Information processing device, information processing system, information processing method and program

Abstract

To enable generation of a route tailored to a user.SOLUTION: An information processing device has a reception unit that receives user information about a user requesting generation of a route, and a route generation unit that generates a route according to the user information in a space based on the user information and map information indicating the space displayed to the user as a target for the generation of the route.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing system, an information processing method, and a program. [Background technology]

[0002] When moving through a certain space, such as a construction site, a commercial facility, a logistics site, or an airport, it may be difficult to move smoothly to your destination.

[0003] Therefore, in order to support movement in a certain space, various route generation or route search technologies (hereinafter referred to as "route generation technologies") have been studied and some of them are provided as applications. Some of these route generation technologies generate routes according to priority conditions (shortest time, shortest distance, etc.) by adding priority conditions regarding time or distance. Summary of the Invention [Problem to be solved by the invention]

[0004] In spaces that are specialized for specific purposes, such as construction sites, commercial facilities, logistics sites, and airports, the appropriate route may differ depending on the relationship a person has with the space. For example, in a commercial facility, even if the starting and ending points are the same, the appropriate route may differ depending on whether the person is a customer or a store clerk.

[0005] The present invention has been made in consideration of the above points, and has an object to make it possible to generate a route that is suited to a user. [Means for solving the problem]

[0006] In order to solve the above problem, the information processing device has a reception unit that receives user information regarding a user who requests the generation of a route, and a route generation unit that generates a route in the space according to the user information based on map information indicating the space displayed to the user as the target for the route generation and the user information. [Effects of the Invention]

[0007] It is possible to generate a route according to the user. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a diagram illustrating an example of a configuration of an information processing system 1 according to a first embodiment. [Figure 2] 1 is a diagram illustrating an example of a hardware configuration of a server device 10 according to a first embodiment. [Figure 3] FIG. 2 is a diagram illustrating an example of a functional configuration of an information processing system 1 according to a first embodiment. [Figure 4] FIG. 10 is a sequence diagram illustrating an example of a processing procedure for updating map information according to the first embodiment. [Figure 5] FIG. 2 is a diagram illustrating an example of the configuration of a map information storage unit 121. [Figure 6] FIG. 10 is a diagram illustrating an example of a space screen. [Figure 7] FIG. 10 is a sequence diagram illustrating an example of a processing procedure for a route generation process according to the first embodiment. [Figure 8] FIG. 2 is a diagram illustrating an example of the configuration of a user information storage unit 122. [Figure 9] FIG. 2 is a diagram showing a first example of a spatial screen showing a route in the first embodiment. [Figure 10] FIG. 10 is a diagram showing a second example of a spatial screen showing a route in the first embodiment. [Figure 11] FIG. 10 is a sequence diagram illustrating an example of a processing procedure for a route generation process according to the second embodiment. [Figure 12]FIG. 11 is a diagram showing an example of a space screen showing a route in the second embodiment. [Figure 13] FIG. 13 is a sequence diagram illustrating an example of a processing procedure for a route generation process according to the third embodiment. [Figure 14] FIG. 13 is a diagram showing a first example of a spatial screen showing a route in the third embodiment. [Figure 15] FIG. 13 is a diagram showing a second example of a spatial screen showing a route in the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Fig. 1 is a diagram showing an example of the configuration of an information processing system 1 in a first embodiment. In Fig. 1, one or more terminal devices 20 are connected to a server device 10 via a communication network 30 such as the Internet.

[0010] The terminal device 20 is a device used by a user who requests the generation of a route suitable for the user in a certain three-dimensional space (hereinafter simply referred to as "space") that includes multiple travel routes. For example, a PC (Personal Computer), a smartphone, a tablet terminal, etc. may be used as the terminal device 20.

[0011] The server device 10 is one or more computers that generate (search) a route suitable for a user in a space in response to a route generation request from the terminal device 20, and display the generated route on the terminal device 20. Note that the space A may be any space specialized for a specific purpose, such as a commercial facility, a logistics site, or an airport. Alternatively, the space A may be a space that is used by a limited number of people, such as a machine room. However, the purpose of moving around the space A may differ depending on the person (the user of the terminal device 20). The server device 10 generates a route that reflects the fact that the purpose of moving around the space A may differ depending on the person.

[0012] Fig. 2 is a diagram showing an example of the hardware configuration of the server device 10 in the first embodiment. The server device 10 in Fig. 2 includes a drive device 100, an auxiliary storage device 102, a memory device 103, a processor 104, and an interface device 105, which are all interconnected via a bus B.

[0013] A program that realizes processing in the server device 10 is provided by a recording medium 101 such as a CD-ROM. When the recording medium 101 storing the program is set in the drive device 100, the program is installed from the recording medium 101 to the auxiliary storage device 102 via the drive device 100. However, the program does not necessarily have to be installed from the recording medium 101, but may be downloaded from another computer via a network. The auxiliary storage device 102 stores the installed program as well as necessary files, data, etc.

[0014] When an instruction to start a program is received, the memory device 103 reads and stores the program from the auxiliary storage device 102. The processor 104 is a CPU or a GPU (Graphics Processing Unit), or a CPU and a GPU, and executes functions related to the server device 10 in accordance with the program stored in the memory device 103. The interface device 105 is used as an interface for connecting to a network.

[0015] The terminal device 20 may also have the same hardware configuration as that shown in FIG.

[0016] 3 is a diagram showing an example of the functional configuration of the information processing system 1 in the first embodiment. The terminal device 20 has an input unit 21, a request sending unit 22, a display control unit 23, etc. These units are realized by processing in which one or more programs installed in the terminal device 20 are executed by a processor of the terminal device 20.

[0017] The input unit 21 accepts input from the user of the terminal device 20. For example, the input unit 21 accepts an instruction from the user to display map information (map information) indicating one of a plurality of spaces (hereinafter referred to as "candidate spaces") that can be candidates for a target for generating a route. In the instruction to display map information, identification information (hereinafter referred to as "space identification information") of the space related to the map information to be displayed is input.

[0018] The input unit 21 also accepts edits from the user regarding the displayed map information. Edits include, for example, moving or deleting existing objects in the space, and adding new objects to the space.

[0019] The input unit 21 further receives an instruction from the user to generate a route in the space related to the displayed map information. In the instruction to generate a route, the start point (start point) and end point (destination) of the route (hereinafter, these two points will be referred to as "route endpoints"), and information about the user (hereinafter, referred to as "user information") are input.

[0020] The request sending unit 22 sends to the server device 10 a request (a space display request, a space editing request, or a route generation request) including input information related to a space display instruction, a space editing instruction, or a route generation instruction.

[0021] The display control unit 23 controls the display of a screen or the like based on the display information transmitted from the server device 10.

[0022] On the other hand, the server device 10 has a reception unit 11, an update unit 12, a route generation unit 13, a display information generation unit 14, and a display information transmission unit 15. Each of these units is realized by a process in which one or more programs installed in the server device 10 are executed by a processor 104. The server device 10 also uses a map information storage unit 121, a user information storage unit 122, and a model storage unit 123. Each of these storage units can be realized using, for example, the auxiliary storage device 102, or a storage device connectable to the server device 10 via a network.

[0023] The reception unit 11 receives requests from the terminal device 20 and information related to the requests. For example, the reception unit 11 receives information related to a space display request, information related to a space editing request, and information related to a route generation request. The reception unit 11 receives space identification information of the space to be displayed as information related to the space display request. The reception unit 11 receives information indicating the editing results of map information related to the space to be edited (hereinafter simply referred to as "editing results") as information related to the space editing request. The reception unit 11 receives route endpoints and user information as information related to the route generation request.

[0024] When the receiving unit 11 receives a spatial editing request, the updating unit 12 updates the map information stored in the map information storage unit 121 based on the editing result.

[0025] Map information is stored in the map information storage unit 121 for each candidate space. The map information is information that represents a three-dimensional space, including information (position information and position attribute information) about objects arranged in the space related to the map information. There are several possible ways to represent a three-dimensional space, such as a point cloud, a mesh, or 3D CAD.

[0026] When the receiving unit 11 receives a route generation request, the route generating unit 13 generates a route that corresponds to the space identification information and connects the route endpoints in the space displayed to the user as a target for route generation (the space related to the space identification information specified in the route generation request) based on map information, user information, and route endpoints. When generating the route, the route generating unit 13 uses a route generation model m1 stored in the model storage unit 123.

[0027] The route generation model m1 is a machine learning model (e.g., a neural network) that has learned the correspondence between user information and route endpoints and routes based on learning data that includes, for each map information, user information, route endpoints, and routes that connect the route endpoints according to the user information in the map information (routes that are correct for the user information and the route endpoints).

[0028] The user information storage unit 122 stores attribute information of each user (hereinafter referred to as "user attributes") in association with user identification information (hereinafter referred to as "user ID") that is information for identifying each user (identification information that differs for each user). User attributes are information that differ for each group when users are grouped based on the user attributes. User attributes refer to, for example, the position or role of the user in a space.

[0029] The display information generating unit 14 generates display information indicating map information to be edited or map information relating to a space for which a route is to be generated, display information indicating the generated route, and the like.

[0030] The display information transmitting unit 15 transmits the display information generated by the display information generating unit 14 to the terminal device 20.

[0031] The following describes the processing procedure executed by the information processing system 1. Fig. 4 is a sequence diagram for explaining an example of the processing procedure of the map information update process in the first embodiment.

[0032] In step S101, the input unit 21 of the terminal device 20 receives a display instruction for a certain space from a user. The display instruction includes input of space identification information for the space. The space identification information may be input by, for example, selecting any map information from a list of map information stored in the map information storage unit 121.

[0033] Next, the input unit 21 transmits a space display request including the received space identification information to the server device 10 (S102).

[0034] When the reception unit 11 of the server device 10 receives the space display request, the display information generation unit 14 generates display information (hereinafter referred to as "space display information") of the space related to the space identification information (hereinafter referred to as "target space") based on the map information stored in the map information storage unit 121 in association with the space identification information included in the space display request (S103).

[0035] FIG. 5 is a diagram showing an example of the configuration of the map information storage unit 121. As shown in FIG. 5, the map information storage unit 121 stores, for each space, object identification information, shape information, position information, and position attribute information of each object (a three-dimensional model of the object) placed in the space. The object identification information is identification information of the object and differs for each object. The shape information is information indicating the shape and size of the object. The position information is three-dimensional coordinate information indicating the position of the object in the space (the position of the reference point of the object). The position attribute information is attribute information (related to the placement position) of the object. The position attribute information may be any information related to the object or the placement position of the object. Examples of position attribute information include the type of object, the nature of the object (whether it is a dangerous object, etc.), etc.

[0036] The configuration of the map information shown in FIG. 5 is an example. Information in other formats capable of expressing a three-dimensional space in which a route can be generated may also be used as the map information. The map information may also be data in text format. For example, the map information may be expressed in CSV (Comma Separated Values) or XML (eXtensible Markup Language), etc.

[0037] The display information generating unit 14 generates space display information showing the target space based on such map information.

[0038] Next, the display information transmitting unit 15 transmits the spatial display information generated by the display information generating unit 14 to the terminal device 20 (S104).

[0039] When the display control unit 23 of the terminal device 20 receives the spatial display information, it displays the target space based on the spatial display information and displays a screen (hereinafter referred to as the "spatial screen") on the display device of the terminal device 20 that can accept instructions to edit the target space and instructions to generate a route in the target space, etc. (S105).

[0040] Fig. 6 is a diagram showing an example of a space screen. In Fig. 6, a space screen 510 shows an example in which a space s1, which is a target space, is displayed as a view (plan view) of the target space from above. However, the display format of the space s1 is not limited to a predetermined one.

[0041] Next, the display control unit 23 accepts from the user an edit regarding the placement of objects in the target space (S106). For example, the user can move or delete existing objects, or place new objects in the target space. Note that step S106 may be implemented using 3D CAD software or the like. In this case, the map information may be 3D model information having a format corresponding to the 3D CAD software or the like.

[0042] When the user inputs an instruction to end editing, the request sending unit 22 sends a space editing request including the space identification information of the target space and the editing result to the server device 10 (S107). The editing result may be, for example, all of the edited map information, or information indicating the difference between the edited map information and the map information before editing.

[0043] When the reception unit 11 of the server device 10 receives the space editing request, the update unit 12 updates the map information stored in the map information storage unit 121 (FIG. 5) in association with the space identification information included in the space editing request, based on the editing result included in the space editing request (S108). That is, the update unit 12 reflects the editing result in the map information.

[0044] In this way, the map information for each space can be updated as needed by the user.

[0045] Fig. 7 is a sequence diagram for explaining an example of a processing procedure for a route generation process in the first embodiment. In Fig. 7, the same steps as those in Fig. 4 are assigned the same step numbers, and their explanations will be omitted as appropriate.

[0046] Steps S101 to S105 are as explained in Fig. 4. Therefore, first, the terminal device 20 displays a space screen 510 (Fig. 6) of a space for which a route is to be generated (hereinafter referred to as "target space").

[0047] Next, the input unit 21 receives an instruction to generate a route in the target space from the user (S201). In the instruction to generate a route, user information and route endpoints (start point and end point) are input. Here, an example in which a user ID is input as the user information will be described.

[0048] Next, the request sending unit 22 sends a route generation request including the space identification information of the target space, the user ID, the route endpoints, etc. to the server device 10 (S202).

[0049] When the reception unit 11 of the server device 10 receives the route generation request, the route generation unit 13 acquires map information (i.e., map information of the target space) stored in the map information storage unit 121 (FIG. 5) in association with the space identification information included in the route generation request (S203). The acquired map information will be hereinafter referred to as "target map information." Next, the route generation unit 13 acquires user attributes corresponding to the user ID included in the route generation request from the user information storage unit 122 (S204).

[0050] Fig. 8 is a diagram showing an example of the configuration of the user information storage unit 122. As shown in Fig. 8, the user information storage unit 122 stores user attributes in association with user IDs. The user attributes acquired in step S204 are hereinafter referred to as "target user attributes."

[0051] Next, the route generation unit 13 generates a route that connects the route endpoints in the target space and corresponds to the target user attributes, based on the route endpoints, the target user attributes, and the target map information (S205). At this time, the route generation unit 13 uses the route generation model m1. Specifically, the route generation unit 13 inputs the route endpoints, the target user attributes, and the target map information to the route generation model m1. The route generation unit 13 outputs a route corresponding to the input based on the learned parameters. At this time, the probability that each of the multiple routes is correct may also be output. In this case, the route generation unit 13 acquires the N routes with the highest probabilities. N may be 1 or 2 or more. For convenience of explanation, it is assumed here that N=1. Note that the route may be represented in the target space, for example, by text information indicating a directed graph representing the route, or may be represented in another data format. A directed graph is a graph obtained by defining points (three-dimensional coordinates) through which the route passes (via) in the target space as nodes and connecting the nodes with directed edges. The route may be generated using one of the following methods: (1) A rule-based method that determines the next moving position from the starting point. A path is generated by finding a point (node) that does not hit an obstacle and gradually extending the node (greedy method). If an obstacle is hit, the path is generated by trial and error, returning to the previous node and extending the node in a different direction. (2) Deep learning-based method. This method associates a map (input) with a map (output) depicting the correct route, and learns the correspondence between them end-to-end. A large number of route patterns are learned to generate routes all at once. Alternatively, in addition to the above, the node coordinates of the route can also be learned (as output values). (For example, if a route is represented by a single straight line, there will be two nodes, and if it is represented by two straight lines, there will be three nodes (because the intermediate points are shared).)

[0052] Next, the display information generation unit 14 generates display information (hereinafter referred to as "route display information") for displaying the target route based on the target map information and the route (hereinafter referred to as "target route") generated by the route generation unit 13 (S206). The route display information is, for example, information for displaying the target route in the target space. Next, the display information transmission unit 15 transmits the route display information to the terminal device 20 (S207).

[0053] Upon receiving the route display information, the display control unit 23 of the terminal device 20 updates the spatial screen 510 (FIG. 6) with the route display information, thereby displaying the target route (S208).

[0054] Fig. 9 is a diagram showing a first example of a spatial screen showing a route in the first embodiment. In Fig. 9, the same parts as in Fig. 6 are given the same reference numerals, and their description will be omitted.

[0055] The space screen 510 in Fig. 9 includes a message m11 and a message m12. The message m11 is a message displayed based on the route generation instruction input in step S201. The message m11 may be input by the user, or may be generated by applying the user ID, start point, and end point input by the user to a message template. The message m12 is a fixed phrase for notifying the user that a route has been generated.

[0056] In space s1, a route generated between a start point p1 and an end point p2 is shown by a line segment. It is assumed that space s1 is a machine room. In FIG. 9, since the user's user attribute is "equipment inspector," a route based on the results of learning by the route generation model m1 for equipment inspectors is shown. Specifically, for equipment inspectors, the route generation model m1 has been learned based on learning data in which the correct answer is a route connecting each piece of equipment in order to inspect the equipment placed in a space serving as a machine room, and therefore a route connecting the equipment is also generated for space s1.

[0057] 10 is a diagram showing a second example of a spatial screen showing a route in the first embodiment. In G3, the same parts as those in FIG. 9 are given the same reference numerals, and the description thereof will be omitted.

[0058] FIG. 10 shows an example of a route that is generated when the same start point and end point are specified for the same space s1 as in FIG. 9 by a user with different user attributes from those in FIG. 9. Because the users are different, the user ID included in message m21 is different from the user ID included in message m11 in FIG. 9. The user attribute of the user in FIG. 10 is "general affairs staff." Unlike the equipment inspector, the general affairs staff avoids machines (avoids danger) when passing through a machine room, and therefore the route generation model m1 has been trained based on learning data that treats routes that avoid machines as correct answers, and therefore a route that avoids machines is also generated for space s1.

[0059] As described above, according to the first embodiment, a route is generated based on user information. Therefore, it is possible to generate a route (three-dimensional route) according to the user. For example, for the same target space (three-dimensional space), different routes can be generated according to the user information.

[0060] In the above example, the user information input to the route generation model m1 is user attributes. However, step S204 in FIG. 7 may not be executed, and a user ID may be input to the route generation model m1. In this case, the user information included in the learning data of the route generation model m1 may also be the user ID. In this case, the route generation model m1 learns different parameters for each user.

[0061] Although the above example shows that the user ID is input by the user, the user may input user attributes instead. In this case, step S204 in Fig. 7 is not executed, and the user attributes input by the user are input as they are to the route generation model m1.

[0062] Next, a second embodiment will be described. In the second embodiment, differences from the first embodiment will be described. Therefore, unless otherwise specified, the second embodiment may be the same as the first embodiment.

[0063] In the second embodiment, the output of the route generation model m1 is different. Specifically, the route generation model m1 generates text information describing the route in addition to the route. The text information describing the route is, for example, text such as "This is the shortest route" or "This is a route that avoids danger." Such a route generation model m1 can be obtained by having a machine learning model learn the correspondence between user information and route endpoints, and between the route and text information for each piece of map information, based on learning data including user information, route endpoints, and routes connecting the route endpoints in a space related to the map information, and a route corresponding to the user information and text information describing the route.

[0064] Fig. 11 is a sequence diagram for explaining an example of the processing procedure of the route generation processing in the second embodiment. In Fig. 11, the same steps as in Fig. 7 are assigned the same step numbers, and their explanations will be omitted as appropriate. In Fig. 11, steps S205, S207, and S208 in Fig. 7 are replaced with steps S205a, S207a, and S208a, respectively.

[0065] In step S205a, the route generation unit 13 generates a route that connects route endpoints in the target space and that corresponds to the target user attributes, and text information that explains the route (hereinafter referred to as "output text"), based on the route endpoints, target user attributes, and target map information. Specifically, the route generation unit 13 inputs the route endpoints, target user attributes, and target map information to the route generation model m1. The route generation unit 13 outputs a route and output text that correspond to the input, based on the learned parameters. When multiple routes are output, output text is output for each route.

[0066] In step S207a, the display information transmitting unit 15 transmits to the terminal device 20 the route display information generated in step S206 and the output text generated in step S205a.

[0067] When the display control unit 23 of the terminal device 20 receives the route display information and the output text, it updates the spatial screen 510 (Figure 6) with the route display information and the output text, thereby displaying the target route and the output text (S208a).

[0068] Fig. 12 is a diagram showing an example of a spatial screen showing a route in the second embodiment. In Fig. 12, the same parts as in Fig. 10 are given the same reference numerals, and the description thereof will be omitted.

[0069] 12, the message m12, which was a fixed phrase in FIG. 10, has been replaced with a message m22. The message m22 is a message based on the output text. By referring to such a message, the user can learn an explanation about the route, such as the reason or basis for generating the route.

[0070] Next, a third embodiment will be described. In the third embodiment, differences from the first embodiment will be described. Therefore, points that are not particularly mentioned may be the same as those in the first embodiment.

[0071] In the third embodiment, the input to the route generation model m1 is different. Specifically, the route generation model m1 receives as input text information (hereinafter referred to as "route generation conditions") indicating conditions for the route (restrictions, requests (needs), etc.) in addition to map information, user information, and route endpoints, and generates a route that connects the route endpoints in the space related to the map information and satisfies the route generation conditions according to the user information. The route generation conditions are, for example, text information such as "shortest route," information about objects placed in the target space indicated by the map information, and text information (hereinafter referred to as "size information") indicating the size of moving objects (objects carried by the user). The information about objects placed in the target space indicated by the map information is, for example, text information (hereinafter referred to as "waypoint information") listing identification information of one or more objects that serve as waypoints on the route.

[0072] When the route generation condition is "shortest route," the route generation model m1 outputs the shortest route, which is a route suited to the user associated with the user information. When the route generation condition is "waypoint information," the route generation model m1 generates a route suited to the user associated with the user information, passing through waypoints indicated by the waypoint information. When the route generation condition is "size information," the route generation model m1 generates a route suited to the user associated with the user information, which is a route through which an object of the size indicated by the size information can pass. Such a route generation model m1 can be obtained by having a machine learning model learn the correspondence between user information, route endpoints, route generation conditions, and routes based on training data for each piece of map information, the training data including user information, route endpoints, route generation conditions, and routes connecting the route endpoints in a space associated with the map information, which routes satisfy the route generation conditions according to the user information. That is, the training data includes, as input, user information, route generation conditions, map information (2D or 3D), and route endpoints, and, as output (correct answer), map information in which a route is drawn (added) to the map information. The learning data may also include, as an output (correct answer), text containing the characteristics of the generated route (shortest route, etc.).

[0073] Fig. 13 is a sequence diagram for explaining an example of the processing procedure of the route generation processing in the third embodiment. In Fig. 13, the same steps as in Fig. 7 are assigned the same step numbers, and their explanations will be omitted as appropriate. In Fig. 13, steps S201, S202, and S205 are replaced with steps S201b, S202b, and S205b, respectively.

[0074] In step S201b, the input unit 21 receives input of user information, route endpoints, and route generation conditions in response to the input of a route generation instruction.

[0075] Next, the request sending unit 22 sends a route generation request including the space identification information of the target space, the user ID, the route endpoints, the route generation conditions, etc. to the server device 10 (S202b). Therefore, the receiving unit 11 of the server device 10 receives the route generation request including the space identification information of the target space, the user ID, the route endpoints, the route generation conditions, etc.

[0076] In step S205b, the route generation unit 13 generates a route that connects the route endpoints in the target space and satisfies the route generation conditions according to the target user attributes, based on the route endpoints, the target user attributes, the route generation conditions, and the target map information (S205b). Specifically, the route generation unit 13 inputs the route endpoints, the target user attributes, the route generation conditions, and the target map information to the route generation model m1. The route generation unit 13 outputs a route corresponding to the input based on the learned parameters.

[0077] The route thus generated is displayed in step S208.

[0078] Fig. 14 is a diagram showing a first example of a spatial screen showing a route in the third embodiment. In Fig. 14, the same parts as in Fig. 9 are given the same reference numerals, and the description thereof will be omitted.

[0079] The spatial screen 510 in Fig. 14 further includes a message m13. The message m13 is a message displayed based on the route generation conditions input in step S201. The message m13 may be input by the user, or may be generated by applying the route generation conditions input by the user to a message template. The route generation conditions may also be included in the message m11.

[0080] In Fig. 14, the inputs other than the route generation conditions are the same as in Fig. 9, and an example is shown in which the shortest route is the route generation condition. Therefore, the shortest route among the routes that pass through each device is shown.

[0081] Moreover, Fig. 15 is a diagram showing a second example of a spatial screen showing a route in the third embodiment. In Fig. 15, the same parts as in Fig. 14 are given the same reference numerals, and the description thereof will be omitted.

[0082] 15 includes a message m23 instead of the message m13. Like the message m13, the message m23 is a message that is displayed based on the route generation conditions input in step S201. The message m23 may be input by the user, or may be generated by applying the route generation conditions input by the user to a message template.

[0083] 15 shows an example in which the inputs other than the route generation conditions are the same as those in FIG. 9, and the route generation conditions are to pass through devices A, B, and C. Therefore, FIG. 15 shows a route that passes through only these devices (in other words, a route that does not pass through device D).

[0084] If size information (for example, length, width, height) is input as a path generation condition, a path is generated that allows an object of the size indicated by the size information to pass through.

[0085] Furthermore, a combination of multiple conditions may be input as the route generation conditions. For example, a route generation condition including two or more of the shortest route, route point information, and size information may be input. Furthermore, conditions other than these may be input.

[0086] The third embodiment and the second embodiment may be combined.

[0087] As described above, according to the third embodiment, a route can be generated according to route generation conditions (user needs, etc.) in addition to user information. Therefore, even if the target space (three-dimensional space) is the same, different routes can be generated if the user attributes and route generation conditions are different.

[0088] (1) For example, if the target space is a certain machine room, depending on the learning of the route generation model m1, it is possible to increase the likelihood that the following route will be preferentially generated according to the user attributes and route generation conditions.

[0089] (1-1) When the user attribute is equipment inspector and the route generation condition is a list of equipment to be inspected, it is possible to increase the likelihood that the shortest route that passes through each equipment in the order listed will be generated preferentially.

[0090] (1-2) When the user attribute is set to "evacuees in the event of a disaster" and the route generation condition is set to "shortest route," it is possible to increase the likelihood that the shortest route that avoids dangerous equipment such as equipment that may catch fire will be generated preferentially.

[0091] (1-3) When the user attribute is the person who delivers the equipment and the route generation condition is the size information of the delivered item, it is possible to increase the possibility that a route that does not interfere with the delivered item will be preferentially generated.

[0092] (1-4) When the user attribute = equipment installer and the route generation condition = the equipment to be installed, it is possible to increase the likelihood that a route that prioritizes the ease of installing the equipment (for example, in a situation where installing equipment in the front makes it impossible to install another equipment in the back, a route that allows installation from the back first) will be preferentially generated.

[0093] (2) Furthermore, when the target space is a commercial facility (such as a supermarket or department store), depending on the learning of the route generation model m1, it is possible to increase the likelihood that the following route will be preferentially generated according to the user attributes and route generation conditions.

[0094] (2-1) When the user attribute is customer and the route generation condition is a list of products desired for purchase, it is possible to increase the likelihood that the shortest route for purchasing the products on the list will be generated with priority.

[0095] (2-2) In the case of user attributes = customer, route generation conditions = routes for families with strollers or carts, or routes for elderly people who have difficulty walking, the likelihood of preferentially generating routes that actively use elevators can be increased.

[0096] (2-3) In the case where the user attribute is staff and the route generation condition is a list of replenishment products or a list of products that need to be reviewed in the sales area, the possibility of preferentially generating the shortest route to visit the products listed can be increased.

[0097] (2-4) When the user attribute is on-site security guard and the route generation condition is a list of inspection locations, it is possible to increase the possibility that a route that takes the shortest route around the inspection locations will be generated with priority.

[0098] Furthermore, even if the user attributes and route generation conditions are the same, different routes can be generated if the target space is different.

[0099] (3) For example, if the user attribute is the person who delivers the equipment, and the route generation conditions are the information on the equipment to be delivered and the shortest route, depending on the learning of the route generation model m1, it is possible to increase the likelihood that the following route will be preferentially generated depending on the target space.

[0100] (3-1) When the target space is a space where existing equipment exists, it is possible to increase the likelihood that a route that will not interfere with the delivered items will be preferentially generated.

[0101] (3-2) In the case of a target space where there is no existing equipment (a space immediately after completion), it is possible to increase the likelihood that a route that prioritizes ease of installation of equipment (for example, a route for installing equipment in order from the farthest from the starting point (because if equipment is installed along the way, it will be necessary to avoid the equipment when installing the farther equipment)) will be generated preferentially.

[0102] (4) Furthermore, if the user attribute is a safety inspector and the route generation conditions are a list of equipment to be inspected, the likelihood that the following route will be preferentially generated depending on the target space can be increased depending on the learning of the route generation model m1.

[0103] (4-1) In the case of a target space where the locations of the equipment in the list are varied, it is possible to increase the likelihood that a route with the shortest travel distance will be generated preferentially, regardless of the order of the list.

[0104] (4-2) When the target space is a space where the locations of the facilities in the list are consistent, it is possible to increase the likelihood that a route that passes through the facilities in the order of the list will be generated preferentially.

[0105] (5) Furthermore, if the user attribute is a person who will evacuate in the event of a disaster and the route generation condition is the shortest route that avoids danger, the likelihood that the following route will be preferentially generated depending on the target space can be increased depending on the learning of the route generation model m1.

[0106] (5-1) When the target space is a space where there are no dangerous facilities (for example, a space where no objects are placed), the possibility of generating a route that allows the user to travel from the starting point to the end point in the shortest time can be increased.

[0107] (5-2) In the case of a target space where dangerous equipment exists, it is possible to increase the likelihood that the shortest route that avoids the dangerous equipment will be generated preferentially.

[0108] (6) Furthermore, if the user attribute is customer, the route generation conditions are a list of purchased items, and "low physical burden," then depending on the learning of the route generation model m1, it is possible to increase the likelihood that the following route will be preferentially generated depending on the target space.

[0109] (6-1) When the target space is a space where the products in the list are located on one floor, the possibility of preferentially generating a route with the shortest travel distance can be increased.

[0110] (6-2) Target space = In the case of a space where the products in the list are located on multiple floors, the possibility of preferentially generating routes that prioritize the use of escalators, elevators, and moving walkways can be increased.

[0111] (7) Furthermore, if the user attribute is staff and the route generation condition is “I want to ensure safety quickly in the event of a disaster,” then depending on the learning of the route generation model m1, it is possible to increase the likelihood that the following route will be preferentially generated depending on the target space.

[0112] (7-1) When the target space is a space where people such as customers are present, the likelihood of a route that can guide customers quickly and safely being generated as a priority can be increased.

[0113] (7-2) When the target space is a space where there are no people such as customers, the possibility of preferentially generating a route that will reach the emergency exit from the source of the disaster in the shortest time can be increased.

[0114] (8) Furthermore, if the user attribute is a manager and the route generation condition is "I want to maximize sales," then depending on the learning of the route generation model m1, it is possible to increase the likelihood that the following route will be preferentially generated depending on the target space.

[0115] (8-1) In the case of a target space such as a department store or shopping mall that contains multiple shops, it is possible to increase the likelihood of preferentially generating routes that encourage customers to move between shops and lead to purchases based on past examples (for example, customers who have purchased baby clothes tend to take a break at a cafe, so a route for that purpose can be generated).

[0116] (8-2) In the case of a target space=a sales floor that needs to be replenished, it is possible to increase the possibility that a route that prioritizes the replenishment of products that are frequently out of stock will be generated.

[0117] The text information used as the route generation conditions is not limited to the above. For example, the following text information may be used as the route generation conditions:

[0118] (1) "Please generate a route with steps of 10 cm or less." (2) "Generate a route that is not exposed to light," assuming that the map information for the space contains information showing the results of the light intensity simulation in the space. (3) "Create a route that avoids cold air exposure," assuming that the map information for the space contains information showing the results of the air conditioning simulation overlay for that space. (4) As an example of allowing the air as a movement range, please generate a 3D path for the drone, measuring 1m x 1m x 1m. In the above embodiments, examples have been shown in which the user is also required to specify route endpoints (starting point, ending point). However, it is also possible to consider the existence of spaces in which the candidates for the starting point and ending point are self-evident. For such spaces, the route generation model m1 may be made to learn the starting point and ending point according to the input (user information, etc.), thereby eliminating the need for the user to input route endpoints when generating a route. In such cases, the route endpoints in the above description may be treated as not existing.

[0119] In addition, in each of the above embodiments, an example in which one route generation model m1 is used has been described, but the route generation model m1 may be learned for each piece of user information, each piece of map information, each piece of route generation condition (in the case of the third embodiment), or each combination of two or more pieces of these pieces of input information. In this case, the route generating unit 13 may generate a route using the route generation model m1 according to the input.

[0120] Furthermore, in each of the above embodiments, after the route is displayed, the user may input information indicating whether or not to adopt the route (whether or not to adopt the generated (proposed) route). If not adopted, the user may be allowed to modify the route as desired. In this case, additional learning may be performed on the route generation model m1 based on the input when the adoption or rejection is input and the modification result. In other words, additional learning may be performed on the route generation model m1 based on learning data that sets the route related to the modification result as the correct route for the input.

[0121] Each function of each of the above embodiments can be realized by one or more processing circuits. Here, the term "processing circuit" in this specification includes a processor programmed to execute each function by software, such as a processor implemented by an electronic circuit, as well as devices such as an ASIC (Application Specific Integrated Circuit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), and conventional circuit modules designed to execute each of the above-described functions.

[0122] Additionally, the devices described in the above embodiments are merely illustrative of one of several computing environments for implementing the embodiments disclosed herein.

[0123] In one embodiment, server device 10 includes multiple computing devices, such as a server cluster, configured to communicate with each other over any type of communications link, including a network, shared memory, etc., to perform the processing disclosed herein. Similarly, terminal device 20 may include multiple computing devices configured to communicate with each other.

[0124] Furthermore, the terminal device 20 may have all of the functions of the server device 10.

[0125] The server device 10 and the terminal device 20 are examples of information processing devices.

[0126] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and variations are possible within the scope of the gist of the present invention as described in the claims.

[0127] For example, aspects of the present invention are as follows.

[0128] <1> a reception unit that receives user information related to a user requesting route generation; a route generation unit that generates a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; An information processing device comprising:

[0129] <2> the route generation unit generates a route corresponding to the user information received by the reception unit using a machine learning model that has learned a correspondence relationship between user information and a route based on learning data including user information and a route corresponding to the user information in the map information; Characterized by <1> The information processing device described.

[0130] <3> The space is a three-dimensional space. Characterized by <1> or <2> The information processing device described.

[0131] <4> The user information is user identification information that differs for each user, or information that differs for each group when users are grouped based on user attributes. Characterized by <1> ~ <3> Any of the information processing devices described above.

[0132] <5> the map information includes information about objects arranged in the space; Characterized by <1> ~ <4> Any of the information processing devices described above.

[0133] <6> the route generation unit generates a route according to the user information of the user and text information describing the route using a machine learning model that has learned a correspondence relationship between user information, a route, and text information based on learning data including user information, a route in the map information according to the user information, and text information describing the route; Characterized by <1> ~ <5> Any of the information processing devices described above.

[0134] <7> The receiving unit further receives text information indicating conditions for a route; the route generation unit generates a route corresponding to the user information and text information received by the reception unit using a machine learning model that has learned a correspondence relationship between the user information and text information and the route based on learning data including user information, text information indicating conditions for the route, and the route corresponding to the user information and the text information in the map information; Characterized by <1> ~ <6> Any of the information processing devices described above.

[0135] <8> the text information includes information about an object located in the space indicated by the map information; Characterized by <7> The information processing device described.

[0136] <9> an update unit that updates information included in the map information stored in the storage unit regarding objects arranged in the space in response to an input by a user; characterized in that it has <5> or <8> The information processing device described.

[0137] <10> The receiving unit further receives size information of an object moving along a path, the route generation unit generates a route according to the user information and size information received by the reception unit, using a machine learning model that has learned a correspondence relationship between the user information and size information of the object and the route based on learning data including user information, size information of the object moving along the route, and a route in the map information that corresponds to the user information and is passable by the object; Characterized by <1> ~ <9> Any of the information processing devices described above.

[0138] <11> a reception unit that receives user information related to a user requesting route generation; a route generation unit that generates a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; a display control unit that displays the route; An information processing device comprising:

[0139] <12> a receiving step of receiving user information relating to a user requesting route generation; a route generation step of generating a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; An information processing method characterized by being executed by a computer.

[0140] <13> a receiving step of receiving user information relating to a user requesting route generation; a route generation step of generating a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; A program that causes a computer to execute the following. [Explanation of symbols]

[0141] 1. Information Processing Systems 10 Server device 11 Reception 12 Update section 13 Route generation unit 14 Display information generation section 15 Display information transmission unit 20 Terminal equipment 21 Input section 22 Request sending section 23 Display control unit 100 Drive device 101 Recording media 102 Auxiliary storage device 103 Memory Device 104 processors 105 Interface Device 121 Map information storage unit 122 User information storage unit 123 Model Memory Unit B Bus m1 Route generation model [Prior art documents] [Patent documents]

[0142] [Patent Document 1] Japanese Patent Application Publication No. 2023-992

Claims

1. a reception unit that receives user information related to a user requesting route generation; a route generation unit that generates a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; An information processing device comprising:

2. the route generation unit generates a route corresponding to the user information received by the reception unit using a machine learning model that has learned a correspondence relationship between user information and a route based on learning data including user information and a route corresponding to the user information in the map information; 2. The information processing apparatus according to claim 1, wherein:

3. The space is a three-dimensional space.

2. The information processing apparatus according to claim 1, wherein:

4. The user information is user identification information that differs for each user, or information that differs for each group when users are grouped based on user attributes.

2. The information processing apparatus according to claim 1, wherein:

5. the map information includes information about objects arranged in the space; 2. The information processing apparatus according to claim 1, wherein:

6. the route generation unit generates a route according to the user information of the user and text information describing the route using a machine learning model that has learned a correspondence relationship between user information, a route, and text information based on learning data including user information, a route in the map information according to the user information, and text information describing the route; 2. The information processing apparatus according to claim 1, wherein:

7. The receiving unit further receives text information indicating conditions for a route; the route generation unit generates a route corresponding to the user information and text information received by the reception unit using a machine learning model that has learned a correspondence relationship between the user information and text information and the route based on learning data including user information, text information indicating conditions for the route, and the route corresponding to the user information and the text information in the map information; 2. The information processing apparatus according to claim 1, wherein:

8. the text information includes information about an object located in the space indicated by the map information; 8. The information processing apparatus according to claim 7,

9. an update unit that updates information included in the map information stored in the storage unit regarding objects arranged in the space in response to an input by a user; 9. The information processing apparatus according to claim 5, further comprising:

10. The receiving unit further receives size information of an object moving along a path, the route generation unit generates a route according to the user information and size information received by the reception unit, using a machine learning model that has learned a correspondence relationship between the user information and size information of the object and the route based on learning data including user information, size information of the object moving along the route, and a route in the map information that corresponds to the user information and is passable by the object; 2. The information processing apparatus according to claim 1, wherein:

11. a reception unit that receives user information related to a user requesting route generation; a route generation unit that generates a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; a display control unit that displays the route; An information processing device comprising:

12. a receiving step of receiving user information relating to a user requesting route generation; a route generation step of generating a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; An information processing method characterized by being executed by a computer.

13. a receiving step of receiving user information relating to a user requesting route generation; a route generation step of generating a route in the space according to the user information based on map information indicating a space displayed to the user as a target for generating the route and the user information; A program that causes a computer to execute the following.

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