module is used to periodically generate a priority control scheme for the neighborhood by using a density-based clustering algorithm based on a preset first time period, according to a relative size relationship between the number of automatic guided vehicles in the motion state in the neighborhood of any automatic guided vehicle in the motion state and a preset minimum density, combined with a priority ranking of each of the target tasks; A design module is used to periodically detect whether there are occupied route points in the running paths of the automatic guided vehicles in the moving state with a preset second time as a period, and when it is detected that there are occupied route points in the running paths of any automatic guided vehicles in the moving state, a local obstacle avoidance route is designed at a corresponding position by using an A-star search algorithm; A scheduling module, configured to schedule all automatic guided vehicles in the node path map based on the priority control scheme and / or the local obstacle avoidance route; A generation module is used to periodically generate a priority control scheme for the neighborhood based on a density-based clustering algorithm, with a preset first time as a period, according to a relative size relationship between the number of automatic guided vehicles in the motion state in the neighborhood of any automatic guided vehicle in the motion state and a preset minimum density, combined with the priority ranking of each of the target tasks, including periodically performing the following steps: Calculating the number of automatic guided vehicles in the motion state in the neighborhood of any automatic guided vehicle in the motion state by using the density-based clustering algorithm; When the number is greater than or equal to the preset minimum density, the automatic guided vehicles in the neighborhood in the moving state are sorted in descending order according to the priority ranking of the target tasks assigned to the automatic guided vehicles in the moving state in the neighborhood to obtain a priority control sorting; Generating a priority control scheme for the neighborhood according to the priority control ranking; The number of moving AGVs in the neighborhood of any moving AGV is calculated using a density-based clustering algorithm, including: Taking any automatic guided vehicle in the motion state as the center and a preset distance as the radius, a circle area with any automatic guided vehicle in the motion state as the core point is obtained; Traversing all the circle areas, when there are other core points in the circle area of ​​any core point, merging the circle areas of the other core points into the circle area of ​​any core point to obtain the neighborhood of any core point; The number of automatic guided vehicles in the motion state in the neighborhood of any core point is obtained by counting.

7. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the automatic guided vehicle scheduling method as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the automatic guided vehicle scheduling method according to any one of claims 1 to 5 are executed.

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