Autonomous mobile vehicle movement prediction system

Abstract

This system provides an autonomous mobile vehicle movement prediction system that allows users to intuitively check the predicted movement range of an autonomous mobile vehicle. [Solution] The movement prediction system 10 comprises a guide robot 20 and a prediction controller 30 that predicts the movement range of the guide robot 20. The prediction controller 30 has a digital map M that represents the current position R of the guide robot 20 and the predicted movement range P of the guide robot 20. The predicted movement range P includes the error range P1 of the position information of the guide robot 20 and the possible range P2 of the guide robot 20 after a predetermined time has elapsed.

Description

Technical Field

[0006] , , ,

[0001] The present invention relates to a movement prediction system for autonomous mobile bodies.

Background Art

[0002] In an office building, a guiding robot may be placed. A guiding robot is a robot that guides visitors to a destination in an office building. The guiding robot includes an autonomous driving type robot. An autonomous driving type guiding robot does not need to be controlled by a human and can recognize the surrounding environment and move by itself (for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the above-described case, a plurality of guiding robots may be arranged in an office building. In this case, it is necessary to avoid collisions between the guiding robots. For example, if the movement prediction range of the guiding robot can be intuitively confirmed on a digital map of the floor of the office building representing the current position of the guiding robot, collisions between the guiding robots can be avoided.

[0005] Therefore, an object of the present invention is to provide a movement prediction system for an autonomous mobile body that can intuitively confirm the movement prediction range of the autonomous mobile body.

Means for Solving the Problems

[0006] The autonomous mobile body movement prediction system according to the present invention comprises an autonomous mobile body and a control device for predicting the movement range of the autonomous mobile body, wherein the control device has a digital map representing the current position of the autonomous mobile body and the predicted movement range of the autonomous mobile body, and the predicted movement range includes the error range of the position information of the autonomous mobile body and the range in which the autonomous mobile body can exist after a predetermined time has elapsed.

[0007] According to the above configuration, the predicted movement range of the autonomous mobile object, including the error range of the autonomous mobile object's position information, can be intuitively confirmed.

[0008] In the autonomous mobile body movement prediction system according to the present invention, when the current position of the autonomous mobile body can be obtained, it is preferable for the control device to set the possible range of existence as a circle centered on the autonomous mobile body.

[0009] In the autonomous mobile body movement prediction system according to the present invention, it is preferable that the control device sets the possible range of existence toward the direction of movement when the current position and direction of movement of the autonomous mobile body can be obtained.

[0010] In the autonomous mobile body movement prediction system according to the present invention, if the control device can acquire the current position and movement path of the autonomous mobile body, it is preferable to set the possible range of existence along the movement path.

[0011] In the autonomous mobile body movement prediction system according to the present invention, it is preferable that the system comprises multiple autonomous mobile bodies, and that the control device predicts the movement of each autonomous mobile body and predicts collisions between the autonomous mobile bodies.

[0012] With the above configuration, it is possible to intuitively check the predicted movement range of autonomous mobile units and avoid collisions between autonomous mobile units. [Effects of the Invention]

[0013] According to the autonomous mobile vehicle movement prediction system of the present invention, the predicted movement range of the autonomous mobile vehicle can be intuitively confirmed. [Brief explanation of the drawing]

[0014] [Figure 1] It is a schematic diagram showing a movement prediction system which is an example of the first embodiment. [Figure 2] It is a schematic diagram showing an example of a movement prediction range. [Figure 3] It is a schematic diagram showing another example of a movement prediction range. [Figure 4] It is a schematic diagram showing another example of a movement prediction range. [Figure 5] It is a diagram showing a conceptual configuration of a spatio-temporal management system in the second embodiment. [Figure 6] It is a diagram showing a specific example of a procedure for event registration by the spatio-temporal management system in the second embodiment. [Figure 7] It is a diagram showing an example of a functional configuration of a spatio-temporal management device in the second embodiment. [Figure 8] It is a diagram showing an example of a structure of event information in the second embodiment. [Figure 9] It is a flowchart showing an example of a processing procedure according to the registration of an event in the spatio-temporal management system of the second embodiment. [Figure 10] It is a diagram showing an example of format conversion of event information in the second embodiment. [Figure 11] It is a diagram showing an example of format conversion of event information in the second embodiment. [Figure 12] It is a diagram showing an example of space control (movement route change) by the spatio-temporal management device in the second embodiment. [Figure 13] It is a diagram showing an example of space control (movement route change) by the spatio-temporal management device in the second embodiment. [Figure 14] It is a diagram showing a time schedule corresponding to FIG. 14 in the second embodiment. [Figure 15] It is a diagram showing an example of spatio-temporal management using a movement prediction range by the spatio-temporal management device in the second embodiment. [Figure 16]It is a diagram showing another example of spatio-temporal management using the movement prediction range by the spatio-temporal management device in the second embodiment.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the present invention will be described in detail. In the following description, specific shapes, materials, directions, numerical values, etc. are examples for facilitating the understanding of the present invention, and can be appropriately changed according to applications, purposes, specifications, etc.

[0016] [Movement Prediction System (First Embodiment)] The movement prediction system of the first embodiment will be described with reference to FIG. 1.

[0017] The movement prediction system 10 of the present embodiment is provided, for example, in the office building 50. However, the movement prediction system of the present invention may be provided, for example, in a hospital, a commercial building, a public building, etc. The movement prediction system 10 is a system that predicts the movement range of the guide robot 20 as an autonomous mobile body arranged on the floor 51 of the office building 50. According to the movement prediction system 10, the movement prediction range of the guide robot 20 can be intuitively confirmed.

[0018] The movement prediction system 10 includes a guide robot 20 whose details will be described later, a prediction controller 30 as a control device that predicts the movement range of the guide robot 20, and a display device 40 that displays a digital map M and the like to be described later. The guide robot 20, the prediction controller 30, and the display device 40 are connected by a network 55.

[0019] [Guide Robot] The autonomous mobile body of the present embodiment is, for example, a guide robot 20 that autonomously moves on each floor 51. Note that the autonomous mobile body of the present invention may be other than a guide robot as long as it is an autonomous mobile body that autonomously moves. The autonomous mobile body of the present invention may be other robots. Other robots include security robots, patrol robots, etc.

[0020] Furthermore, the autonomous mobile entity of the present invention may not be limited to robots, but may also be a human being, such as a building user 21. The autonomous mobile entity of the present invention may also include a guidance robot 20 and a building user 21. In this case, the movement prediction system allows for intuitive confirmation of the predicted movement ranges of the guidance robot 20 and the building user 21.

[0021] The guidance robot 20 guides visitors to their respective destinations on each floor 51 of the office building 50. These destinations include, for example, restrooms, lounges, and designated tenants. Multiple guidance robots 20 are deployed on each floor 51. The guidance robots 20 do not require human control and move by recognizing their surroundings on their own.

[0022] The guidance robot 20 may have an input unit. The input unit may be a touch panel display, a voice input receiving unit, etc. The guidance robot 20 also has a driving unit. The driving unit may have three or four wheels, etc.

[0023] The guide robot 20 has a robot controller (not shown). The robot controller includes a processor, such as a CPU, a storage device such as semiconductor memory, and an interface with an external device. The storage device stores programs executed by the processor or data used by the processor for processing. The robot controller may have multiple processors, storage devices, interfaces, etc.

[0024] The robot controller may store a digital map of floor 51 where the guidance robot 20 is located. When a visitor enters a destination into the input section, the robot controller moves towards the destination based on the digital map of floor 51. This allows the guidance robot 20 to guide the visitor to their destination.

[0025] [Predictive Controller] An example of a prediction controller 30, which is part of the first embodiment, will be described using Figures 2 to 4.

[0026] The predictive controller 30 predicts the movement range of the guide robot 20. According to the predictive controller 30, as will be described in detail later, the predicted movement range of the guide robot 20 can be intuitively confirmed. The predictive controller 30 includes a processor, such as a CPU, storage devices such as semiconductor memory, and interfaces to external devices. The storage devices store programs executed by the processor or data used by the processor for processing. The predictive controller 30 may have multiple processors, storage devices, interfaces, etc.

[0027] As shown in Figures 2 to 4, the memory device of the prediction controller 30 stores a digital map M of each floor 51. The prediction controller 30 can also acquire at least the current position of the guide robot 20. The digital map M represents the current position R of the guide robot 20. The digital map M also represents the predicted movement range P of the guide robot 20. The predicted movement range P includes the error range P1 of the position information of the guide robot 20 in the digital map M and the possible range P2 of the guide robot 20's presence after a predetermined time has elapsed. In the digital map M, floor F is represented as floor 51.

[0028] The error range P1 is the sum of the error between the position of the guidance robot 20 on the actual floor 51 and the position of the guidance robot 20 on the digital map M, and the position of the guidance robot 20 on the digital map M. The error range P1 is represented as a circle centered on the position of the guidance robot 20 on the digital map M. The diameter of the error range P1 may be determined, for example, based on the maximum error between the position of the guidance robot 20 on the actual floor 51 and the position of the guidance robot 20 on the digital map M over a predetermined period in the past.

[0029] As shown in Figure 2, the possible location range P2 is the range in which the guide robot 20 will be located after a predetermined time has elapsed. When only the current position of the guide robot 20 can be obtained, the possible location range P2 is represented as a circle centered on the current position R on the digital map M. However, the possible location range P2 is represented only in the area on floor 51 in which the guide robot 20 can move. More specifically, the possible location range P2 is not represented in areas where the guide robot 20 does not move, such as walls or elevator shafts.

[0030] As shown in Figure 3, the possible range P2 is set on the direction of movement side when the current position and direction of movement of the guide robot 20 can be obtained. When the direction of movement of the guide robot 20 can be obtained, this includes cases where the prediction controller 30 can obtain the destination of the guide robot 20, or where the prediction controller 30 can obtain the direction of movement of the guide robot 20. More specifically, when the direction of movement of the guide robot 20 can be obtained, the possible range P2 is represented as a circle centered at a predetermined distance in the direction of movement from the current position R on the digital map M.

[0031] As shown in Figure 4, the possible range P2 is set along the movement path when the current position and movement path of the guidance robot 20 can be obtained. Cases in which the movement path of the guidance robot 20 can be obtained include cases where the destination of the guidance robot 20 is known and it is moving through a narrow passage, and cases in which the prediction controller 30 can obtain the future path of the guidance robot 20. More specifically, when the movement path of the guidance robot R can be obtained, the possible range P2 is represented in the digital map M as the range along the movement path with the error range P1 aligned.

[0032] As described above, the prediction controller 30 allows for intuitive confirmation of the predicted movement range of the guide robot 20. Furthermore, the prediction controller 30 displays the predicted movement ranges P of multiple guide robots 20 on the digital map M, and if the predicted movement ranges P of each guide robot 20 come into contact, it can determine the possibility of a collision between the guide robots 20 after a predetermined time has elapsed.

[0033] Collisions between the guidance robots 20 should be avoided, considering the smooth operation and safety of the guidance robots 20. Therefore, it is preferable to modify the operation plan of at least one of the guidance robots 20 so that collisions between multiple guidance robots 20 are avoided.

[0034] [Display device] Let us once again use Figure 1 to describe a display device 40, which is an example of the first embodiment.

[0035] The display device 40 displays the aforementioned digital map M on a display or the like. The digital map M displays the current position of the guidance robot 20 and the predicted movement range P described above. The display device 40 may be installed in a control room or the like so that the manager of the office building 50 can check it. Alternatively, the display device 40 may be installed on floor 51 so that visitors to the office building 50 can check it. The display device 40 allows for intuitive confirmation of the predicted movement range of the guidance robot 20. In addition, the manager can check the likelihood of collisions with the guidance robot 20 in real time.

[0036] [Spatiotemporal Management System (Second Embodiment)] Using Figures 5 to 11, we will describe a spatiotemporal management device 100, which is a second embodiment to which the above-described movement prediction range P is applied.

[0037] Figure 5 shows the conceptual configuration of the spatiotemporal management system (an example of an information processing system) of this embodiment. In the spatiotemporal management system of this embodiment, the spatiotemporal management device 100 manages spatiotemporal matters with respect to the target space 110. In other words, the spatiotemporal management device 100 manages various events occurring in the target space 110 using information defined by space and time. Furthermore, the "management" by the spatiotemporal management device 100 may also include controlling events in the target space 110. In this context, "occurrence" of an event includes not only dynamically changing events such as the movement of people or autonomous mobile devices, or the operation of lighting or air conditioning equipment, but also fixed elements (e.g., a hazardous area) defined for a specific spatial portion of the target space 110. In other words, events in this embodiment may include not only dynamically existing events but also statically existing ones. In the following explanation, the event itself will also be referred to as an event, and the information that defines the event in terms of time and space will also be referred to as event information.

[0038] The target space 110 can be decomposed into, for example, multiple managed-area spaces 111, each representing a different managed object. In the figure, five managed-area spaces 111 (111-1 to 111-5) are shown as an example. Although not shown in the figure, each managed-area space 111 may have a corresponding management system. The figure also shows an example where the target space 110 includes both a real space 110A and a virtual space 110B. Real space 110A includes managed-area spaces 111-1 to 111-4, and virtual space 110B includes managed-area space 111-5. In the figure, an example is shown where real space 110A includes multiple managed-area spaces 111 and virtual space 110B includes one managed-area space 111, but virtual space 110B may also contain multiple managed-area spaces 111.

[0039] Specifically, the managed-area 111-1 is a space in the real-world space 110A where the building structure is the subject of management. The building structure is, for example, a building partition. The building structure corresponding to the managed-area 111-1 may be defined, for example, by a digital map of the building stored in a building management system (not shown). In this case, the building management system may associate information defined for specific spatial areas (spatial parts) formed under the building structure with the digital map, such as dangerous areas where there is a risk to the movement of autonomous mobile objects, or congested areas where people and autonomous mobile objects tend to be crowded.

[0040] The managed-only space 111-2 is a space in which the air conditioning equipment installed in the real space 110A is subject to management. The air conditioning equipment present in the managed-only space 111-2 may be controlled by, for example, an air conditioning management system (not shown) installed in accordance with the real space 110A.

[0041] The managed-separated space 111-3 is a space in which the lighting equipment installed in the real space 110A is the subject of management. The lighting equipment present in the managed-separated space 111-3 may be managed by, for example, a lighting management system (not shown) installed in correspondence with the real space 110A.

[0042] The managed-by-management-specific space 111-4 is a space in which autonomous mobile entities existing in the real space 110A are subject to management. Autonomous mobile entities existing in the managed-by-management-specific space 111-5 may be managed by, for example, an autonomous mobile entity management system (not shown) provided in correspondence with the real space 110A.

[0043] The managed-by-management space 111-5 is a space constructed as a digital twin, a virtual space 110B corresponding to the target space 110. In the virtual space 110B as a digital twin, for example, a user as a person can exist as an avatar. The virtual space 110B as a digital twin may be managed by a virtual space management system (not shown).

[0044] In addition to the examples above, the managed-by-management spaces 111 may also include spaces that manage people present in the real space 110A, spaces that manage equipment other than air conditioning and lighting (e.g., elevators), and spaces that manage static objects such as furniture and fixtures. In the case of a managed-by-management space 111 that manages people, management related to people may be carried out by, for example, a schedule management system that manages people's schedules in the real space 110A.

[0045] The specific examples of the space designated as the target space 110 are not particularly limited. The target space 110 may, for example, be a space corresponding to the interior of a building. Furthermore, the target space 110 may be a space including the building and its surrounding outdoor area, a commercial facility, a leisure facility, a public facility, a park, etc., or a block of a predetermined area.

[0046] The spatiotemporal management device 100 manages each of the various events occurring in the target space 110 using event information in a format defined by time and space. In the correspondence with the target space 110 illustrated in Figure 5, each event occurring in each of the managed separate spaces 111 is managed using a common event format. In other words, the spatiotemporal management device 100 in this embodiment can centrally manage a variety of events occurring in the target space 110, regardless of the differences in the types of managed objects for each managed object space 111, using event information in a common format. Furthermore, this management by the spatiotemporal management device 100 can be viewed as integrating and managing the managed object spaces 111 that exist individually within the target space 110. The spatiotemporal management device 100 may be configured to control building structures, air conditioning, lighting, autonomous mobile devices, avatars in virtual space 110B, etc., by coordinating with management systems corresponding to each of the managed spaces 111.

[0047] [Event Registration] Figure 6 illustrates a specific example of the event registration procedure in a spatiotemporal management system.

[0048] The spatiotemporal management device 100 is connected to the external management system 120 in a communicative manner. The external management system 120 may be a system that manages targets corresponding to one of the managed object spaces 111 in Figure 5, for example. Specifically, if it is managed object space 111-4 for managing autonomous mobile objects, then the management system for managing autonomous mobile objects corresponds to the external management system 120. In order to enable the spatiotemporal management device 100 to manage events (phenomena) under its control, the external management system 120 performs event registration to register the event information of the target event with the spatiotemporal management device 100 (step S10). As part of the event registration, the external management system 120 transmits registration information indicating the content of the event (phenomenon) to be registered to the spatiotemporal management device 100.

[0049] The spatiotemporal management device 100 generates event information 130 based on registration information received from the external management system 120 (step S12). The event information is in a format that includes, for example, event type information, area information, schedule information, and metadata. Event type information indicates the type of event being handled. Area information indicates the area (spatial domain) related to the corresponding event. The schedule information contains time-related information about the corresponding event. Metadata is information that describes various attributes of the event in question.

[0050] The spatiotemporal management device 100 determines the type of event indicated in the received registration information and generates event type information indicating the determined event type.

[0051] Furthermore, the spatiotemporal management device 100 converts the information indicating the area corresponding to the event, which is included in the received registration information, from a format compatible with the external management system 120 to a format compatible with event information, thereby generating area information.

[0052] Furthermore, the spatiotemporal management device 100 generates a timestamp based on the time information about the corresponding event included in the received registration information, and associates the generated timestamp with a spatial region indicated in the area information, for example. That is, the timestamp associated with the spatial region in the area information may be used as schedule information. In other words, event information, through area information and schedule information, can define the relationship between space and time for a corresponding event. For example, in the event information for a movement event corresponding to an autonomous mobile object, the relationship between space and time is defined such that the schedule information indicates the time the autonomous mobile object occupies a spatial area corresponding to the movement path indicated by the area information.

[0053] Furthermore, the spatiotemporal management device 100 generates metadata by adding information indicating attributes of the corresponding event included in the received registration information.

[0054] The spatiotemporal management device 100 performs processing corresponding to the registration of the generated event information (event registration processing) (step S14). As part of the event registration processing, the spatiotemporal management device 100 determines whether there is any spatiotemporal overlap between the generated event information and event information already stored (registered) in the event information storage unit 131. If there is no overlap with other event information, the spatiotemporal management device 100 may newly store the generated event information in the event information storage unit 131. The event information storage unit 131 stores the registered event information as a database. On the other hand, if the spatiotemporal management device 100 finds that the generated event information overlaps with other event information, it modifies at least one of the overlapping event information and the generated event information to avoid duplication, and then stores the generated event in the event information storage unit 131. In this case, if other event information is changed, the spatiotemporal management device 100 updates the other event information stored in the event information storage unit 131 with the changed content.

[0055] [Space-time management device] The configuration of the spatiotemporal management device 100 will be explained using Figure 7.

[0056] The spatiotemporal management device 100 includes hardware such as a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), and SSD (Solid State Drive). The functions of the spatiotemporal management device 100 shown in the figure are realized by the CPU in the spatiotemporal management device 100 executing a program.

[0057] The spatiotemporal management device 100 in Figure 7 comprises a communication unit 101, a control unit 102, and a storage unit 103. The communication unit 101 is connected to various devices shown in Figure 6 via a network (wireless / wired) to enable communication.

[0058] The control unit 102 performs various controls in the spatiotemporal management device 100. The control unit 102 includes an event processing unit 121 (an example of an event processing unit). The event processing unit 121 manages events in the target space 110 by processing event information stored in the event information storage unit 131. The event processing unit 121 can also generate event information based on the definition of a specified event and store (register) the generated event information in the event information storage unit 131. The processes in steps S12 and S14 of Figure 6 may be executed by the event processing unit 121.

[0059] The memory unit 103 stores various types of information corresponding to the spatiotemporal management device 100. The memory unit 103 in the figure includes an event information storage unit 131. The event information storage unit 131 stores events. An event is information used by the spatiotemporal management device 100 for spatiotemporal management, and is information that defines a predetermined event in the target space 110. The event information storage unit 131 stores event information corresponding to each event in the target space 110.

[0060] Figure 8 shows an example of the structure of event information corresponding to a single event. Each event information entry includes fields for event type, area, schedule, and metadata.

[0061] The event type information field stores event type information indicating the type of the corresponding event. Event types may be classified as follows: events that define an area in the target space 110, events that control the movement of autonomous mobile units, events that guide the movement of users (non-autonomous movement), events that represent objects themselves such as furniture and fixtures, and events that detect predetermined items such as congestion or disaster conditions in a specific area of ​​the target space. In addition, the event type may also indicate the management type corresponding to the managed space 111 explained in Figure 5.

[0062] The area information field stores area information (an example of spatial domain information) corresponding to an event. Area information is information describing the region (spatial domain) within the target space 110 to which the event corresponds. The area information field may also store information indicating which of the managed space 111 described in Figure 5 the corresponding event belongs to. As a concrete example, if an event defines a spatial area within the target space 110 that an autonomous mobile object can pass through, the area information will contain a description indicating the spatial area that the autonomous mobile object can pass through. The spatial area indicated by the area information may be represented, for example, by the coordinates of the corresponding space. The spatial region described by the area information may be a planar (two-dimensional) region in the target space 110, or it may be a region in three-dimensional space.

[0063] Furthermore, area information may also define the shape of the spatial domain as a corresponding three-dimensional space. Specifically, the shape of the spatial domain in area information may be defined by coordinates, by three-dimensional geometric shapes such as cuboids or spheres, by a shape formed by stacking one or more cubes in a voxel format, or by a complex shape using 3D data. In addition, depending on the area information, the shape of the spatial domain may be defined as changing over time based on conditions (triggers) such as metadata.

[0064] The schedule information field stores schedule information for the corresponding event. For example, if an event defines a combination of spatial areas and time periods in which an autonomous mobile object can pass through within the target space, the schedule information will contain a description indicating the time periods in which the autonomous mobile object can pass through.

[0065] In addition to dynamic events that change over time, events may also be static events that do not change over time. Examples of dynamic events include, for instance, "the changing position of an autonomous mobile object over time," "time slot reservations for a rental space," and "the congestion rate of a space at a given time." Examples of static events include, for example, "areas where autonomous vehicles can travel (fixed)", "areas where autonomous vehicles are prohibited from entering (fixed)", "areas where autonomous vehicles are prohibited from stopping", and "hourly rental fees for areas". Schedule information corresponding to dynamic events may include timestamps that reflect changes in the corresponding event over time. On the other hand, scheduling information corresponding to static events may be configured to stipulate that there are no changes over time regarding the corresponding event.

[0066] Metadata is information that describes various attributes of a target event (phenomenon). The diagram shows an example of the definition of metadata items included in the metadata. In the diagram, the metadata items include event ID, space occupancy status, priority, pre-event, post-event, related events, movement status, moving entity, origin point, destination point, area change status, space definition, and status reference. The metadata may include metadata items used for managing the corresponding event from among the metadata items listed above. Furthermore, the metadata may include metadata items other than those listed above, depending on the definition of the corresponding event.

[0067] The Event ID metadata is an identifier that uniquely identifies the corresponding event.

[0068] The space occupancy metadata indicates whether the spatial area defined by the area information of the corresponding event can be occupied, excluding the spatial areas of other events. If the space occupancy metadata indicates "Yes," the spatial area of ​​the corresponding event is not allowed to overlap with the spatial areas of other events. If the space occupancy metadata indicates "No," the spatial area of ​​the corresponding event is allowed to overlap with the spatial areas of other events.

[0069] Priority metadata indicates priority regarding spatial occupancy. For example, if the metadata for spatial occupancy of an event indicates "Yes," and the metadata for spatial occupancy of other overlapping events also indicates "Yes," then the event with the highest priority can occupy the spatial area, excluding the other events.

[0070] Pre-event metadata is used when there are pre-events (events that must be processed before the corresponding event) that should be triggered, and it indicates the event ID of the pre-event. Metadata for a post-event is included when there are events (post-events) that should be processed following the corresponding event, and it indicates the event ID of the post-event. Related event metadata is used when there are other events (related events) that are highly relevant to the corresponding event, and it indicates the event ID of the related event.

[0071] The metadata indicating whether or not movement occurred indicates whether the corresponding event involved the movement of a moving object, such as a user or an autonomous mobile device. Here, "movement" can be distinguished into "autonomously mobile (like a service robot)", "not autonomously moving but can be moved to a different location (like furniture)", and "not moving".

[0072] The metadata for the moving entity indicates what the moving entity is when the metadata for the corresponding event indicates "movement occurred". The moving entity may be, for example, an autonomous mobile object moving in real or virtual space, a person (user) moving in real space, or an avatar moving in virtual space. If the moving entity is an autonomous mobile unit, the event processing unit 121 executes processing related to the autonomous movement of the target autonomous mobile unit based on the corresponding event.

[0073] The metadata for the starting point indicates the starting point defined for the corresponding movement when the metadata for movement status indicates "movement occurred". The starting point may be indicated, for example, as coordinates within the target space 110. The destination metadata indicates the destination specified for the corresponding movement when the movement metadata indicates "movement occurred". The destination may be indicated, for example, as coordinates within the target space 110. For example, if the corresponding event information describes the movement of a certain autonomous mobile object, and the preceding or succeeding event also describes the movement of the same autonomous mobile object, the arrival point of the preceding event and the departure point of the following event may be set to indicate the same coordinates.

[0074] The metadata indicating whether or not an area has been changed shows whether or not the spatial region described in the area information of the corresponding event information can be changed.

[0075] The spatial definition metadata indicates the definition of the spatial region indicated by the area information stored in the corresponding event information. For example, depending on the spatial definition metadata, it may be possible to indicate whether the corresponding spatial region is an area where autonomous mobile units can pass or an area where autonomous mobile units are prohibited from passing. Furthermore, the spatial definition metadata may include data that describes the characteristics of that specific spatial region. For example, it may include temperature values, illuminance values, etc., at specific points in that space. These values ​​may be measured values, values ​​calculated through simulation, or values ​​(thresholds) that are specified as conditions. The comparison, calculation, and conditional branching of this metadata may be reflected in the control that spans across different managed spaces.

[0076] The metadata for the state reference indicates the reference destination when the corresponding event information needs to refer to a predetermined state. Specifically, if the corresponding event information is defined as representing a sensing result, the metadata for the state reference indicates the reference destination, such as a database that stores the sensing results.

[0077] Referring to the flowchart in Figure 9, an example of a processing procedure corresponding to event registration in the spatiotemporal management system of this embodiment will be described. Step S100: In the spatiotemporal management device 100, the event processing unit 121 generates event type information indicating the corresponding event type based on the input information specifying the event type.

[0078] Step S102: The event processing unit 121 generates area information based on the information corresponding to the input area definition.

[0079] Step S104: The event processing unit 121 generates schedule information based on the time information specified in relation to the target event. Note that the processing in step S104 may be omitted if, for example, the target event simply defines a spatial region and does not require a definition related to time.

[0080] Step S106: The event processing unit 121 generates metadata based on the metadata data for each item entered in response to the target event.

[0081] Step S108: The event processing unit 121 generates event information including the event type information generated in step S100, the area information generated in step S102, the schedule information generated in step S104, and the metadata generated in step S106. The event processing unit 121 stores the generated event information in the event information storage unit 131.

[0082] Step S110: The event processing unit 121 determines whether the event defined by the newly generated event information (new event information) in step S108 overlaps (interferes with) other events defined by other registered event information. Here, other registered event information refers to event information stored in the event information storage unit 131. As a specific example of overlap, if the event defined by the new event information is a movement event that defines the movement of an autonomous mobile body, then the spatial movement by the autonomous mobile body defined by the new event information may overlap with spatial movement by other registered movement events, or with an exclusive area defined as an event by an area event.

[0083] Step S112: The event processing unit 121 determines whether or not there are duplicates in the result of the determination in step S110.

[0084] Step S114: If it is determined in step S112 that there are no duplicates, the event processing unit 121 registers new event information. In other words, the event processing unit 121 stores the new event information in the event information storage unit 131.

[0085] Step S116: On the other hand, if it is determined in step S112 that there is a duplicate, the event processing unit 121 decides which event information to change in order to resolve the duplicate from the new event information and the event information of other registered events that have a relationship of overlap with the new event information. At this time, the event processing unit 121 may refer to information such as priority, whether or not there is movement, whether or not there is an area change, etc., of the new event information and the other event information, and may decide not to change the event information and to decide which event information can be changed, or to decide which event information has a lower priority to change. Alternatively, in step S116, it may decide to change both the new event information and the other event information.

[0086] Step S118: The event processing unit 121 modifies the event information that was determined to be changed in step S116 so that duplication is eliminated. Specific examples of such duplication elimination modifications to event information will be described later.

[0087] Step S120: The event processing unit 121 determines whether or not the event information modified in step S118 includes other registered event information.

[0088] Step S122: If it is determined in step S120 that other event information was included, the event processing unit 121 updates the other event information stored in the event information storage unit 131 with the content changed in step S118. After the processing in step S122, the process transitions to step S114, where new event information is registered. In this case, the newly registered event information may have been modified by step S118.

[0089] On the other hand, if step S120 determines that no other event information already registered is included, the event processing unit 121 skips step S122 and proceeds to the processing in step S114. In other words, in this case, the new event information modified in step S118 is registered.

[0090] Alternatively, the external management system 120 may perform the event information generation process from steps S100 to S108, then transmit the generated event information to the spatiotemporal management device 100, and the spatiotemporal management device 100 may register the event information by performing the processing from step S110 onward in response to receiving the event information.

[0091] As described above, in this embodiment, in order to standardize the format of event information among various events, a format conversion is performed, for example, to convert the format corresponding to an external management system to a format corresponding to event information (event-compatible format).

[0092] Figure 10 shows an example of format conversion. The digital map MP1-1 in the figure is an example of a digital map corresponding to a certain building in the target space 110. The line diagrams represented in the digital map MP1-1 correspond to the line representation of the map in the external management system and the virtual walls on the map of the robot travel management system. In this figure, for convenience, a two-dimensional digital map of the building viewed from a planar perspective is shown, but the digital map MP1-1 may be a three-dimensional digital map. In the digital map MP1-1, walls, partitions, and other structures within a building are represented by lines. The event processing unit 121 of the spatiotemporal management device 100 generates area information from the building structure shown in the digital map MP1-1, and performs a format conversion to the area format defined in this invention, as shown in the digital map MP1-2 in the same figure. In other words, the event processing unit 121 converts the building structure shown by lines in the digital map MP1-1 into a spatial range (i.e., an area) with area and volume. By converting the space represented by lines into an area in this way, the structural space within a building can be treated as area information in an event.

[0093] Figure 11 also shows another example of format conversion. The digital map MP2-1 in the figure shows the travel path information of an autonomous mobile entity managed by an external system. The travel path information managed by the external management system is represented by waypoints WP1, WP2, and WP3, as shown in the figure. Waypoint WP1 indicates the starting point, waypoint WP3 indicates the arrival point (destination), and waypoint WP2 indicates a relay point.

[0094] The event processing unit 121 converts the movement path indicated by waypoints on the digital map MP2-1 into a movement path RT1 consisting of a ribbon-shaped area with a predetermined width, as shown on the digital map MP2-2. By converting the movement path RT1 into an area format in this way, it becomes possible to treat the movement path of the autonomous mobile object as area information represented by area and volume in events that define the movement of the autonomous mobile object. The width of the converted movement path may be set based, for example, on the maximum width of the corresponding autonomous mobile object when viewed from the front. In this case, the width of the converted movement path may be the maximum width of the autonomous mobile object when viewed from the front, plus a safety margin width to avoid contact with surrounding people or objects. Alternatively, information on both the maximum width and the width with the margin width added may be used for the width of the converted movement path.

[0095] This format conversion of the movement path of an autonomous mobile object into area information may also be applied to events such as those that involve the planned movement of an avatar in the virtual space 110B.

[0096] The spatiotemporal management device 100 of this embodiment processes events generated as described above and stored in the event information storage unit 131, thereby enabling appropriate control of various aspects of the target space 110, regardless of whether the corresponding target space 110 is a real space or a virtual space.

[0097] [Examples of applications for spatiotemporal management systems] Using Figures 12 to 14, an example of spatiotemporal management by the spatiotemporal management device 100 will be explained, specifically regarding event control (spatiotemporal management) when changing (modifying) the movement path while moving a moving subject.

[0098] The event control described below may target either the real space 110A or the virtual space 110B within the target space 110. Furthermore, the control of the moving entity here may be the control of an autonomous mobile object in the real space, or it may be the guidance of a user (human) for movement. Also, the control of the moving entity here may be the control of an avatar in the virtual space 110B, or the guidance of a movement path for an avatar corresponding to a user. The following explanation uses the example of changing the movement path of an autonomous mobile object in real space.

[0099] In Figure 12, the digital map MP3-1 shows the movement path RT2 within the target space 110, indicated by the area information of event information (movement event information) in which the movement of a single autonomous mobile object is defined as an event (movement event). The event processing unit 121 determines the interference status between the movement path RT2 indicated by the current movement event information and events (phenomena) indicated by other event information, as part of the movement control of the autonomous mobile body based on movement event information. Therefore, the event processing unit 121 searches for event information from the event information stored in the event information storage unit 131 for events (phenomena) that overlap (interfere) with, for example, the combination of the movement path indicated by the movement event information and the time (movement time) during which the movement along that movement path takes place. Here, we take the example of when three events corresponding to digital maps MP3-2, MP3-3, and MP3-4 in Figure 12 are found. Digital map MP3-2 shows the spatial area (movable area AR1) in which autonomous mobile objects can move within the same target space 110 that the movement event targets. In other words, digital map MP3-2 shows the content of event information that defines the movable area AR1 in the same target space 110 that the movement event information targets, as area event information that defines an event as a spatial area (area event).

[0100] Regarding area event information, there are cases where it does not include schedule information and cases where it does. Area event information that does not include schedule information is configured so that the definition of the spatial area indicated by the area information is valid at all times. Area event information that includes schedule information is configured so that the definition of the spatial area indicated by the area information is valid only for the time period indicated by the schedule information.

[0101] Digital map MP3-3 shows the spatial area (no-entry area AR2) where entry by autonomous mobile units is prohibited within the same target space 110 that the movement event information targets. In other words, digital map MP3-3 shows the content of the area event that defines the no-entry area AR2 within the same target space 110 that the movement event targets.

[0102] Digital map MP3-4 shows the spatial region (stop-prohibition area AR3) where the autonomous mobile object is prohibited from pausing within the same target space 110 that the movement event targets. In other words, digital map MP3-4 shows the content of the area event that defines the stop-prohibition area AR3 within the same target space 110 that the movement event targets.

[0103] Furthermore, the digital map MP3-5 in Figure 13 shows reserved area AR5, which is set up in the same target space 110 as the movement event, and overlaps with the movement time indicated by the corresponding movement event information. During the time when reserved area AR5 is active, entry of autonomous mobile units into reserved area AR5 is prohibited based on metadata such as whether the space can be occupied and its priority.

[0104] The event processing unit 121 compares the travel route RT1, defined by the travel event information as shown in the digital map MP2-2, with the movable area AR1, the no-entry area AR2, the no-stop area AR3, and the reserved area AR5. The digital map MP3-6 in Figure 14 shows the results of comparing the travel route RT2 with the accessible area AR1, the no-entry area AR2, the no-stop area AR3, and the reserved area AR5. As can be seen from the digital map MP3-6, the area currently designated as the travel route RT2 is located within the accessible area AR1 and does not overlap with the no-entry area AR2, but it partially overlaps with the reserved area AR5.

[0105] Furthermore, the time schedule table in Figure 14 shows an example of how the schedule for travel route RT2 is compared with the schedules for the accessible area AR1, the no-entry area AR2, the no-stop area AR3, and the reserved area AR5, based on the schedule information. The movable area AR1, the no-entry area AR2, and the no-stop area AR3 are defined as permanently existing areas, without any time-based scheduling information or events. On the other hand, reservation area AR5 has its time slot determined by the event schedule information. Specifically, in the diagram, reservation area AR5 is set for the period from time t1 to t4. Furthermore, the autonomous mobile unit's travel path RT1 is determined by the schedule information to be a period from time t2 to t3. As can be seen from the figure, the period from time t2 to t3 during which the autonomous mobile object moves along the travel path RT1 overlaps with the period during which the no-entry area AR2, the no-stop area AR3, and the reserved area AR5 are set.

[0106] Therefore, the event processing unit 121 searches for a route for travel route RT2 that does not overlap with the reserved area AR5, as illustrated in the digital map MP3-7 in Figure 13, and changes the travel route to the searched route. The event processing unit 121 updates the area information of the travel event information to show the changed travel route RT2.

[0107] In this way, the event processing unit 121 can properly manage spatiotemporal relationships by adjusting the temporal and spatial overlaps between events based on the time schedule. The event processing unit 121 may notify the external management system that manages the target in the corresponding managed space 111 of the updated travel path RT2. In this case, the event processing unit 121 may convert the travel path RT2 into a format supported by the external management system to be notified (for example, a waypoint format) before notifying it.

[0108] [Examples of applying movement prediction range in spatiotemporal management systems] Using Figures 15 and 16, we will explain another example of spatiotemporal management by the spatiotemporal management device 100: event control (spatiotemporal management) using the movement prediction range P.

[0109] As described above, the spatiotemporal management device 100 may, as part of its event registration process, determine whether there is spatiotemporal overlap between the generated event information and event information already stored (registered) in the event information storage unit 131. In order to confirm spatiotemporal "event" overlap, it is necessary to compare both schedule information and area information in correspondence, which makes it difficult to handle situations where high real-time processing is required.

[0110] For example, to prevent collisions between multiple moving objects, and to avoid spatiotemporal overlap between "movement event of moving object A" and "movement event of moving object B," it is not practical from a system processing standpoint to check the area information and schedule information of each event, which are updated frequently with each movement. Furthermore, for operators using the system, it is difficult to check both schedule information and area information simultaneously, as they need to grasp both at the same time.

[0111] Therefore, the following defines the area information in the schedule information for an autonomous mobile object for a movement event. In this case, the area information defines the movement prediction range P mentioned above. Specifically, we take the example of performing spatial control on the aforementioned guidance robot 20, which is an autonomous mobile object in the real space 110A within the target space 110.

[0112] As shown in Figure 15, the digital map MP4-1 shows two predicted movement ranges PA and PB after a predetermined time has elapsed, which are defined by the operation plans defined by the movement events of two guide robots 20 as an example. In Figure 15, the predicted movement ranges PA and PB are shown to be in contact. The contact of the predicted movement ranges of multiple guide robots 20 corresponds to the guide robots 20 colliding with each other after a predetermined time has elapsed.

[0113] In this context, "collision" may include not only situations where the two guide robots 20 physically come into contact, but also situations where they are not physically in contact but are within a certain distance of each other. In other words, under the current operating schedule for the two guide robots 20, a situation arises where the two guide robots 20 will collide after a predetermined time has elapsed. The event processing unit 121 of the spatiotemporal management device 100 recognizes the above collision situation by referring to the movement events of the two guide robots 20.

[0114] Collisions between the guidance robots 20 are preferable to avoid, considering the smooth operation and safety of the guidance robots 20. Therefore, in this example, as a control measure when the predicted movement ranges PA and PB of multiple guidance robots 20 overlap, the spatiotemporal management device 100 modifies the operation plan of the guidance robots 20 in a movement event so as to avoid collisions between the multiple guidance robots 20.

[0115] As shown in Figure 16, the digital map MP4-2 displays the predicted movement range P after a predetermined time has elapsed, as defined by each of the driving plans defined by the movement events of the guidance robot 20 as an example. The digital map MP4-2 also contains a hazardous area AR6. A hazardous area AR6 is an area that is defined as being hazardous by its corresponding area event. Whether an area event corresponds to a hazardous area may be defined by the event type. Furthermore, if a hazardous area has specific time periods when it is hazardous and other time periods when it is not, the time periods when it is hazardous may be defined by the schedule information. In addition, information indicating the degree of hazard in a hazardous area may be stored as one of the metadata items in the area event.

[0116] The digital map MP4-2 shows, as an example, the predicted movement range P after a predetermined time has elapsed, as defined by each of the operation plans defined by the movement events of the guidance robot 20. In Figure 16, the predicted movement range P overlaps with the hazardous area AR6. The overlap of the predicted movement range P with the hazardous area AR6 corresponds to the guidance robot 20 entering the hazardous area AR6 after a predetermined time has elapsed. Therefore, in this example, as a control measure when the predicted movement range P of the guidance robot 20 overlaps with the hazardous area AR6, the spatiotemporal management device 100 modifies the operation plan of the guidance robot 20 in the movement event so that the guidance robot 20 does not enter the hazardous area AR6.

[0117] [summary] The present invention is further described by the following embodiments. Configuration 1: The system comprises an autonomous mobile unit and a control device that predicts the movement range of the autonomous mobile unit. The control device has a digital map representing the current position of the autonomous mobile body and the predicted movement range of the autonomous mobile body. The movement prediction range includes the error range of the position information of the autonomous mobile body and the range in which the autonomous mobile body can exist after a predetermined time has elapsed. A system for predicting the movement of autonomous mobile objects. Configuration 2: The autonomous mobile body movement prediction system described in Configuration 1, If the control device can acquire the current position of the autonomous mobile body, it sets the possible range of existence as a circle centered on the autonomous mobile body. A system for predicting the movement of autonomous mobile objects. Configuration 3: The autonomous mobile body movement prediction system described in configuration 2, If the control device can acquire the current position and direction of movement of the autonomous mobile body, it sets the possible range of existence toward the direction of movement. A system for predicting the movement of autonomous mobile objects. Configuration 4: The autonomous mobile body movement prediction system described in configuration 2, If the control device can acquire the current position and movement path of the autonomous mobile body, it sets the possible range of existence along the movement path. A system for predicting the movement of autonomous mobile objects. Configuration 5: A movement prediction system for an autonomous mobile body as described in any of configurations 1 to 4, The autonomous mobile unit comprises multiple such units, The control device predicts the movement of each of the autonomous mobile units and predicts collisions between the autonomous mobile units. A system for predicting the movement of autonomous mobile objects.

[0118] It should be noted that the present invention is not limited to the embodiments and their modifications described above, and various changes and improvements are possible within the scope of the claims of this application. [Explanation of symbols]

[0119] 10 Movement prediction system, 20 Guidance robot (autonomous mobile unit), 25 Robot controller, 30 Prediction controller (control device), 40 Display device, 50 Office building, 51 Floor, 55 Network, 100 Spatiotemporal management device, 101 Communication unit, 102 Control unit, 103 Storage unit, 110 Target space, 110A Real space, 110B Virtual space, 111 Spaces managed by specific entities, 120 External management system, 121 Event processing unit, 130 Event information, 131 Event information storage unit

Claims

1. The system comprises an autonomous mobile unit and a control device that predicts the movement range of the autonomous mobile unit. The control device has a digital map representing the current position of the autonomous mobile body and the predicted movement range of the autonomous mobile body. The movement prediction range includes the error range of the position information of the autonomous mobile body and the range in which the autonomous mobile body can exist after a predetermined time has elapsed. A system for predicting the movement of autonomous mobile objects.

2. A movement prediction system for an autonomous mobile body according to claim 1, If the control device can acquire the current position of the autonomous mobile object, it sets the autonomous mobile object as the center of a circle. A system for predicting the movement of autonomous mobile objects.

3. A movement prediction system for an autonomous mobile body according to claim 2, If the control device can acquire the current position and direction of movement of the autonomous mobile body, it sets the possible range of existence toward the direction of movement. A system for predicting the movement of autonomous mobile objects.

4. A movement prediction system for an autonomous mobile body according to claim 2, If the control device can acquire the current position and movement path of the autonomous mobile body, it sets the possible range of existence along the movement path. A system for predicting the movement of autonomous mobile objects.

5. A motion prediction system for an autonomous mobile body according to any one of claims 1 to 4, The autonomous mobile unit comprises multiple such units, The control device predicts the movement of each of the autonomous mobile units and predicts collisions between the autonomous mobile units. A system for predicting the movement of autonomous mobile objects.

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