CN116167515A - AGV distribution path planning method, device, equipment and medium - Google Patents
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Abstract
The invention discloses an AGV distribution path planning method, an AGV distribution path planning device, AGV distribution path planning equipment and AGV distribution path planning media. Wherein the method comprises the following steps: acquiring a distribution data set of a target AGV; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information; acquiring the priority of each distribution point in the distribution data set; and determining a target delivery path of the target AGV according to the priority and the delivery point position information. According to the technical scheme, the AGV distribution path can be planned flexibly, and the distribution efficiency is improved.
Description
Technical Field
The present invention relates to the field of path planning algorithms, and in particular, to a method, apparatus, device, and medium for planning an AGV delivery path.
Background
Along with the development of information integration of logistics enterprises, an automatic transport vehicle (Automated Guided Vehicle, AGV) automatic transport system is widely applied as an important means of logistics informatization and automation, and is mainly used for distributing materials, products and the like in parks or workshops.
At present, the AGV delivery mode is single, generally delivers a material or a product at a time, and a plurality of production line delivery demands in a workshop generally use a plurality of AGV dollies, and delivery is mainly carried out according to a first-in first-out principle, and in an emergency, the automatic delivery device can be dispatched through artificial adjustment means such as an emergency bill insertion.
Disclosure of Invention
The invention provides a method, a device, equipment and a medium for planning an AGV delivery path, which can flexibly plan the AGV delivery path and improve the delivery efficiency.
According to an aspect of the present invention, there is provided an AGV delivery path planning method including:
acquiring a distribution data set of a target AGV; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information;
acquiring the priority of each distribution point in the distribution data set;
and determining a target delivery path of the target AGV according to the priority and the delivery point position information.
Optionally, the distribution data further comprises a material category and a material amount; acquiring a delivery data set of a target AGV, comprising:
acquiring material types, material amounts and material basic information;
forming a boxing problem based on the material category, the material amount and the material basic information;
and solving the boxing problem to obtain a distribution data set of the target AGV.
Optionally, solving the boxing problem to obtain a delivery data set of the target AGV includes:
acquiring the load capacity of the target AGV;
and solving the boxing problem based on the loading capacity to obtain a distribution data set of the target AGV.
Optionally, determining the target delivery path of the target AGV according to the priority and the delivery point position information includes:
determining distance information between every two distribution points according to the distribution point position information to obtain a distance information set;
performing path planning of a set optimization algorithm on the distance information set based on the priority to obtain a target delivery path of the target AGV; the target delivery path is formed by connecting a plurality of delivery points in the delivery data set according to a certain sequence.
Optionally, setting a path planning of an optimization algorithm for the distance information set based on the priority, to obtain a target delivery path of the target AGV, including:
and taking the priority as a constraint condition, and performing path planning of a set optimization algorithm on the distance information set to obtain a target delivery path of the target AGV.
According to another aspect of the present invention, there is provided an AGV delivery path planning apparatus including:
the distribution data set acquisition module is used for acquiring a distribution data set of the target AGV; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information;
the priority acquisition module is used for acquiring the priority of each distribution point in the distribution data set;
and the target delivery path determining module is used for determining a target delivery path of the target AGV according to the priority and the delivery point position information.
Optionally, the distribution data further comprises a material category and a material amount; a delivery dataset acquisition module comprising:
the acquisition unit is used for acquiring the material types, the material amounts and the material basic information;
the boxing problem forming unit is used for forming a boxing problem based on the material category, the material quantity and the material basic information;
and the boxing problem solving unit is used for solving the boxing problem to obtain a distribution data set of the target AGV.
Optionally, the solution unit for a vanning problem is specifically configured to:
acquiring the load capacity of the target AGV;
and solving the boxing problem based on the loading capacity to obtain a distribution data set of the target AGV.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the AGV delivery path planning method according to any one of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute the method for planning an AGV delivery path according to any one of the embodiments of the present invention.
According to the technical scheme, the distribution data set of the target AGV is obtained; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information; acquiring the priority of each distribution point in the distribution data set; and determining a target delivery path of the target AGV according to the priority and the delivery point position information. According to the technical scheme, the AGV distribution path can be planned flexibly, and the distribution efficiency is improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an AGV delivery path planning method according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram of an AGV delivery path planning apparatus according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of an AGV delivery path planning method according to an embodiment of the present invention, where the method may be performed by an AGV delivery path planning apparatus, which may be implemented in hardware and/or software, and may be configured in an electronic device with data processing capabilities. As shown in fig. 1, the method includes:
s110, acquiring a distribution data set of the target AGV.
Wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information. The delivery point position information may be understood as the position information of each delivery point to which the target AGV needs to be delivered. The distribution point position information may include a plurality of positions of the distribution points, and there may be 5, 6, 7, 8, or the like, for example. The target AGV may be understood as an AGV that needs to make a delivery path plan. The delivery data set may be derived from actual delivery requirements. An automated guided vehicle (Automated Guided Vehicle, AGV) may be referred to as being equipped with an electromagnetic or optical, etc. automated guide. In this embodiment, a delivery data set of the target AGV may be acquired.
In this embodiment, optionally, the distribution data preferably includes a material category and a material amount; acquiring a delivery data set of a target AGV, comprising: acquiring material types, material amounts and material basic information; forming a boxing problem based on the material category, the material amount and the material basic information; and solving the boxing problem to obtain a distribution data set of the target AGV.
The material type may be understood as a type of material to be dispensed, for example, a type of blank, structural member, etc., and may be classified according to a type of material in actual situations. The material category may be different for each dispensing point location in this embodiment. The material quantity can be the material quality or the material quantity, and can be determined according to actual demands. The material amount may be a material mass in the present embodiment. The basic information of the material can comprise basic information such as the size, specification and number of the material. The problem of packing is understood to be that packing some boxes into containers is a mathematical problem often encountered in industrial production, such as the problem of packing containers. The bin packing problem may be formed based on the material category, the material amount, and the material basis information. Solving the binning problem in this embodiment may be by a heuristic greedy algorithm (First Fit Decreasing, FFD). Among them, the strategy of the FFD algorithm is a typical heuristic greedy algorithm in the boxing problem, and the basic idea is to sort the articles from big to small and then sequentially load the articles from front to back into the box which can hold the articles first. In this embodiment, other algorithms may be used to solve the boxing problem, and may be set according to actual situations. The delivery data set for the target AGV may be obtained by solving a vanning problem. In this embodiment, the problem of boxing can be solved, and the type of the best loaded material for the delivery AGV can be obtained, so as to achieve the best delivery efficiency, and finally, a delivery data set containing a plurality of delivery point positions, material types and material amounts of each AGV can be formed.
Illustratively, a workshop has 5 AGV carts (a, B, C, …, respectively) and 19 stations (A, B, C, …, respectively) for the AGVs to dispense material, 30 types of material (M1, M2, M3, … M30, respectively). Specifically, the types and the quantities of materials at the distribution demand points in each distribution process can be counted, a packing problem (from distribution point position to material quantity) is formed by combining with the basic information of the materials, such as A-M1-30, A-M2-21, B-M2-11, B-M3-10 and …, the best loading material types and quantities of the AGV trolley can be solved by adopting a heuristic greedy algorithm FFD, and finally a distribution data set of the distribution point position, the materials and the material quantity of each trolley can be formed, for example, the distribution data set of the a trolley can be a- (A-M1-30, B-M2-11, D-M13-24, E-M19-30, H-M21-9,K-M27-13).
In the embodiment, the material category, the material amount and the material basic information can be acquired, then the boxing problem is formed based on the material category, the material amount and the material basic information, and the boxing problem is solved through an algorithm, so that a distribution data set of the target AGV is obtained. By such an arrangement in this embodiment, a delivery data set including a plurality of pieces of delivery data may be obtained, thereby facilitating the AGV to plan the delivery path.
In this embodiment, optionally, solving the boxing problem to obtain the delivery data set of the target AGV includes: acquiring the load capacity of the target AGV; and solving the boxing problem based on the loading capacity to obtain a distribution data set of the target AGV.
The load may be the maximum weight that the AGV cart is able to load. The load may be pre-configured. In this embodiment, the loading capacity of each AGV may be the same or different, and may be set according to actual requirements. Solving the vanning problem based on the load in this embodiment may be understood as the sum of the material weights of the dispensed materials in the dispensed data set cannot be greater than the load of the target AGV.
In this embodiment, the load capacity of the target AGV may be obtained, and the boxing problem may be solved based on the load capacity, so as to obtain the delivery data set of the target AGV. With this arrangement in this embodiment, the data set can be more reliable by considering the load of the AGV to determine the delivery data set.
S120, acquiring the priority of each distribution point in the distribution data set.
The priority of each distribution point may be preset. In this embodiment, priority information of each delivery point in the delivery data set may be obtained.
S130, determining a target delivery path of the target AGV according to the priority and the delivery point position information.
The target delivery path may be determined according to a preset priority of each delivery point and the position information of the delivery point. In this embodiment, the target delivery path of the target AGV may be determined according to the priority and the delivery point position information.
In this embodiment, optionally, determining the target delivery path of the target AGV according to the priority and the delivery point position information includes: determining distance information between every two distribution points according to the distribution point position information to obtain a distance information set; performing path planning of a set optimization algorithm on the distance information set based on the priority to obtain a target delivery path of the target AGV; the target delivery path is formed by connecting a plurality of delivery points in the delivery data set according to a certain sequence.
Wherein the distance information set may be understood as distance matrix data information. The distance information set may be distance information between two distribution points determined based on the distribution point position information. For example, if the distribution point information is 6, the distance information set may be matrix data information of 6*6. The set optimization algorithm may be a particle swarm algorithm, a simulated annealing algorithm, a genetic algorithm, or the like. In this embodiment, path planning may be performed by setting an optimization algorithm for the distance information set based on the priority. In the embodiment, the particle swarm algorithm can be used for planning the path of the AGV trolley, solving the optimal delivery path traversing all delivery position points, and finally, the trolley can plan the optimal path according to the algorithm for carrying out material transportation delivery. The target delivery path may be formed by a plurality of delivery points in the delivery data set being connected in a certain order. The certain sequence can be understood as the sequence of the distribution point positions, and can be set according to actual requirements.
In this embodiment, distance information between distribution points may be determined according to the position information of the distribution points to obtain a distance information set, and a path planning of an optimization algorithm is set for the distance information set based on priority, so as to obtain a target distribution path formed by connecting a plurality of distribution points in a distribution data set according to a certain order, so that the distribution data set is provided. Through such setting in this embodiment, can plan the delivery route of target AGV to can improve the delivery time rate, promote the AGV delivery full rate at every turn, improve delivery efficiency, increase the manufacturing cost of enterprise.
In this embodiment, optionally, setting a path planning of an optimization algorithm for the distance information set based on the priority, where the target delivery path of the target AGV includes: and taking the priority as a constraint condition, and performing path planning of a set optimization algorithm on the distance information set to obtain a target delivery path of the target AGV.
The constraint condition may be a constraint condition in path planning. The constraints may be preset by the skilled person. The constraint condition in the embodiment is priority, and priority can be set for each distribution point, and different weights are set according to the priority, so that path planning of an optimization algorithm is set for the distance information set. For example, if the priority of a certain delivery point is 1, a weight of 0.2 may be assigned, and if the priority of a certain delivery point is 2, a weight may be assigned
In this embodiment, the priority may be used as a constraint condition, and the path planning of the optimization algorithm may be set for the distance information set, so as to obtain the target delivery path of the target AGV. Through the arrangement, the distance information set can be subjected to path planning of a set optimization algorithm through the set constraint conditions, the constraint conditions can be flexibly set, and the AGV can be subjected to distribution path planning more flexibly.
According to the technical scheme, the distribution data set of the target AGV is obtained; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information; acquiring the priority of each distribution point in the distribution data set; and determining a target delivery path of the target AGV according to the priority and the delivery point position information. According to the technical scheme, the AGV distribution path can be planned flexibly, and the distribution efficiency is improved.
Example two
Fig. 2 is a schematic structural diagram of an AGV delivery path planning apparatus according to a second embodiment of the present invention, where the apparatus may execute the method for processing stream data in real time according to any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method. As shown in fig. 2, the apparatus includes:
a delivery data set acquisition module 210, configured to acquire a delivery data set of the target AGV; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information.
A priority obtaining module 220, configured to obtain the priority of each delivery point in the delivery data set.
The target delivery path determining module 230 is configured to determine a target delivery path of the target AGV according to the priority and the delivery point position information.
Optionally, the distribution data further comprises a material category and a material amount; a delivery dataset acquisition module comprising:
the acquisition unit is used for acquiring the material types, the material amounts and the material basic information;
the boxing problem forming unit is used for forming a boxing problem based on the material category, the material quantity and the material basic information;
and the boxing problem solving unit is used for solving the boxing problem to obtain a distribution data set of the target AGV.
Optionally, the solution unit for a vanning problem is specifically configured to:
acquiring the load capacity of the target AGV;
and solving the boxing problem based on the loading capacity to obtain a distribution data set of the target AGV.
Optionally, the target delivery path determining module 230 includes:
the distance information set acquisition unit is used for determining distance information between every two distribution points according to the distribution point position information to obtain a distance information set;
the path planning unit is used for carrying out path planning of a set optimization algorithm on the distance information set based on the priority, and obtaining a target delivery path of the target AGV; the target delivery path is formed by connecting a plurality of delivery points in the delivery data set according to a certain sequence.
Optionally, the path planning unit is specifically configured to set a path plan of an optimization algorithm for the distance information set by using the priority as a constraint condition, so as to obtain a target delivery path of the target AGV.
The AGV delivery path planning device provided by the embodiment of the invention can execute the AGV delivery path planning method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. Technical details not described in detail in this embodiment can be found in the methods provided in all the foregoing embodiments of the invention.
Example III
Fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 3, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the AGV delivery path planning method.
In some embodiments, the AGV delivery path planning method may be implemented as a computer program tangibly embodied on a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When a computer program is loaded into RAM 13 and executed by processor 11, one or more of the steps of the AGV delivery path planning method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the AGV delivery path planning method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. An AGV delivery path planning method, comprising:
acquiring a distribution data set of a target AGV; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information;
acquiring the priority of each distribution point in the distribution data set;
and determining a target delivery path of the target AGV according to the priority and the delivery point position information.
2. The method of claim 1, wherein the distribution data set further comprises a material category and a material quantity; acquiring a delivery data set of a target AGV, comprising:
acquiring material types, material amounts and material basic information;
forming a boxing problem based on the material category, the material amount and the material basic information;
and solving the boxing problem to obtain a distribution data set of the target AGV.
3. The method of claim 2 wherein solving the vanning problem to obtain a delivery data set for the target AGV includes:
acquiring the load capacity of the target AGV;
and solving the boxing problem based on the loading capacity to obtain a distribution data set of the target AGV.
4. The method of claim 1 wherein determining a target delivery path for the target AGV based on the priority and the delivery point location information comprises:
determining distance information between every two distribution points according to the distribution point position information to obtain a distance information set;
performing path planning of a set optimization algorithm on the distance information set based on the priority to obtain a target delivery path of the target AGV; the target delivery path is formed by connecting a plurality of delivery points in the delivery data set according to a certain sequence.
5. The method of claim 4 wherein setting a path plan for an optimization algorithm for the distance information set based on the priority to obtain a target delivery path for the target AGV comprises:
and taking the priority as a constraint condition, and performing path planning of a set optimization algorithm on the distance information set to obtain a target delivery path of the target AGV.
6. An AGV delivery path planning apparatus comprising:
the distribution data set acquisition module is used for acquiring a distribution data set of the target AGV; wherein the distribution data set comprises a plurality of pieces of distribution data, and the distribution data comprises distribution point position information;
the priority acquisition module is used for acquiring the priority of each distribution point in the distribution data set;
and the target delivery path determining module is used for determining a target delivery path of the target AGV according to the priority and the delivery point position information.
7. The apparatus of claim 6 wherein said dispensing data further comprises a material category and a material quantity; a delivery dataset acquisition module comprising:
the acquisition unit is used for acquiring the material types, the material amounts and the material basic information;
the boxing problem forming unit is used for forming a boxing problem based on the material category, the material quantity and the material basic information;
and the boxing problem solving unit is used for solving the boxing problem to obtain a distribution data set of the target AGV.
8. The device according to claim 7, characterized by a vanning problem solving unit, in particular for:
acquiring the load capacity of the target AGV;
and solving the boxing problem based on the loading capacity to obtain a distribution data set of the target AGV.
9. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the AGV delivery path planning method of any of claims 1-5.
10. A computer readable storage medium having stored thereon computer instructions for causing a processor to execute the AGV delivery path planning method according to any one of claims 1-5.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117522253A (en) * | 2024-01-05 | 2024-02-06 | 湘江实验室 | Collaborative distribution path planning method and device for truck unmanned aerial vehicle |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117522253A (en) * | 2024-01-05 | 2024-02-06 | 湘江实验室 | Collaborative distribution path planning method and device for truck unmanned aerial vehicle |
| CN117522253B (en) * | 2024-01-05 | 2024-04-19 | 湘江实验室 | Collaborative distribution path planning method and device for truck unmanned aerial vehicle |
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