Optimal path calculation method, device and system based on node reduction

Abstract

The invention relates to an optimal path calculation method, device and system based on node reduction, in particular to an optimal path calculation method, device and system based on node reduction. An optimal path from a starting node to a destination node can be effectively calculated based on a graph including a plurality of nodes corresponding to a job space in a logistics automation system. Disclosed is an optimal path calculation method for calculating an optimal path from a first node to a second node on the basis of a graph including a plurality of nodes corresponding to a job space and edges connecting the plurality of nodes, and comprising: a representative node calculation step for calculating the optimal path from the first node to the second node; the optimal path calculation system calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from a plurality of representative nodes, wherein the plurality of representative nodes comprise nodes connected with more than three sides in the plurality of nodes; a representative node optimal path calculation step of calculating a representative node optimal path from the first representative node to the second representative node; and an optimal path calculation step of calculating an optimal path from the first node to the second node in consideration of the representative node optimal path, the distance difference from the first representative node to the first node, and the distance difference from the second representative node to the second node.

Description

Technical Field

[0001] The present invention relates to a method, device and system for calculating an optimal path based on node reduction, and more specifically, to a method, device and system for calculating an optimal path based on node reduction, which can effectively calculate the optimal path from a starting node to a destination node based on a graph containing multiple nodes corresponding to a work space in a logistics automation system. Background Art

[0002] In recent years, with the development of e-commerce and the spread of factory automation, logistics automation systems that can efficiently handle the transportation of goods and the like with minimal intervention by operators have been widely used.

[0003] More specifically, various attempts are being made, for example, using logistics robots such as Automated Guided Vehicles (AGV) or Autonomous Mobile Robots (AMR) to transport products or parts in logistics warehouses or factories, or using overhead hoist transports (OHT) to transport wafers in semiconductor factories, in order to automate logistics and improve operational efficiency, thereby reducing costs.

[0004] More specifically, Figure 1 Amazon's Kiva system, shown here, operates more than 200,000 automated guided vehicles (AGVs) 10 in logistics warehouses around the world, thereby reducing logistics costs by 20% and shortening logistics handling time to 1 / 6.

[0005] At this time, the shortest path from the start node to the destination node and its cost information are derived and used for path search or task allocation of the logistics robot or the like, which are the main decisions of the logistics automation system.

[0006] For this reason, Figure 2 As shown, in traditional logistics automation systems, the entire work space is usually represented as a graph consisting of nodes and edges, and the shortest path and cost information are calculated using the Dijkstra algorithm or the A* algorithm.

[0007] However, the problem with the prior art described above is that as the number of nodes increases, the execution time of the algorithm increases exponentially.

[0008] Therefore, if Figure 3As shown, when the above-mentioned Dijkstra algorithm is applied in a logistics system in an operating space 200 composed of multiple nodes, it may take too long to calculate, increase the computing load of the server, and thus increase the control request and response time between the server and the logistics robot, thereby reducing the operating efficiency of the logistics system. Summary of the invention

[0009] 1. Technical issues to be resolved

[0010] The present invention is proposed to solve the above-mentioned problems in the prior art, and its purpose is to provide an optimal path calculation method, device and system based on node reduction, which can effectively reduce the calculation time required for detecting the shortest path based on a graph containing multiple nodes corresponding to the working space in the logistics automation system.

[0011] In addition, the purpose of the present invention is to provide an optimal path calculation method, device and system based on node reduction, which can reduce the computing load of the server, thereby realizing rapid control requests and responses between the server and the logistics robot, and realizing stable system operation.

[0012] It is obvious to those skilled in the art that other detailed objects of the present invention can be understood and appreciated from the detailed contents described below.

[0013] (II) Technical solution

[0014] According to one aspect of the present invention for solving the technical problem, an optimal path calculation method calculates an optimal path from a first node to a second node based on a graph including multiple nodes corresponding to a work space and edges connecting the multiple nodes, and is characterized in that the optimal path calculation method includes: a representative node calculation step, in which an optimal path calculation system calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from multiple representative nodes, and the multiple representative nodes include nodes connected to more than three edges among the multiple nodes; a representative node optimal path calculation step, in which a representative node optimal path from the first representative node to the second representative node is calculated; and an optimal path calculation step, in which an optimal path from the first node to the second node is calculated taking into account the representative node optimal path, the distance difference from the first representative node to the first node, and the distance difference from the second representative node to the second node.

[0015] In the representative node calculation step, the representative node closest to each of the multiple nodes may be calculated as the representative node of each node.

[0016] At this time, in the representative node calculation step, the first representative node and the second representative node may be calculated using a first table, wherein the first table includes information on the correspondence between the plurality of nodes and the representative node.

[0017] In addition, in the representative node optimal path calculation step, the representative node optimal path is calculated using a second table containing information on the distance between each of the representative nodes.

[0018] At this time, in the representative node optimal path calculation step, the representative node optimal path is calculated based on the second table by applying Dijkstra algorithm or A* algorithm.

[0019] In addition, in the optimal path calculation step, the optimal path from the first node to the second node is calculated using a first table containing information on the correspondence relationship between the plurality of nodes and the representative node and the distance difference between the two.

[0020] In addition, the optimal path calculation method may further include: a representative node graph construction step, constructing a representative node graph from the graph, the representative node graph containing information about multiple representative nodes, and the multiple representative nodes including nodes among the multiple nodes connected to more than three edges.

[0021] The representative node graph may include information about the multiple representative nodes and multiple representative edges connecting the multiple representative nodes.

[0022] In addition, according to another aspect of the present invention, an optimal path calculation system calculates an optimal path from a first node to a second node based on a graph including multiple nodes corresponding to a work space and edges connecting the multiple nodes, and is characterized in that the optimal path calculation system includes: a representative node calculation unit, which calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from multiple representative nodes, and the multiple representative nodes include nodes connected to more than three edges among the multiple nodes; a representative node optimal path calculation unit, which calculates a representative node optimal path from the first representative node to the second representative node; and an optimal path calculation unit, which calculates an optimal path from the first node to the second node by considering the representative node optimal path, a distance difference (offset) from the first representative node to the first node, and a distance difference (offset) from the second representative node to the second node.

[0023] (III) Beneficial effects

[0024] Therefore, according to one embodiment of the present invention, the optimal path calculation method, device and system according to one embodiment of the present invention can effectively reduce the calculation time required for detecting the shortest path based on a graph containing multiple nodes corresponding to the working space in a logistics automation system.

[0025] In addition, the optimal path calculation method, device and system according to an embodiment of the present invention can reduce the computing load of the server, thereby realizing rapid control requests and responses between the server and the logistics robot, and realizing stable system operation.

[0026] The effects that can be obtained in the present invention are not limited to the above-mentioned technical effects, and those skilled in the art can clearly understand other technical effects not mentioned through the contents recorded in this specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings, which are included as a part of the detailed description, provide embodiments of the present invention to help understanding of the present invention, and together with the detailed description, explain the technical concept of the present invention.

[0028] Figure 1 is a diagram schematically showing Amazon's Kiva system according to the prior art.

[0029] Figure 2 is a diagram illustrating Dijkstra's algorithm according to the prior art.

[0030] Figure 3 FIG. 4 is a flow chart schematically illustrating a method for calculating an optimal path according to an embodiment of the present invention.

[0031] Figure 4 FIG. 1 is a diagram schematically showing a configuration of a logistics automation system according to an embodiment of the present invention.

[0032] Figures 5 to 7 is a diagram illustrating an optimal path calculation method according to an embodiment of the present invention.

[0033] Figure 8 FIG. 1 is a diagram illustrating a comparative example of an optimal path calculation method according to an embodiment of the present invention.

[0034] Fig. 9 FIG. 1 is a diagram schematically showing a configuration of an optimal path calculation system according to an embodiment of the present invention. Best Mode for Carrying Out the Invention

[0035] The present invention can be modified in many ways and can have many embodiments. A specific embodiment will be described in detail below based on the drawings.

[0036] The following embodiments are provided to help fully understand the methods, devices and / or systems described in this specification. However, these are only examples and the present invention is not limited thereto.

[0037] When describing an embodiment of the present invention, if it is judged that the detailed description of the known technology related to the present invention may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted. In addition, the terms described below are defined in consideration of their role in the present invention, and these terms are defined differently according to the intention or convention of the user, operator, etc. Therefore, the definition of these terms should be based on the entire content of this specification. The terms used in the detailed description are only used to describe embodiments of the present invention and are not restrictive. Unless otherwise expressly stated, the expression in the singular form should include the meaning of the plural form. In this description, the expressions such as "including" or "having" mean certain features, numbers, steps, operations, elements, a part thereof, or a combination thereof, and should not be interpreted as excluding the existence or possibility of one or more other features, numbers, steps, operations, elements, a part thereof, or a combination thereof beyond the described content.

[0038] In addition, although the terms first, second, etc. may be used to describe various components, the components are not limited by the terms, and the terms are only used to distinguish one component from another.

[0039] Hereinafter, exemplary implementations of a method, device and system for calculating an optimal path based on node reduction according to an embodiment of the present invention will be described in sequence with reference to the accompanying drawings.

[0040] However, if Figure 2 As shown, in a conventional logistics automation system, path exploration and work allocation of a logistics robot or the like are performed based on a graph including a plurality of nodes corresponding to a work space and edges connecting the plurality of nodes.

[0041] As a more specific example, Figure 2 As shown in (a), based on a graph including a plurality of nodes and edges corresponding to the workspace, the Dijkstra algorithm or the A* algorithm can be applied to calculate the number of nodes from the starting node (for example, Figure 2 of (a) node 1) to the destination node (e.g., Figure 2 The shortest path and corresponding cost of node 6) of (a) or, as Figure 2 As shown in (b), the logistics robot located at the shortest distance among multiple logistics robots can be selected (for example, Figure 2 (b) r2) assigns the jobs to be performed.

[0042] More specifically, as a typical shortest path search algorithm, Dijkstra's algorithm can be mentioned, such as Figure 2 As shown in (a), the algorithm explores the shortest path between two nodes in a graph-like work space.

[0043] However, the time complexity of Dijkstra's algorithm is O(|V| 2 ), the computation time will increase exponentially with the increase of the number of nodes.

[0044] In addition, if Figure 2 As shown in (b), when the logistics automation system is running, tasks are assigned to logistics robots and movement commands are issued based on the Dijkstra algorithm.

[0045] At this time, the Dijkstra algorithm can be used to select the logistics robot closest to the cargo location for job allocation.

[0046] More specifically, in Figure 2 In (b), when the shortest path value from node a to node b is c(a, b), the job can be assigned to the logistics robot r2 with the shortest path value closest to the cargo location s (i.e., Figure 2 (b) c(s,r2)=3).

[0047] However, when the Dijkstra algorithm and the like are applied to a traditional logistics system as described above, the execution time of the algorithm increases exponentially with the number of nodes, thereby prolonging the computation time and increasing the computation load of the server.

[0048] More specifically, in the prior art, an actual logistics system in an operation space 200 composed of multiple nodes may require excessively long computing time, which may increase the load on the server, thereby increasing the control request and response time between the server and the logistics robot and reducing operating efficiency.

[0049] For example, taking a large-scale logistics automation system with more than 9,000 nodes, in this case, calculating the shortest moving path of a single logistics robot may require a large computing load. If N logistics robots are considered, the computing time may take several seconds or longer.

[0050] Furthermore, each execution of job allocation may require several seconds or longer computing time, which greatly reduces the overall operating efficiency of the logistics automation system.

[0051] In this regard, in an optimal path calculation method, device and system based on node reduction according to an embodiment of the present invention, in order to be able to identify and use information that is highly relevant to decision-making, the existing graph containing multiple nodes and edges is converted into a hierarchical graph representing the node graph, thereby reducing the total number of nodes, and the route is calculated based on this, which greatly reduces the calculation time and can also reduce the computing load of servers, etc. in actual industrial sites, thereby achieving rapid control requests and responses between servers and logistics robots and stable system operation.

[0052] Furthermore, the optimal path calculation method, device and system based on node reduction according to an embodiment of the present invention can be applied to various logistics automation systems with graph structures, thereby having a greater influence.

[0053] In addition, Figure 3 A flow chart of an optimal path calculation method according to an embodiment of the present invention is schematically shown in FIG.

[0054] like Figure 3 As shown, the optimal path calculation method according to an embodiment of the present invention is a method for calculating the optimal path from a first node to a second node based on a graph including multiple nodes corresponding to a workspace 200 and edges connecting the multiple nodes, and is characterized in that it includes: a representative node calculation step S110, in which the optimal path calculation system 120 calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from multiple representative nodes, and the multiple representative nodes include nodes connected to more than three edges among the multiple nodes; a representative node optimal path calculation step S120, in which the representative node optimal path from the first representative node to the second representative node is calculated; and an optimal path calculation step S130, in which the optimal path from the first node to the second node is calculated by considering the representative node optimal path, the distance difference (offset) from the first representative node to the first node, and the distance difference from the second representative node to the second node.

[0055] In the representative node calculation step S110, the representative node closest to each of the multiple nodes may be calculated as the representative node of each node.

[0056] At this time, in the representative node calculation step S110, the first representative node and the second representative node may be calculated using a first table, wherein the first table includes information on the correspondence between the plurality of nodes and the representative node.

[0057] Furthermore, in the representative node optimal path calculation step S120, the representative node optimal path may be calculated using a second table, wherein the second table contains information about the distance between each of the representative nodes.

[0058] At this time, in the representative node optimal path calculation step S120, the representative node optimal path may be calculated based on the second table by applying a Dijkstra algorithm or an A* algorithm.

[0059] Furthermore, in the optimal path calculation step S130, the optimal path from the first node to the second node may be calculated using a first table, wherein the first table contains information about the correspondence between the plurality of nodes and the representative node and the distance difference between the two.

[0060] At this time, in the optimal path calculation step S130, the representative node optimal path and the first table may be used to calculate the shortest path from the first node to the second node.

[0061] In addition, the method may further include a representative node graph construction step (not shown), wherein a representative node graph is constructed from the graph, wherein the representative node graph includes information about multiple representative nodes, and the multiple representative nodes include nodes among the multiple nodes that are connected to more than three edges.

[0062] At this time, the representative node graph may include information on the plurality of representative nodes and a plurality of representative edges connecting the plurality of representative nodes.

[0063] Therefore, in the optimal path calculation method, device and system according to one embodiment of the present invention, the computing time required for detecting the shortest path based on a graph containing multiple nodes corresponding to the working space in the logistics automation system can be effectively reduced, and the computing load of the server can be further reduced to achieve rapid control requests and responses between the server and the logistics robot, and achieve stable system operation.

[0064] in addition, Figure 4 The configuration diagram of a logistics automation system 100 to which an optimal path calculation method according to an embodiment of the present invention is applied is schematically shown.

[0065] like Figure 4 As shown, a logistics automation system 100 according to an embodiment of the present invention may be composed of a plurality of logistics robots 110, 110a, ... 110n such as automated guided vehicles (AGVs) and a server, and may include an optimal path calculation system 120 for calculating the optimal path of the logistics robot 110 and a communication network 130 connecting the logistics robot 110 and the optimal path calculation system 120.

[0066] Therefore, the logistics robot 110 can obtain the optimal path information in the working space 200 from the optimal path calculation system 120 to move or perform work.

[0067] More specifically, in the present invention, the optimal path of a logistics robot will be calculated, wherein the logistics robot may include an automated guided vehicle (AGV) that performs operations while moving along a predetermined path, an autonomous mobile robot (AMR), an overhead hoist transport (OHT) used in semiconductor factories, etc., but the present invention is not limited to this and may further include various devices that perform logistics and other operations while moving along a predetermined path.

[0068] Furthermore, although an automatic guided vehicle (AGV) is mainly described below, this is only an example, and the present invention is not limited thereto, but can be applied to various devices depending on the application used.

[0069] In addition, the logistics robot 110 can move or perform operations based on the optimal path information received from the optimal path calculation system 120 composed of the server, etc., but the present invention is not limited to this and can operate in a more diverse manner, for example, moving or performing operations based on the information received from the optimal path calculation system 120 and data calculated through additional operations, etc.

[0070] Among them, the optimal path calculation system 120 can be configured using a server, etc., but the present invention is not limited to this. Depending on the operating environment, the optimal path calculation system 120 may not be implemented as a separate device, but may be combined with one or more logistics robots 110 to be configured as an integrated type.

[0071] Furthermore, the communication network 130 connecting the logistics robot 110 and the optimal path calculation system 120 may include a wired network and a wireless network, specifically, may include a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), and other communication networks. In addition, the communication network 130 may also include the well-known World Wide Web (WWW). However, the communication network 130 according to the present invention is not limited to the networks listed above, and may also include a well-known wireless data network or a well-known wired / wireless network.

[0072] Below, refer to Figure 3 and Figure 4 , the optimal path calculation method, device and system according to an embodiment of the present invention are decomposed into various components for more detailed description.

[0073] In which, in an optimal path calculation method according to an embodiment of the present invention, in a logistics automation system 100, based on a graph including multiple nodes corresponding to a work space 200 and edges connecting the multiple nodes, an optimal path from a first node as a starting node to a second node as a destination node is calculated.

[0074] To this end, first, in the representative node calculation step S110, the optimal path calculation system 120 calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from a plurality of representative nodes, and the plurality of representative nodes include nodes among the plurality of nodes connected to more than three edges.

[0075] In the representative node calculation step S110, the representative node closest to each of the multiple nodes may be calculated as the representative node of each node.

[0076] At this time, in the representative node calculation step S110, the first representative node and the second representative node may be calculated using a first table, wherein the first table includes information on the correspondence between the plurality of nodes and the representative node.

[0077] Therefore, in the representative node optimal path calculation step S120, the representative node optimal path may be calculated using a second table, where the second table contains information about the distance between each of the representative nodes.

[0078] At this time, in the representative node best path calculation step S120, the representative node best path may be calculated by applying the Dijkstra algorithm based on the second table, but the present invention is not necessarily limited thereto.

[0079] In addition, the optimal path calculation method according to an embodiment of the present invention may further include a representative node graph construction step (not shown), wherein a representative node graph is constructed from the graph, wherein the representative node graph contains information about a plurality of representative nodes, and the plurality of representative nodes contain nodes among the plurality of nodes that are connected to more than three edges.

[0080] At this time, the representative node graph may include information on the plurality of representative nodes and a plurality of representative edges connecting the plurality of representative nodes.

[0081] More specifically, if Figure 5 As shown in (a), in a conventional logistics automation system 100, for the sake of operation and management of the logistics robot 110, nodes with predetermined spacing are usually created and managed, even if these nodes are not branch points / convergence points.

[0082] However, nodes that are not branch points or junctions as described above may result in unnecessary calculations when applying the Dijkstra algorithm, etc., thereby greatly increasing the required computing resources and computing time.

[0083] In this regard, in an optimal path calculation method, device and system according to an embodiment of the present invention, as Figure 5 As shown in (b), by selecting and utilizing representative nodes based on branch points / junction points, that is, logical nodes instead of all nodes, the computing resources and computing time required for optimal path calculation can be effectively reduced.

[0084] More specifically, if Figure 6 As shown in (a), in a conventional logistics automation system 100, a plurality of nodes are generally used at regular intervals even if they are not branch points / junction points, and a link table (Link Table) containing information about the plurality of nodes and information about the connection relationship between each node is created and used.

[0085] In this regard, in an optimal path calculation method, device and system according to an embodiment of the present invention, as Figure 6 As shown in (b), for the work space 200, a representative node table (= second table) containing information about each representative node and a distance difference table (= first table) containing information about the correspondence between the multiple nodes and the representative nodes and the distance difference between the two can be created based on a graph containing multiple nodes and multiple edges.

[0086] That is, from Figure 6 As can be seen from (b), all nodes in the workspace 200 can be represented by information about the representative node of the corresponding node and the distance difference with the representative node. Therefore, the relationship between each node and the corresponding representative node can be constructed into a distance difference table (= first table).

[0087] Therefore, in the optimal path calculation step S130, the optimal path from the first node to the second node is calculated by considering the representative node optimal path, the distance difference (offset) from the first representative node to the first node calculated from the distance difference table (=first table), and the distance difference from the second representative node to the second node.

[0088] At this time, the first table may contain information about the correspondence between the multiple nodes and the representative node and the distance difference between the two, so the first table can be used to calculate the best path from the first node to the second node, and the representative node best path calculated in the representative node best path calculation step S120 and the first table can be further used to calculate the shortest path from the first node to the second node.

[0089] More specifically, in order to calculate Figure 7 (a) from the starting node ( Figure 7 (a) from the origin to the destination node ( Figure 7 To find the shortest path from a specific first node to a second node of (a) a destination, first (1) it is necessary to identify representative nodes of the first node and the second node.

[0090] To this end, the representative nodes of the first node and the second node may be calculated using a distance difference table (=first table).

[0091] More specifically, in calculating Figure 7 In the case of the shortest path from node 2 (origin) to node 26 (destination) in (a), we can use Figure 7 The distance difference table (=first table) in (b) calculates node 3 and node 24 as representative nodes for the node 2 and the node 26 .

[0092] Then, (2) the optimal path from the first node to the second node can be calculated by applying Dijkstra's algorithm or the like based on the representative node table (= second table).

[0093] More specifically, based on Figure 7 The representative node table of (b) is calculated by applying Dijkstra algorithm etc. Figure 7 The optimal path between the node 3 as the representative node and the node 24 shown in (a) (=representative node optimal path).

[0094] Therefore, (3) the optimal path value from the first node to the second node can be calculated by considering the calculated optimal path of the representative node and the distance difference value with respect to the first node and the second node.

[0095] More specifically, if Figure 7 As shown in (a), by adding the distance difference from node 2 to node 3, the shortest path value from node 3 to node 24, and the distance difference from node 24 to node 26, the shortest path value from node 2 to node 26 can be calculated.

[0096] Therefore, in the optimal path calculation method, device and system according to one embodiment of the present invention, the calculation time required for detecting the shortest path based on a graph containing multiple nodes corresponding to the working space in the automatic logistics system can be effectively reduced, thereby reducing the computing load of the server, thereby realizing rapid control requests and responses between the server and the logistics robot, and achieving stable system operation. DETAILED DESCRIPTION

[0097] More specifically, as an experimental example of the present invention, the optimal path calculation method, device and system according to an embodiment of the present invention are applied to an automated guided vehicle (AGV)-based logistics automation system with 9088 nodes and 11183 edges, as described below.

[0098] First, the time taken to calculate the shortest path between a specific first node and a second node by directly applying the Dijkstra algorithm to a graph containing a total of 9088 nodes and 11183 edges is an average of 17.095ms ( Figure 8 (a) (i) Single Pair Cost), however, in the optimal path calculation method, device and system according to an embodiment of the present invention, it takes an average of 0.001ms ( Figure 8 (b) (iv) Single Pair Cost), it can be confirmed that this can calculate the shortest path for a single node pair in a very short time of 0.006% of the prior art.

[0099] In addition, in the above experimental example, it takes 8104.1 seconds to directly apply the Dijkstra algorithm to calculate the shortest path between all 9088 nodes in a graph containing 9088 nodes and 11183 edges ( Figure 8 The cost of all node pairs in (a) and (ii) is about 135 minutes), while the optimal path calculation method, device and system according to one embodiment of the present invention takes a total of 214.5 seconds ( Figure 8 The cost of all node pairs in (b) and (v) is about 3.56 minutes), which confirms that this is able to calculate the shortest paths of all nodes in 2.647% of the time of the existing technology.

[0100] In addition, according to an embodiment of the present invention, the optimal path calculation method, device and system can pre-construct a representative node table from a graph containing all nodes and edges, and the representative node table contains multiple representative nodes, and the multiple representative nodes include nodes connected to more than three edges among multiple nodes (i.e., nodes on branch points / convergence points).

[0101] In this regard, for the graph containing a total of 9088 nodes and 11183 edges in the above experimental example, it is necessary to identify representative nodes and edges that are highly relevant to the decision from all nodes and edges. The result of measuring the time required for this process alone confirmed that the time required to calculate 1855 representative nodes was 39.1 seconds ( Figure 8 (b)(iii)).

[0102] Therefore, although it is possible to calculate the shortest path for each pair of nodes by applying the Dijkstra algorithm to all nodes according to the prior art (single node pair (Single Pair)), in a complex logistics automation system 100 including multiple nodes, dozens to hundreds of shortest paths need to be calculated simultaneously, which may generate an excessive system load and cause a significant delay in the calculation time. Furthermore, if the shortest paths of all nodes are to be calculated in batches, it may take a considerable amount of time, up to several hours, which may be difficult to apply in practical applications (all node pairs (All Pair)).

[0103] In this regard, in an optimal path calculation method, device and system according to an embodiment of the present invention, representative nodes, etc. can be pre-calculated in only tens of seconds at the initial driving time point, and then the shortest path for each pair of nodes can be calculated in a very short time, thereby realizing efficient operation of a large-scale logistics automation system 100.

[0104] also, Fig. 9 FIG. 1 shows a configuration diagram of an optimal path calculation system 120 according to an embodiment of the present invention.

[0105] like Fig. 9 As shown, the optimal path calculation system 120 according to an embodiment of the present invention is an optimal path calculation system 120 that calculates the optimal path from a first node to a second node based on a graph including multiple nodes corresponding to a workspace 200 and edges connecting the multiple nodes. The optimal path calculation system 120 may include a representative node calculation unit 121, a representative node optimal path calculation unit 122, and an optimal path calculation unit 123.

[0106] Here, more details of the optimal path calculation system 120 according to an embodiment of the present invention can be found in the above reference. Figures 1 to 8 It is inferred from the description of the optimal path calculation method according to an embodiment of the present invention, so the core configuration will be described hereinafter, and a more detailed description will be omitted.

[0107] More specifically, in the optimal path calculation system 120 according to an embodiment of the present invention, the representative node calculation unit 121 calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from a plurality of representative nodes, and the plurality of representative nodes include nodes among the plurality of nodes connected to more than three edges.

[0108] Furthermore, the representative node optimal path calculation unit 122 calculates a representative node optimal path from the first representative node to the second representative node.

[0109] Furthermore, the optimal path calculation unit 123 calculates the optimal path from the first node to the second node by considering the representative node optimal path, the distance difference (offset) from the first representative node to the first node, and the distance difference (offset) from the second representative node to the second node.

[0110] Therefore, in the optimal path calculation method, device and system according to an embodiment of the present invention, the calculation time required for detecting the shortest path based on a graph containing multiple nodes corresponding to the working space in a logistics automation system can be effectively reduced.

[0111] In addition, in the optimal route calculation method, device and system according to an embodiment of the present invention, the computing load of the server can be reduced to achieve rapid control requests and responses between the server and the logistics robot, and to achieve stable operation of the system.

[0112] The above description is merely an exemplary description of the technical idea of ​​the present invention, and a person skilled in the art of the present invention can make various modifications and variations without departing from the essential features of the present invention. Therefore, the embodiments described in the present invention are intended to illustrate rather than limit the technical idea of ​​the present invention, and the present invention is not limited to these embodiments. The protection scope of the present invention shall be interpreted according to the claims, and all technical ideas within the scope equivalent to the claims shall be interpreted as belonging to the scope of the rights of the present invention.

Claims

1. An optimal path calculation method, wherein the optimal path calculation method calculates an optimal path from a first node to a second node based on a graph including a plurality of nodes corresponding to a workspace and edges connecting the plurality of nodes, wherein: The optimal path calculation method comprises: a representative node calculation step, wherein the optimal path calculation system calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from a plurality of representative nodes, wherein the plurality of representative nodes include nodes connected to more than three edges among the plurality of nodes; a representative node best path calculation step, calculating a representative node best path from the first representative node to the second representative node; and The best path calculation step calculates the best path from the first node to the second node by considering the best path of the representative node, the distance difference from the first representative node to the first node, and the distance difference from the second representative node to the second node.

2. The optimal path calculation method according to claim 1, characterized in that: In the representative node calculation step, a representative node closest to each of the plurality of nodes is calculated as the representative node of each node.

3. The optimal path calculation method according to claim 2, characterized in that: In the representative node calculation step, the first representative node and the second representative node are calculated using a first table, the first table including information on the correspondence relationship between the plurality of nodes and the representative node.

4. The optimal path calculation method according to claim 1, characterized in that: In the representative node optimal path calculation step, the representative node optimal path is calculated using a second table containing information on the distance between each of the representative nodes.

5. The optimal path calculation method according to claim 4, characterized in that: In the representative node optimal path calculation step, the representative node optimal path is calculated based on the second table using a Dijkstra algorithm or an A* algorithm.

6. The optimal path calculation method according to claim 1, characterized in that: In the optimal path calculation step, the optimal path from the first node to the second node is calculated using a first table containing information on the correspondence between the plurality of nodes and the representative node and the distance difference between the two.

7. The optimal path calculation method according to claim 6, characterized in that: In the optimal path calculation step, the shortest path from the first node to the second node is calculated using the representative node optimal path and the first table.

8. The optimal path calculation method according to claim 1, characterized in that: Further including: A representative node graph construction step is to construct a representative node graph from the graph, wherein the representative node graph includes information about a plurality of representative nodes, and the plurality of representative nodes include nodes connected to more than three edges among the plurality of nodes.

9. The optimal path calculation method according to claim 8, characterized in that: The representative node graph contains information about the plurality of representative nodes and a plurality of representative edges connecting the plurality of representative nodes.

10. An optimal path calculation system, the optimal path calculation system calculating an optimal path from a first node to a second node based on a graph including a plurality of nodes corresponding to a workspace and edges connecting the plurality of nodes, characterized in that: The optimal path calculation system comprises: a representative node calculation unit that calculates a first representative node corresponding to the first node and a second representative node corresponding to the second node from a plurality of representative nodes, wherein the plurality of representative nodes include nodes connected to three or more edges among the plurality of nodes; a representative node optimal path calculation unit that calculates a representative node optimal path from the first representative node to the second representative node; and The optimal path calculation unit calculates an optimal path from the first node to the second node in consideration of the representative node optimal path, the distance difference from the first representative node to the first node, and the distance difference from the second representative node to the second node.

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