system

Abstract

To make enable provision of map information that allows a moving object to move along an appropriate route according to a task when performing the task.SOLUTION: A system 1 comprises a rule storage unit 104, an attribute value storage unit 105, an acquisition unit 101, a generating unit 102, and a transmitting unit 103. The rule storage unit 104 stores a rule indicating whether or not an attribute value of each attribute in each area can be moved to an area of the attribute value for each task that can be assigned to a moving object. The attribute value storage unit 105 stores an attribute value of each attribute in a predetermined area. The acquisition unit 101 acquires a task assigned to the moving object in the predetermined area. The generating unit 102 generates map information indicating whether or not the moving object can be moved to the predetermined area based on the acquired rule according to the task and the attribute value of each attribute in the predetermined area. The transmitting unit 103 transmits the generated map information to the moving object.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to systems and the like. [Background technology]

[0002] There is a technology in which a mobile object moves autonomously based on map information. Patent Document 1 describes a system that uses multiple mobile robots to guide a user, in which the map information is updated based on information acquired by the multiple mobile robots. For example, Patent Document 1 also describes that the mobile robot calculates a walking route from destination information, self-location information, and map information, and guides the user to walk along the calculated walking route. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-211961 Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, map information is generated for when a mobile robot guides a user. However, tasks vary depending on the mobile object. Therefore, when performing a task, the mobile object may move through a location that is inappropriate for that task.

[0005] An example of an object of the present disclosure is to provide a system or the like that can provide map information that enables a mobile object to travel an appropriate route for performing work. [Means for solving the problem]

[0006] A system according to one aspect of the present disclosure includes a rule storage means for storing rules indicating whether or not a mobile body can move to an area having an attribute value corresponding to the attribute value of each attribute in each area for each task that can be assigned to the mobile body; an attribute value storage means for storing attribute values ​​of each attribute in a predetermined area; an acquisition means for acquiring tasks assigned to the mobile body in the predetermined area; a generation means for generating map information indicating whether or not the mobile body can move to the predetermined area based on the rule corresponding to the acquired task and the attribute values ​​of each attribute in the predetermined area; and a transmission means for transmitting the generated map information to the mobile body.

[0007] A method according to one aspect of the present disclosure acquires tasks assigned to a mobile body in a predetermined area, and refers to a rule storage means that stores rules indicating whether or not the mobile body can move to an area with the attribute value for each attribute of each area, for each task that can be assigned to the mobile body, and an attribute value storage means that stores the attribute values ​​of each attribute of the predetermined area, to generate map information indicating whether or not the mobile body can move to the predetermined area based on the rule corresponding to the acquired task and the attribute value of each attribute of the predetermined area, and transmits the generated map information to the mobile body.

[0008] In one aspect of the present disclosure, a program causes a computer to perform the following processes: a process of acquiring tasks assigned to a mobile body in a specified area; a process of generating map information indicating whether the mobile body can move to the specified area based on the rule corresponding to the acquired task and the attribute value of each attribute of the specified area, by referring to a rule storage means that stores rules indicating whether the mobile body can move to the area for each attribute value for each task that can be assigned to the mobile body, and an attribute value storage means that stores the attribute values ​​of each attribute of the specified area; and a process of transmitting the generated map information to the mobile body. [Effects of the Invention]

[0009] According to the present disclosure, map information can be provided that enables a mobile body to travel along an appropriate route for performing work. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram showing a configuration example of a system according to a first embodiment; [Figure 2] 4 is a flowchart illustrating an example of an operation of the system according to the first embodiment. [Figure 3] FIG. 10 is an explanatory diagram illustrating an example of a system according to a second embodiment. [Figure 4] FIG. 10 is an explanatory diagram simply illustrating an example of the operation of the system according to the second embodiment. [Figure 5] FIG. 2 is an explanatory diagram showing an example of a trajectory of movement of a robot and positions from which data was acquired. [Figure 6] FIG. 10 is a block diagram showing a configuration example of an information processing device according to a second embodiment. [Figure 7] FIG. 10 is an explanatory diagram showing an example of rules for each task. [Figure 8] FIG. 10 is a block diagram showing a configuration example of a robot according to a second embodiment. [Figure 9] FIG. 10 is an explanatory diagram showing an example of generating map information when the robot 21 is shopping for fresh food. [Figure 10] FIG. 10 is an explanatory diagram showing an example of generating map information when a robot is shopping for fragile items. [Figure 11] FIG. 10 is an explanatory diagram showing an example of generating map information when a robot guides an elderly person carrying a cane. [Figure 12] FIG. 10 is an explanatory diagram showing an example of generating map information when a robot guides a child; [Figure 13] FIG. 10 is an explanatory diagram showing an example of the difference between already-transmitted map information and newly generated map information; [Figure 14] 10 is a flowchart showing an example of an operation of acquiring data by the information processing device according to the second embodiment. [Figure 15] 10 is a flowchart showing an example of an operation of transmitting map information by the information processing device according to the second embodiment. [Figure 16] FIG. 11 is a block diagram showing a configuration example of an information processing device according to a third embodiment. [Figure 17] FIG. 10 is an explanatory diagram showing an example of the priority of rules in each area of ​​a data center. [Figure 18] FIG. 10 is an explanatory diagram showing an example of rules for a security policy and rules for a privacy policy. [Figure 19] FIG. 10 is an explanatory diagram showing an example of rules according to whether or not important people are hospitalized in a hospital. [Figure 20] FIG. 10 is an explanatory diagram showing an example in which rules are different for an area in which an important person is hospitalized. [Figure 21] FIG. 10 is an explanatory diagram showing an example in which rules for each line in a factory are used. [Figure 22] 11 is a flowchart illustrating an example of an operation of the information processing device according to the third embodiment. [Figure 23] FIG. 2 is an explanatory diagram illustrating an example of a hardware configuration of a computer device. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, with reference to the drawings, embodiments of a system, an information processing device, a method, a program, and a recording medium for recording the program according to the present disclosure will be described in detail. However, the drawings only show a schematic configuration of the embodiment of the present disclosure. Furthermore, the embodiment of the present disclosure described below is merely an example, and can be modified as appropriate within the scope of the same essence.

[0012] Here, we will provide a brief explanation of digital twins. Digital twins are a technology that collects information from the real world and recreates that real world in a virtual space based on the collected information. More specifically, digital twins are a solution that collects information obtained in real time and uses technologies such as AI (artificial intelligence) to recreate and simulate situations that could actually occur in a virtual space on a computer, etc., in order to predict what will happen in the real world. Time-series information is obtained from sensors installed in various locations and mobile devices equipped with sensors. When simulating in virtual space, a dynamic map is created by overlaying the acquired time-series information and future prediction information on map information, and the actual situation is reproduced as a twin in the virtual space. In order to represent real-world events (World) on a dynamic map, the data used in the simulation is accumulated in layers categorized by purpose.

[0013] In the system described in this embodiment, for example, data including attribute values ​​of each attribute associated with a position at each position of a device that emits information in real space is acquired. The system may manage multiple attribute values ​​of the same attribute at different positions as a layer. In other words, a layer is a group of information consisting of multiple attribute values ​​of a certain attribute.

[0014] (Embodiment 1) FIG. 1 is a block diagram showing an example of the configuration of a system according to a first embodiment. The system 1 provides a mobile object with map information indicating whether the mobile object can move into a predetermined area. The predetermined area is not particularly limited. The predetermined area may be indoors or outdoors. The type of the mobile object is not particularly limited. The system 1 includes an acquisition unit 101, a generation unit 102, a transmission unit 103, a rule storage unit 104, and an attribute value storage unit 105.

[0015] The rule storage unit 104 stores, for each task that can be assigned to a mobile object, rules indicating whether or not a mobile object can move to a specific attribute value area (a specific attribute value area within a layer) for each attribute value of each area. An attribute value area is an area to which an attribute value is assigned or managed. Tasks can be assigned to a mobile object. The tasks are not particularly limited. Examples of tasks include guidance, inspection, cleaning, and disinfection. Guidance tasks may be further subdivided, such as guiding elderly people and children. Cleaning tasks may be further subdivided, such as cleaning carpets, cleaning flooring, and cleaning with chemicals. As described above, attributes are not particularly limited to temperature, humidity, congestion level, volume, and the like. Attributes may also include high temperature, high congestion, and the like. Attributes may also include whether or not there are pregnant women, children, wheelchair users, or VIPs. The attribute value storage unit 105 stores attribute values ​​for each attribute in a predetermined area. The attribute values ​​may be specific numerical values ​​such as temperature, humidity, volume, and the like. In the case of temperature, the attribute value is a numerical value such as 25°C. The attribute value may also be expressed as a binary value. More specifically, for example, if the attribute is the presence or absence of a pregnant woman, an attribute value of 1 may indicate that a pregnant woman is present, and an attribute value of 0 may indicate that a pregnant woman is not present.

[0016] The acquisition unit 101 acquires tasks assigned to mobile objects in a predetermined area. Specifically, the acquisition unit 101 may acquire task information that can identify the task, such as the task name and task number. The acquisition unit 101 may also acquire detailed task information. For example, if the task is guidance, the acquisition unit 101 may acquire information such as a specific guidance target. More specifically, the acquisition unit 101 may acquire tasks by, for example, receiving a task notification from the mobile object. The acquisition unit 101 may also acquire tasks for the mobile object by receiving a notification from another device that manages the mobile object. The acquisition unit 101 may also acquire tasks for each mobile object stored in, for example, a storage unit (not shown).

[0017] The generation unit 102 generates map information indicating whether a mobile object can move into a predetermined area based on the acquired rule corresponding to the task and the attribute values ​​for each attribute in the predetermined area. Specifically, the generation unit 102 references the rule storage unit 104 to read the acquired rule corresponding to the task. The generation unit 102 also references the attribute value storage unit 105 to read the attribute values ​​for each attribute in the predetermined area. The generation unit 102 then generates map information based on the rule corresponding to the task and the read attribute values ​​for each attribute. Specifically, if the attribute values ​​for each attribute of the predetermined area read from the attribute value storage unit 105 include an attribute value for which movement is prohibited in the rule corresponding to the task, the generation unit 102 generates map information that prohibits movement into the predetermined area. An example will be described below in which the rule prohibits movement into areas where the temperature is 20°C or higher. If the temperature in the predetermined area is 25°C, the generation unit 102 generates map information that prohibits movement into the predetermined area. On the other hand, if the temperature in the predetermined area is 15° C., the generating unit 102 generates map information that allows travel to the predetermined area.

[0018] The transmitting unit 103 transmits the generated map information to the mobile body. The mobile body receives the map information. Then, the mobile body determines whether or not to move to a predetermined area based on the map information. For example, the mobile body may generate a route to a destination based on the map information.

[0019] 2 is a flowchart showing an example of an operation of the system 1 according to the first embodiment. The acquisition unit 101 acquires a task assigned to a mobile object (step S101). In step S101, for example, the acquisition unit 101 may acquire the task by receiving a notification of the task from the mobile object. The generation unit 102 generates map information indicating whether the mobile object can move to a predetermined area based on a rule corresponding to the acquired task and attribute values ​​for each attribute in the predetermined area (step S102). The system 1 ends the operation of the flow.

[0020] Next, the effects of the first embodiment will be described. The system 1 generates map information indicating whether or not a mobile object can move to a predetermined area based on the rules corresponding to the acquired work and the attribute values ​​for each attribute in the predetermined area. As a result, the system 1 can provide map information that enables a mobile object to move along an appropriate route according to the work when performing the work. For example, The first embodiment is not limited to the above-described examples and may be modified in various ways. For example, each functional unit shown in FIG. 1 may be realized by one device (information processing device). Also, for example, each functional unit shown in FIG. 1 may be realized by two or more devices. For example, one information processing device may have an acquisition unit 101, a generation unit 102, and a transmission unit 103. Then, a storage device connected to one information processing device via a communication network may have a rule storage unit 104 and an attribute value storage unit 105.

[0021] (Embodiment 2) Next, a second embodiment will be described in detail with reference to the drawings. Below, the description of the second embodiment will be omitted for the content that overlaps with the above description, so long as the description of the second embodiment is not unclear. In the second embodiment, a robot will be used as an example of a moving object.

[0022] 3 is an explanatory diagram showing an example of a system according to the second embodiment. The system 2 includes an information processing device 20, one or more robots 21, and a robot management device 22. The information processing device 20, the robot 21, and the robot management device 22 are connected via a communication network 23.

[0023] The information processing device 20 provides the robot 21 with map information indicating whether or not the moving object can move into a predetermined area. The robot 21 moves autonomously based on the map information. Although there is one robot 21 in FIG. 3, the system 2 may have multiple robots 21.

[0024] The robot management device 22 also manages the work of each robot 21. For example, the robot management device 22 may assign work to the robot 21.

[0025] Furthermore, the information processing device 20 may simulate future predictions based on each piece of collected data in the digital twin. Alternatively, the system 2 may include a simulation device (not shown), and the information processing device 20 may acquire simulation results from the simulation device.

[0026] The robot management device 22 and the information processing device 20 may be the same device. Also, the robot management device 22 and a simulation device (not shown) may be the same device.

[0027] 4 is a diagram illustrating a simplified example of an operation of the system 2 according to the second embodiment. The information processing device 20 collects data in a predetermined area L, for example. The information processing device 20 can acquire data including attribute values ​​of various attributes such as temperature, humidity, and images.

[0028] The information processing device 20 may analyze each collected data. For example, when acquiring a temperature, the information processing device 20 may analyze which location in a predetermined area L has a high temperature. Furthermore, for example, the information processing device 20 may detect a person from an image. Then, the information processing device 20 can identify, within the predetermined area L, locations where a person in a wheelchair is present, or locations where a pregnant woman or infant is present. For example, the information processing device 20 updates map information used by the robot 21 for movement so that the robot 21 can safely perform the task assigned to it. For example, when the robot 21 is carrying a large amount of luggage, it is dangerous for the robot 21 to pass near a person in a wheelchair. Therefore, the information processing device 20 generates map information that prohibits movement to locations where a person in a wheelchair is present and the vicinity of those locations. Then, the information processing device 20 transmits the map information to the robot 21.

[0029] FIG. 5 is an explanatory diagram showing an example of the trajectory of robot movement and positions where data was acquired. This diagram shows an example of robots 21-1 to 21-4 moving within area L. Each of the robots 21-1 to 21-4 moves autonomously within area L, for example. The robots 21-1 to 21-4 may be service robots assigned different tasks, or may be service robots assigned the same task. Each robot 21 collects data at each location using various sensors and imaging devices. For example, each robot 21 acquires data including multiple types of attribute values ​​at each location. Here, the data is associated with the location. In FIG. 5, location P1 has coordinates (x1, y1) when area L is represented by x-axis and y-axis coordinates. Time T1 is 11:20. The data associated with location P1 and time T1 includes a temperature value and a humidity value. In FIG. 5, the temperature value is 25° C. and the humidity value is 40%. Note that the data may be associated with a time if the location is the same.

[0030] 6 is a block diagram showing an example of a configuration of an information processing device 20 according to the second embodiment. The information processing device 20 includes a task acquisition unit 201, a generation unit 202, a transmission unit 203, a data acquisition unit 206, an identification unit 207, and a storage unit 208. The identification unit 207 and the storage unit 208 are functional units added from the first embodiment. The task acquisition unit 201, the generation unit 202, the transmission unit 203, and the data acquisition unit 206 each have, as basic components, the functions of the acquisition unit 101, the generation unit 102, and the transmission unit 103 described in the first embodiment, respectively.

[0031] The storage unit 208 stores, for example, the processing results of each unit of the information processing device 20. Examples of the storage unit 208 include a read-only memory (ROM), a random access memory (RAM), a semiconductor memory, a hard disk drive (HDD), and a solid state drive (SSD). The storage unit 208 may be a combination of these. In FIG. 6, the storage unit 208 has a rule storage unit 204 and an attribute value storage unit 205. The rule storage unit 204 and the attribute value storage unit 205 have, as basic components, the functions of the rule storage unit 104 and the attribute value storage unit 105, respectively, described in the first embodiment. First, the rule storage unit 204 will be described.

[0032] Fig. 7 is an explanatory diagram showing an example of rules for each task. The rule storage unit 204 stores, for each task (task information), rules indicating whether or not the attribute value of each attribute can be moved to the area of ​​that attribute value. That is, in Fig. 7, for each task, each piece of information in the horizontal direction indicates whether or not the attribute value can be moved to the area of ​​that attribute value.

[0033] 7, the task information stored in the rule storage unit 204 is information that can uniquely identify a task, such as the name of the task assigned to the robot 21 and task identification information. Specific tasks include cleaning, security, guidance, shopping, etc. Tasks may be classified in more detail.

[0034] 7, when the task is shopping, different rules may be set depending on the items purchased during the shopping. For example, different rules may be stored in the rule storage unit 204 for shopping when the items purchased include fresh food and shopping when the items purchased include fragile items.

[0035] As will be described later, when the task is guidance, rules may be set depending on the person to be guided. For example, different rules may be stored in the rule storage unit 204 when the person to be guided is an elderly person using a cane and when the person to be guided is a child.

[0036] Also, in Figure 7, "attribute" is the name of the attribute. Note that the example of Figure 7 is not limited to this, and any attribute may be used as long as it can be uniquely identified. Examples of attributes include "sound (loud)", "temperature (high)", and "wheelchair present". "sound (loud)" indicates that the sound is loud. "temperature (high)" indicates that the temperature is high. "wheelchair present" indicates that there is a person in a wheelchair. "unevenness" indicates that there are unevenness. Note that the attribute may simply be an attribute that represents the environment, such as sound, temperature, or humidity.

[0037] The following describes loud sounds. If loud sounds are permitted to move, the robot 21 can move to areas where the volume is equal to or greater than a predetermined volume. If loud sounds are prohibited to move, the robot 21 cannot move to areas where the volume is equal to or greater than a predetermined volume. For example, if the task is cleaning, loud sounds are permitted to move. Therefore, the robot 21 assigned the cleaning task can move to areas where the volume is equal to or greater than a predetermined volume. For example, if the task is guiding elderly people who use canes, loud sounds are prohibited to move. Therefore, the robot 21 assigned the task of guiding elderly people who use canes cannot move to areas where the volume is equal to or greater than a predetermined volume.

[0038] The temperature (high) will now be described. If the temperature (high) is movable, the robot 21 can move to an area where the temperature is equal to or higher than a predetermined temperature. If the temperature (high) is prohibited from moving, the robot 21 cannot move to an area where the temperature is equal to or higher than a predetermined temperature. In FIG. 7, for example, if the task is cleaning, the temperature (high) is movable. Therefore, the robot 21 assigned to the cleaning task can move to an area where the temperature is equal to or higher than a predetermined temperature. For example, if the task is shopping for fresh food, the temperature (high) is prohibited from moving. Therefore, the robot 21 assigned to the shopping for fresh food task cannot move to an area where the temperature is equal to or higher than a predetermined temperature.

[0039] If "Wheelchair Present" indicates that movement is permitted, the robot 21 can move to an area where a person in a wheelchair is present. If "Wheelchair Present" indicates that movement is prohibited, the robot 21 cannot move to an area where a person in a wheelchair is present. In FIG. 7, for example, a robot 21 assigned to cleaning work cannot move to an area where a person in a wheelchair is present. For example, a robot 21 assigned to security work can move to an area where a person in a wheelchair is present. Note that, since there may be cases where a person in a wheelchair moves, the rules may define whether or not the robot can move to an area where a person in a wheelchair is present and an area nearby that area.

[0040] If the unevenness allows movement, the robot 21 can move into the area with the unevenness. On the other hand, if the unevenness prohibits movement, the robot 21 cannot move into the area with the unevenness. A robot 21 assigned to cleaning work can move into an area with the unevenness. A robot 21 assigned to guiding an elderly person who uses a cane cannot move into an area with the unevenness.

[0041] In this way, the rules define whether or not movement to the area of ​​each attribute value is possible depending on various attributes. Note that the operations and attributes shown in FIG.

[0042] Returning to the description of FIG. 6 , the attribute value storage unit 205 will be described. The attribute value storage unit 205 stores an attribute value of each attribute for each of a plurality of small regions included in a predetermined region. For example, the attribute value is sensor information or image data acquired within the small region. Examples of sensor information include temperature data and humidity data. For example, when multiple pieces of sensor information for the same attribute are acquired within a small region, a statistical value such as an average value, a median value, or a mode value may be used as the attribute value. Furthermore, when sensor information is not acquired in a small region, the attribute value may be interpolated using sensor information from other small regions. Furthermore, the attribute value storage unit 205 may manage the attribute values ​​of each attribute in chronological order.

[0043] Furthermore, the small regions are not particularly limited. The sizes of the small regions may be the same or different. For example, each of the regions obtained by dividing a predetermined area into a mesh pattern at equal intervals may be defined as a small region. Furthermore, for example, if the first floor of a building is a predetermined region, each conference room may be defined as a small region. Furthermore, the small regions may be grouped.

[0044] 8 is a block diagram showing an example of a configuration of the robot 21 according to the second embodiment. The robot 21 includes a work management unit 211, a map acquisition unit 212, a movement control unit 213, and a storage unit 208. The storage unit 208 stores, for example, the processing results of each unit of the information processing device 20. Examples of the storage unit 208 include ROM, RAM, semiconductor memory, HDD, and SSD. The storage unit 208 may also be a combination of these.

[0045] Next, each functional unit in FIGS. 6 and 8 will be described. The data acquisition unit 206 acquires data from each robot 21 moving within a predetermined area and from sensors installed within the predetermined area. The data includes location information. The data includes attribute values ​​of each attribute. The attribute values ​​are values ​​detected by the robot 21 or sensors at each location. The method by which the robot 21 acquires its location is not particularly limited. For example, markers may be attached to the ground or floor in advance, and the location may be stored for each marker. The robot 21 may acquire location information as data from markers shown in an image. Furthermore, when outdoors, the robot 21 may acquire location information using, for example, a global positioning system (GPS). Furthermore, the robot 21 may determine its location using a device such as a beacon. Furthermore, the robot 21 may determine its location using a sensor such as a light detection and ranging (Lidar). The data acquisition unit 206 stores each acquired data in the attribute value storage unit 205.

[0046] The task acquisition unit 201 acquires the task assigned to the robot 21. The task acquisition unit 201 may acquire the task assigned to the robot 21 from the robot 21. The task acquisition unit 201 may acquire the task assigned to the robot 21 from the robot management device 22.

[0047] Next, the generation unit 202 generates map information indicating whether the robot 21 can move to each of the multiple small areas based on the acquired rules for the task and the attribute values ​​for each attribute in the multiple small areas. The generation unit 202 generates map information that prohibits movement to small areas having attribute values ​​corresponding to attributes for which movement is prohibited in the rules for the task. The generation unit 202 generates map information indicating that movement is permitted to small areas that do not have attribute values ​​corresponding to attributes for which movement is prohibited in the rules for the task. An example will be described in which the rules prohibit movement to high temperature areas and high humidity areas. The generation unit 202 generates map information indicating that movement to small areas that are either high temperature or high humidity is prohibited among the multiple small areas, but indicating that movement to small areas that are neither high temperature nor high humidity is not prohibited.

[0048] Furthermore, the generation unit 202 may generate map information indicating whether the robot 21 can move to a small area in the traveling direction of the robot 21 among the plurality of small areas. This eliminates the need to send information that the robot 21 does not use, thereby reducing the amount of data required for transmission. Furthermore, the robot 21 does not need to receive unnecessary map information. Therefore, the robot 21 does not need to store unnecessary map information. The traveling direction may be acquired from the robot management device 22 or the robot 21. For example, the task acquisition unit 201 may acquire the traveling direction along with the task. For example, the generation unit 202 may identify the traveling direction of the robot 21 from task information.

[0049] FIG. 9 is an explanatory diagram showing an example of map information generated when the robot 21 is shopping for fresh food. In FIG. 9, the task assigned to the robot 21 is shopping for fresh food. Here, for simplicity of explanation, only the temperature (high) in the rules shown in FIG. 7 will be used for explanation. Note that in the rules shown in FIG. 7, when the task is shopping for fresh food, movement of the temperature (high) is prohibited. The robot 21 shown in FIG. 9 cannot move to a small area of ​​the area L where the temperature is equal to or higher than a predetermined temperature.

[0050] 9, the work management unit 211 of the robot 21 transmits the assigned work to the information processing device 20. The work acquisition unit 201 of the information processing device 20 acquires the work assigned to the robot 21 from the robot 21.

[0051] 9 shows high-temperature areas and low-temperature areas in area L. The generation unit 202 generates map information that indicates that movement to small areas with high temperatures is prohibited within area L, and that movement to small areas with low temperatures is permitted. The transmission unit 203 then transmits the map information to the robot 21.

[0052] The map acquisition unit 212 of the robot 21 acquires map information from the information processing device 20. The map acquisition unit 212 may store the map information in the storage unit 208. Then, the movement control unit 213 controls movement in the predetermined area L based on the map information. As a result, the robot 21 moves without passing through areas with high temperatures. Note that the movement control unit 213 may, for example, generate a route that passes through areas of the predetermined area L other than the small areas where movement is prohibited in the map information. Then, the movement control unit 213 may control the operation and movement of the robot 21 so that the robot 21 follows the generated route. As a result, the robot 21 can move without passing through areas with high temperatures when shopping for fresh food. Therefore, the robot 21 can perform work while preventing the fresh food from spoiling.

[0053] Fig. 10 is an explanatory diagram showing an example of generating map information when the robot 21 is shopping for fragile items. In Fig. 10, the task assigned to the robot 21 is shopping for fragile items. For simplicity of explanation, the following description will be given using the congestion level (not shown) as an attribute.

[0054] For example, the rule may define that if the task is shopping for fragile items, movement to a highly congested area is prohibited.

[0055] 10, the work management unit 211 of the robot 21 transmits the assigned work to the information processing device 20. The work acquisition unit 201 of the information processing device 20 acquires the work assigned to the robot 21 from the robot 21.

[0056] 10 shows areas with high congestion levels and areas with low congestion levels in area L. The generation unit 202 generates map information that indicates that movement to small areas with high congestion levels is prohibited within area L and that movement to small areas with low congestion levels is permitted. The transmission unit 203 then transmits the map information to the robot 21.

[0057] The map acquisition unit 212 of the robot 21 acquires map information from the information processing device 20. The map acquisition unit 212 may store the acquired map information in the storage unit 208. Then, the movement control unit 213 controls movement in a predetermined area L based on the map information. This allows the robot 21 to move without passing through highly congested areas when shopping for fragile items. Therefore, the robot 21 can perform its work more safely.

[0058] Fig. 11 is an explanatory diagram showing an example of map information generation when the robot 21 guides an elderly person carrying a cane. In Fig. 11, the task assigned to the robot 21 is to guide the elderly person carrying a cane. Here, for the sake of simplicity, the description will be given using unevenness as an attribute.

[0059] For example, the rule defines that when the task is to guide an elderly person with a cane, movement into an uneven area is prohibited.

[0060] 11, the work management unit 211 of the robot 21 transmits the assigned work to the information processing device 20. The work acquisition unit 201 of the information processing device 20 acquires the work assigned to the robot 21 from the robot 21.

[0061] 11 shows areas with unevenness and areas without unevenness in area L. The generation unit 202 generates map information that indicates that movement to small areas with unevenness within area L is prohibited and that movement to small areas without unevenness is permitted. Then, the transmission unit 203 transmits the map information to the robot 21.

[0062] The map acquisition unit 212 of the robot 21 acquires map information from the information processing device 20. The map acquisition unit 212 may store the acquired map information in the storage unit 208. Then, the movement control unit 213 controls movement in a predetermined area based on the map information. This allows the robot 21 to guide an elderly person carrying a cane along a flat road without bumps or unevenness. In this way, the robot 21 can perform its work more safely.

[0063] Fig. 12 is an explanatory diagram showing an example of map information generated when the robot 21 guides a child. In Fig. 12, the task assigned to the robot 21 is to guide a child who is interested in a toy. Here, for the sake of simplicity, the explanation will be given using concaves and convexes.

[0064] Here, for example, the rule defines that when the task is to guide a child, the robot 21 is prohibited from moving to an area that the child is interested in. Information such as the child's interests may be provided in advance by, for example, the child's parent.

[0065] 12, the work management unit 211 of the robot 21 transmits the assigned work to the information processing device 20. At this time, the work management unit 211 may notify detailed information about the target of guidance, such as information about the child's interests. The work acquisition unit 201 of the information processing device 20 acquires the work assigned to the robot 21 from the robot 21.

[0066] 12 shows the toy section and other areas in area L. The generation unit 202 generates map information that indicates that movement to small areas within area L that are included in the toy section or that are close to the toy section is prohibited, and that movement to other small areas is permitted. The transmission unit 203 then transmits the map information to the robot 21.

[0067] The map acquisition unit 212 of the robot 21 acquires map information from the information processing device 20. The map acquisition unit 212 may store the acquired map information in the storage unit 208. Then, the movement control unit 213 controls movement in a predetermined area based on the map information. This allows the robot 21 to guide the child away from the toy section.

[0068] <Differences in map information> Next, a case where map information has already been transmitted will be described. When the robot 21 receives map information multiple times, it requires a large memory capacity to store each piece of map information. Therefore, the identification unit 207 identifies the difference between the map information that has already been transmitted to the robot 21 and the newly generated map information. Then, the transmission unit 203 transmits the difference to the robot 21. Here, the identification unit 207 may identify the difference between the map information that has already been transmitted to the robot 21 and the generated map information, regarding a small area in the traveling direction of the robot 21.

[0069] Specifically, for example, the identification unit 207 may identify a small area to which movement is prohibited in the generated map information from among small areas to which movement is not prohibited in the already transmitted map information. Then, the transmission unit 203 transmits information indicating that movement to the identified small area is prohibited. This allows the transmission unit 203 to transmit information about the new area to which movement is prohibited.

[0070] Alternatively, for example, the identification unit 207 may identify a small area to which movement is not prohibited in the generated map information from among the small areas to which movement is prohibited in the already transmitted map information. Then, the transmission unit 203 transmits information indicating that the robot 21 is not prohibited from moving to the identified area. This allows the transmission unit 203 to transmit information about the area to which movement is now permitted.

[0071] Fig. 13 is an explanatory diagram showing an example of the difference between the transmitted map information and the newly generated map information. In Fig. 13, in area L, the white parts are movable. In Fig. 13, the dark parts (non-white parts) are prohibited from movement.

[0072] 13, the identification unit 207 identifies a partial area PL1 including a plurality of small areas and a partial area PL2 including a plurality of small areas from the area L. The transmission unit 203 transmits information indicating that the partial area PL1 and the partial area PL2 have become prohibited from movement from the already-sent map information.

[0073] Then, based on this information, the robot 21 may update the map information stored in the storage unit 208. For example, the robot 21 changes the information on the partial area PL1 and the partial area PL2 in the map information.

[0074] 14 is a flowchart showing an example of an operation of acquiring data by the information processing device 20 according to the second embodiment. The information processing device 20 acquires data (step S201). As described above, the data includes location information and attribute values ​​of each attribute. In step S201, the information processing device 20 may acquire the data from a device such as a sensor installed in a predetermined area. Alternatively, in step S201, the information processing device 20 may acquire the data from a device such as a sensor included in each robot 21 moving in the predetermined area. Next, the information processing device 20 stores the data in the attribute value storage unit 205 (step S202).

[0075] 15 is a flowchart showing an example of an operation of transmitting map information by the information processing device 20 according to the second embodiment. The task acquisition unit 201 acquires a task assigned to the robot 21 (step S211). Specifically, the task acquisition unit 201 acquires information that can uniquely identify the task, such as the task name of the task assigned to the robot 21 and task identification information.

[0076] The generating unit 202 generates map information based on the rules according to the task and the attribute values ​​of the attributes for each of the plurality of small areas (step S212).

[0077] The identification unit 207 identifies a difference between the map information that has been sent to the robot 21 and the generated map information (step S213). In step S213, the identification unit 207 may identify a difference between the map information that has been sent and the generated map information regarding a small area in the traveling direction of the robot 21.

[0078] Furthermore, in step S213, the identification unit 207 may identify a small area to which movement is prohibited in the generated map information from among small areas to which movement is not prohibited in the transmitted map information. Alternatively, in step S213, the identification unit 207 may identify a small area to which movement is not prohibited in the generated map information from among small areas to which movement is prohibited in the transmitted map information.

[0079] The transmitting unit 203 transmits the identified difference (step S214), and the information processing device 20 ends the operation of the flow.

[0080] Next, the effects of the second embodiment will be described. The attribute value storage unit 205 is included in a predetermined area. It stores attribute values ​​for each attribute in each of a plurality of small areas. The information processing device 20 generates map information indicating whether a mobile object can move to each of the plurality of small areas based on the rules corresponding to the acquired work and the attribute values ​​for each attribute in the plurality of small areas. This allows the information processing device 20 to provide, for example, map information indicating in detail whether movement is possible in a predetermined area.

[0081] Furthermore, the information processing device 20 may generate map information indicating whether the mobile object can move to a small area in the moving direction of the mobile object among a plurality of small areas. This eliminates the need for the information processing device 20 to generate map information for areas not used by the mobile object, thereby reducing the amount of processing. Furthermore, the robot 21 does not need to receive unnecessary map information.

[0082] Furthermore, the information processing device 20 identifies the difference between the map information that has already been transmitted to the mobile object and the generated map information. Then, the information processing device 20 transmits the difference to the robot 21. This allows the robot 21 to obtain the latest map information by using the existing map information and the difference. Therefore, the robot 21 does not need to receive unnecessary map information.

[0083] Furthermore, the information processing device 20 identifies small areas to which movement is prohibited in the generated map information from among small areas to which movement is not prohibited in the transmitted map information. The information processing device 20 transmits information indicating that movement to the identified areas is prohibited. This allows the robot 21 to obtain information on new areas to which movement is prohibited.

[0084] Furthermore, the information processing device 20 identifies small areas to which movement is not prohibited in the generated map information from among the small areas to which movement is prohibited in the transmitted map information. Then, the information processing device 20 transmits information indicating that movement to the identified areas is not prohibited. This allows the robot 21 to obtain information about areas to which movement is now permitted.

[0085] Furthermore, the information processing device 20 identifies a difference between the map information already transmitted to the robot 21 and the generated map information regarding a small area in the traveling direction of the moving object. This prevents the robot 21 from receiving unnecessary map information.

[0086] The second embodiment is not limited to the above-described example and may be modified in various ways. For example, each functional unit of the information processing device 20 may be realized by a plurality of devices. For example, the rule storage unit 204 and the attribute value storage unit 205 may be realized by a storage device connected to the information processing device 20 via the communication network 23.

[0087] (Embodiment 3) Next, a third embodiment will be described in detail with reference to the drawings. Below, the description of the third embodiment will be omitted for the content that overlaps with the above description, so long as the description of the third embodiment is not unclear. In the third embodiment, an example will be described in which, using the functions described in the second embodiment as basic functions, when a plurality of rules are stored for each task, one of the plurality of rules is selected to generate map information.

[0088] Furthermore, the system according to the third embodiment includes, as a basic configuration, each component of the system 2 described in the second embodiment. For example, the system according to the third embodiment includes an information processing device, a robot, and a robot management device, similar to the system 2 described in the second embodiment. The functional units of the robot do not need to be changed from the functional units described in the second embodiment, and therefore detailed description thereof will be omitted.

[0089] FIG. 16 is a block diagram showing an example of a configuration of an information processing device according to the third embodiment. The information processing device 30 includes a task acquisition unit 301, a generation unit 302, a transmission unit 303, a data acquisition unit 306, an identification unit 307, a storage unit 308, and a selection unit 309. In the third embodiment, the selection unit 309 is added to the functional units described in the second embodiment. The task acquisition unit 301 may have, as a basic configuration, the functions of the acquisition unit 101 or the task acquisition unit 201 described in the first embodiment. The generation unit 302 and the transmission unit 303 may have, as a basic configuration, the functions of the generation units 102 and 202 and the transmission units 103 and 203 described in the first and second embodiments, respectively. The data acquisition unit 306, the identification unit 307, and the storage unit 308 may have, as a basic configuration, the functions of the data acquisition unit 206, the identification unit 207, and the storage unit 208 described in the second embodiment, respectively.

[0090] Furthermore, the attribute value storage unit 305 may have the attribute value storage unit 205 described in the second embodiment as a basic function.

[0091] The rule storage unit 304 may store, for each task, a plurality of rules indicating whether or not an attribute value of an attribute can be moved to a region of the attribute value. For example, the rule storage unit 304 may store a rule for each task for each policy. Also, for example, the rule storage unit 304 may store a rule for each task for each line in a manufacturing plant. Also, for example, the rule storage unit 304 may store a rule for each task for each attribute value of a predetermined attribute.

[0092] <Policy-based rules> First, a detailed description will be given of each policy in the case where rules are stored in the rule storage unit 304 for each task. A policy is a guideline for the movement of a robot in each area. For example, a policy is a guideline for observing safety, security, privacy, etc. For example, a policy is set for each area. Alternatively, a policy priority may be set for each area.

[0093] Specifically, the rule storage unit 304 stores, for each task, a plurality of rules for the safety policy that indicate whether or not an attribute value of an attribute can be moved to an area. The rule storage unit 304 stores, for each task, a plurality of rules for the security policy that indicate whether or not an attribute value of an attribute can be moved to an area. The rule storage unit 304 stores, for each task, a plurality of rules for the privacy policy that indicate whether or not an attribute value of an attribute can be moved to an area.

[0094] Then, the selection unit 309 selects a rule from the rule storage unit 304 based on the policy set for the predetermined area. The generation unit 302 generates map information indicating whether or not a mobile object can move into the predetermined area based on the selected rule and attribute values ​​for each attribute in the predetermined area. Specific examples of map information generated by the generation unit 302 are as described in the first and second embodiments.

[0095] 17 is an explanatory diagram showing an example of the priority of rules in each area of ​​a data center. In FIG. 17, the data center has a shared floor, a floor for client Y, and a floor for client Z.

[0096] For example, on the shared floor, the floor of client Y, the safety policy takes the highest priority. Also, on the floor of client Y, the privacy policy takes the highest priority.

[0097] Here, an example will be described in which the robot 31 cleans all of the shared floor, the floor of client Y, and the floor of client Z. For example, in the case of the shared floor, the selection unit 309 selects a rule corresponding to the safety policy and cleaning task from the rule storage unit 304. The generation unit 302 generates map information indicating whether a mobile object can move to each small area on the shared floor, based on the selected rule and the attribute values ​​of each attribute of multiple small areas included in the shared floor.

[0098] Also, for example, in the case of the floor of client Y, the selection unit 309 selects a rule corresponding to the safety policy and cleaning work from the rule storage unit 304. The generation unit 302 generates map information indicating whether a mobile object can move to each small area on the floor of client Y, based on the selected rule and the attribute values ​​of each attribute of the multiple small areas included in the floor of client Y.

[0099] Also, for example, in the case of the floor of client Z, the selection unit 309 selects a rule corresponding to the privacy policy and cleaning work from the rule storage unit 304. The generation unit 302 generates map information indicating whether a mobile object can move to each small area on the floor of client Z, based on the selected rule and the attribute values ​​of each attribute of the multiple small areas included in the floor of client Z.

[0100] In this way, the information processing device 30 can generate map information based on the policy set for the area and the rules according to the work of the robot 31.

[0101] 18 is an explanatory diagram showing an example of rules for a security policy and rules for a privacy policy. Here, it is assumed that a policy is set for each factory. For example, a security policy is set for a factory that manufactures precision equipment. For example, a privacy policy is set for a factory that manufactures national defense equipment.

[0102] In FIG. 18 , there are differences between the rules for the security policy and the rules for the privacy policy, for example, when the robot 31 is providing a tour of a factory. For example, in the case of a tour of a factory, the rules for the security policy allow the robot 31 to move to areas with loud noises and areas with high temperatures, but prohibit movement to areas where line workers are present. For example, the rules for the privacy policy prohibit movement to areas with loud noises, areas with high temperatures, and areas where line workers are present. In this way, the areas that the robot 31 can move to differ depending on the rules for each policy.

[0103] <Rules according to the attribute value of a given attribute> Next, a detailed description will be given of a case where rules are stored in the rule storage unit 304 for each task with respect to each attribute value of a predetermined attribute.

[0104] The rule storage unit 304 stores rules for each attribute value of a predetermined attribute, for each task, that indicate whether or not the attribute value of each attribute can be moved to the area of ​​the attribute value. The predetermined attribute is not particularly limited. For example, the predetermined attribute may be low temperature, presence or absence of construction work, etc.

[0105] The selection unit 309 selects a rule from the rule storage unit 304 based on the attribute value of a predetermined attribute stored in the attribute value storage unit 305 .

[0106] The generation unit 302 generates map information indicating whether the robot 31 can move into a predetermined area, based on the selected rule and the attribute values ​​for each attribute in the predetermined area.

[0107] Here, an example will be described in which the predetermined attribute is the presence or absence of a VIP. Rules for each task when a VIP is present in the predetermined area and rules for each task when a VIP is not present in the predetermined area may be stored in the rule storage unit 304.

[0108] FIG. 19 is an explanatory diagram showing example rules for when a VIP is hospitalized in a hospital and when not. In FIG. 19, there are rules for when a VIP is not hospitalized (normal rules) and rules for when a VIP is hospitalized (rules when a VIP is hospitalized). For example, when the task is to guide visitors, the two rules differ in whether or not it is possible to move to an area where a patient is present. For example, under the normal rules, it is possible to move to an area where a patient is present. On the other hand, under the rules when a VIP is hospitalized, it is prohibited to move to an area where a patient is present.

[0109] Furthermore, the rules according to the attribute values ​​of the predetermined attributes may be combined with rules for each policy. For example, the policy set for an area may be switched based on the attribute values ​​of the predetermined attributes. Then, the selection unit 309 may select a rule according to the policy and work set for the area.

[0110] 20 is an explanatory diagram showing an example in which rules are different for areas where important people are hospitalized. In FIG. 20, the hospital has a common area, ward X, and an isolation ward. Safety policies are originally set for the common area, ward X, and isolation ward.

[0111] For example, consider an attribute indicating whether or not a VIP is hospitalized. Here, a VIP is hospitalized in ward X. The attribute value of the attribute may be manually input. For example, when a VIP is hospitalized, the attribute value of an attribute indicating whether or not a VIP is hospitalized in a small area including a hospital room in ward X may be manually set to "Hospitalized."

[0112] In a small area including a hospital room in ward X, the attribute value of an attribute indicating whether or not a VIP is hospitalized is "Hospitalized." The selection unit 309 selects, for ward X, a privacy policy and rules according to the work when the attribute value is "Hospitalized." The generation unit 302 then generates map information based on the privacy policy, the rules according to the work of the robot 31, and the attribute values ​​of the attributes of each of the multiple small areas included in ward X. This makes it possible to prevent the robot 31 from moving to a hospital room where a VIP is hospitalized or to an area near that room in ward X.

[0113] The above-described examples are not limiting. For example, a detection unit (not shown) may detect that the attribute value of a predetermined attribute has reached a predetermined attribute value. Then, a request unit (not shown) may request each of the multiple robots 31 to notify the robots 31 of the assigned tasks when it detects that the attribute value of the predetermined attribute has reached the predetermined attribute value. Each robot 31 then notifies the robots 31 of the tasks. The task acquisition unit 301 acquires the tasks from each robot 31. Then, the selection unit 309 selects a rule corresponding to the predetermined attribute value. The generation unit 302 generates map information based on the selected rule and the attribute value of each attribute. This allows the information processing device 30 to immediately update the map information when the attribute value of a predetermined attribute reaches the predetermined attribute value.

[0114] <Rules according to the line> Furthermore, in a factory, rules according to the production line may be stored in the rule storage unit 304 .

[0115] FIG. 21 is an explanatory diagram showing an example in which rules are used for each line in a factory. For example, the factory has areas L1, L2, and L3. Area L1 has line C. Area L2 has line A. Area L3 has line B. The rule storage unit 304 stores rules for each task for each line. The selection unit 309 selects a rule for each area according to the manufacturing line. Therefore, rule C is applied to area L1. Rule A is applied to area L2. Rule B is applied to area L3. The generation unit 302 then generates map information based on the selected rules.

[0116] Suppose that there is a change in the factory after that. Area L1 has line C. Area L2 has line D. Area L3 has line A. The selection unit 309 selects a rule according to the manufacturing line for each area. Therefore, rule C is applied to area L1. Rule D is applied to area L2. Rule A is applied to area L3. The generation unit 302 then generates map information based on the selected rules.

[0117] This allows the information processing device 30 to generate map information using rules according to the lines in each area.

[0118] 22 is a flowchart showing an example of an operation of the information processing device 30 according to the third embodiment. The acquisition unit acquires a task assigned to the robot 31 (step S301). Next, the selection unit 309 selects a rule from the rule storage unit 304 (step S302). In step S302, the selection unit 309 may select a rule from the rule storage unit 304 based on, for example, a policy set for a predetermined area in which the robot 31 moves. In step S302, the selection unit 309 selects a rule from the rule storage unit 304 based on, for example, an attribute value of a predetermined attribute stored in the attribute value storage unit 305.

[0119] The generating unit 302 generates map information based on the selected rule (step S303). The identifying unit 307 identifies the difference between the map information already sent to the robot 31 and the generated map information (step S304). Then, the transmitting unit 303 transmits the identified difference (step S305). The information processing device 30 ends the operation of the flow.

[0120] Next, the effects of the third embodiment will be described. The rule storage unit 304 stores, for each policy, rules indicating whether or not movement to an area corresponding to the attribute value of each attribute is permitted for each task. The information processing device 30 selects a rule from the rule storage unit 304 based on the policy set for a predetermined area. The generation unit 302 generates map information indicating whether or not the robot 31 is permitted to move to the predetermined area based on the selected rule and the attribute values ​​for each attribute in the predetermined area. This allows the information processing device 30 to select an appropriate rule from the rules corresponding to each policy based on the policy set for each area. The information processing device 30 can provide more appropriate map information. Therefore, the robot 31 can perform a task using more appropriate map information.

[0121] The rule storage unit 304 stores, for each attribute value of a predetermined attribute, a rule indicating whether or not the robot 31 can move to an area corresponding to the attribute value for that attribute value for each task. The information processing device 30 then selects a rule from the rule storage unit 304 based on the attribute value of the predetermined attribute stored in the attribute value storage unit 305. The information processing device 30 generates map information indicating whether or not the robot 31 can move to the predetermined area based on the selected rule and the attribute value for each attribute in the predetermined area. This allows the information processing device 30 to select an appropriate rule from multiple rules based on dynamically changing attribute values. The information processing device 30 can provide more appropriate map information. Therefore, the robot 31 can perform the task using more appropriate map information.

[0122] The third embodiment is not limited to the above-described examples and can be modified in various ways. For example, in the third embodiment, for ease of explanation, each device has the functional units described in the second embodiment, but this is not limiting. For example, the information processing device 30 according to the third embodiment may not have the identifying unit 307. In this way, the system according to the third embodiment may not have some functional units as appropriate.

[0123] This concludes the description of each embodiment.

[0124] (Computer equipment) Next, an example of a hardware configuration when each information processing device and moving body is realized by a computer device will be described. Fig. 23 is an explanatory diagram showing an example of a hardware configuration of a computer device. Some or all of the components of the information processing devices 10, 20, 30 and robots 21, 31 described in the above-mentioned first, second, and third embodiments can also be realized using any combination of a computer device 40 and a program as shown in Fig. 23, for example.

[0125] The computer device 40 includes, for example, a processor 401, a ROM 402, a RAM 403, a storage device 404, a communication interface 405, and an input / output interface 406. Each component is connected to each other via a bus 407.

[0126] The processor 401 controls the entire computer device 40. Examples of the processor 401 include a CPU (Central Processing Unit) and a DSP (Digital Signal Processor). The computer device 40 has a storage unit including a ROM 402, a RAM 403, and a storage device 404. Examples of the storage device 404 include a semiconductor memory such as a flash memory, an HDD, and an SSD. For example, the storage device 404 stores various programs such as an OS (Operating System) program, application programs, and the programs described in each embodiment. Alternatively, the ROM 402 stores various programs such as application programs and the programs described in each embodiment. The RAM 403 is used as a work area for the processor 401.

[0127] The processor 401 also loads programs stored in the storage device 404, ROM 402, etc. The processor 401 then executes each process coded in the program. The processor 401 may also download various programs via the communication network 43. The processor 401 also functions as a part or all of the computer device 40. The processor 401 may then execute the processes or instructions in the illustrated flowchart based on the program.

[0128] The communication interface 405 is connected to a communication network 43 such as a LAN (Local Area Network) or WAN (Wide Area Network) via a wireless or wired communication line. This allows the computer device 40 to be connected to external devices and external computers via the communication network 43. The communication interface 405 serves as an interface between the communication network 43 and the inside of the computer device 40. The communication interface 405 also controls the input and output of data from the external devices and external computers.

[0129] Furthermore, the input / output interface 406 is connected to at least one of an input device, an output device, and an input / output device. The connection method may be wireless or wired. Examples of input devices include a keyboard, a mouse, and a microphone. Examples of output devices include a display device, a lighting device, and a speaker that outputs audio. Examples of input / output devices include a touch panel display. Note that the input device, output device, and input / output device may be built into the computer device or may be external.

[0130] The hardware configuration of the computer device 40 shown in FIG. 23 is an example. The computer device 40 may not have some of the components shown in FIG. 23. The computer device 40 may have components other than those shown in FIG. 23. The computer device 40 may have devices not shown. For example, the computer device 40 may have a camera as an imaging device. The computer device 40 may also have various sensors. The sensors are not limited to a temperature sensor, a humidity sensor, a pressure sensor, an acceleration sensor, a proximity sensor, an optical sensor, etc. The computer device 40 may also have a drive device, etc. The processor 401 may then read programs and data from a recording medium attached to the drive device, etc., into the RAM 403. Examples of recording media include an optical disk, a flexible disk, a magneto-optical disk, and a USB (Universal Serial Bus) memory.

[0131] Furthermore, when the computer device 40 is a mobile body such as the robots 21 and 31, it may have a device for controlling the movement function in addition to the processor 401.

[0132] This concludes the description of the hardware configuration example of each device. There are various variations in the implementation method of each device. For example, the system may be implemented by any combination of different computers and programs for each component. Furthermore, multiple components included in each device may be implemented by any combination of a single computer and program.

[0133] Furthermore, some or all of the components of the information processing device may be realized by circuits for specific applications. Furthermore, some or all of the system may be realized by general-purpose circuits including a processor such as an FPGA (Field Programmable Gate Array). Furthermore, some or all of the system may be realized by a combination of circuits for specific applications and general-purpose circuits. Furthermore, these circuits may be a single integrated circuit. Alternatively, these circuits may be divided into multiple integrated circuits. Furthermore, the multiple integrated circuits may be configured by being connected via a bus or the like.

[0134] Furthermore, when some or all of the components of each device are realized by a plurality of computers, circuits, etc., the plurality of computers, circuits, etc. may be centrally located or distributed.

[0135] The methods described in each embodiment are realized by being executed by a computer device. Also, the methods are realized by being executed by a computer device that executes a program prepared in advance. The programs described in each embodiment are recorded on a computer-readable recording medium such as an HDD, SSD, flexible disk, optical disk, magnetic optical disk, or USB memory. Then, the programs are executed by being read from the recording medium by a computer. Also, the programs may be distributed via a communication network 43.

[0136] The functions of each of the components of the systems in each embodiment described above may be realized by hardware, such as computer device 40 shown in Fig. 23. Alternatively, each component may be realized by a computer device or firmware under program control.

[0137] Although the present disclosure has been described above with reference to various embodiments, the present disclosure is not limited to the above embodiments. The configuration and details of each disclosure may include embodiments to which various modifications that would be apparent to those skilled in the art are applied within the scope of the present disclosure. The present disclosure may also include embodiments in which the details described herein are appropriately combined or substituted as necessary. For example, details described using a particular embodiment may also be applied to other embodiments to the extent that no contradiction occurs. For example, although multiple operations are described in sequence in the form of a flowchart, the order of description does not limit the order in which the multiple operations are performed. Therefore, when implementing each embodiment, the order of the multiple operations may be changed as long as it does not interfere with the content.

[0138] Some or all of the above-described embodiments can be described as follows: However, some or all of the above-described embodiments are not limited to the following.

[0139] (Appendix 1) a rule storage means for storing rules indicating whether or not a mobile object can move to an area having an attribute value corresponding to each attribute of each area for each task that can be assigned to the mobile object; an attribute value storage means for storing attribute values ​​of each attribute in a predetermined area; an acquisition means for acquiring a task assigned to the mobile body in the predetermined area; a generating means for generating map information indicating whether the mobile object can move into the predetermined area based on the acquired rule corresponding to the work and the attribute value of each attribute of the predetermined area; a transmitting means for transmitting the generated map information to the mobile object; A system comprising: (Appendix 2) the predetermined region includes a plurality of small regions, the attribute value storage means stores an attribute value of each of the attributes in each of the plurality of small regions; the generating means generates the map information indicating whether the mobile object can move to each of the plurality of small areas based on the acquired rule corresponding to the task and the attribute value of each of the attributes in the plurality of small areas. 10. The system of claim 1. (Appendix 3) the generating means generates the map information indicating whether the mobile object can move to a small area in a traveling direction of the mobile object among the plurality of small areas. 1. The system described in Appendix 2. (Appendix 4) a determination means for determining a difference between map information already transmitted to the mobile unit and the generated map information; Equipped with the transmitting means transmits the difference to the moving body. 1. The system described in Appendix 2. (Appendix 5) the specifying means specifies a small area to which movement is prohibited in the generated map information from among small areas to which movement is not prohibited in the transmitted map information; the transmitting means transmits information indicating that the moving object is prohibited from moving into the identified small area. 10. The system described in Appendix 4. (Appendix 6) the specifying means specifies a small area to which movement is not prohibited in the generated map information from among small areas to which movement is prohibited in the transmitted map information; the transmitting means transmits information indicating that movement to the identified small area is not prohibited. 10. The system described in Appendix 4. (Appendix 7) the specifying means specifies a difference between the map information already transmitted to the mobile body and the generated map information, regarding the small area in the traveling direction of the mobile body; 7. The system of any of claims 4 to 6. (Appendix 8) a selection means for selecting a rule; Equipped with the rule storage means stores, for each policy, a rule indicating whether or not an attribute value of each attribute can be moved to an area of ​​the attribute value for each task; the selection means selects a rule from the rule storage means based on a policy set in the predetermined area; the generating means generates the map information indicating whether the moving object can move into the predetermined area based on the selected rule and the attribute value of each attribute in the predetermined area. 8. The system of any of claims 1 to 7. (Appendix 9) a selection means for selecting a rule; Equipped with the rule storage means stores, for each attribute value of a predetermined attribute, a rule indicating whether or not the attribute value of each attribute can be moved to an area of ​​the attribute value for each task; the selection means selects a rule from the rule storage means based on the attribute value of the predetermined attribute stored in the attribute value storage means; the generating means generates the map information indicating whether the moving object can move into the predetermined area based on the selected rule and the attribute value of each attribute in the predetermined area. 8. The system of any of claims 1 to 7. (Appendix 10) a rule storage means for storing rules indicating whether or not a mobile object can move to an area having an attribute value corresponding to each attribute of each area for each task that can be assigned to the mobile object; an attribute value storage means for storing attribute values ​​of each attribute in a predetermined area; an acquisition means for acquiring a task assigned to the mobile body in the predetermined area; a generating means for generating map information indicating whether the mobile object can move into the predetermined area based on the acquired rule corresponding to the work and the attribute value of each attribute of the predetermined area; a transmitting means for transmitting the generated map information to the mobile object; An information processing device comprising: (Appendix 11) Acquire tasks assigned to the mobile unit in a predetermined area; a rule storage means for storing rules indicating whether or not the mobile body can move to an area having an attribute value corresponding to each attribute value of each area for each task that can be assigned to the mobile body, and an attribute value storage means for storing attribute values ​​of each attribute of the predetermined area, and generating map information indicating whether or not the mobile body can move to the predetermined area based on the rule corresponding to the task that has been acquired and the attribute value of each attribute of the predetermined area; transmitting the generated map information to the mobile object; method. (Appendix 12) On the computer, A process of acquiring tasks assigned to the mobile body in a predetermined area; a process of generating map information indicating whether the mobile body can move to a predetermined area based on the acquired rule corresponding to the work and the attribute value of each attribute of the predetermined area, by referring to a rule storage means that stores rules indicating whether the mobile body can move to the area for each attribute value for each area for each work that can be assigned to the mobile body, and an attribute value storage means that stores the attribute values ​​of each attribute of the predetermined area; a process of transmitting the generated map information to the mobile object; A program that executes the following. (Appendix 13) A process of acquiring tasks assigned to the mobile body in a predetermined area; a process of generating map information indicating whether the mobile body can move to a predetermined area based on the acquired rule corresponding to the work and the attribute value of each attribute of the predetermined area, by referring to a rule storage means that stores rules indicating whether the mobile body can move to the area for each attribute value for each area for each work that can be assigned to the mobile body, and an attribute value storage means that stores the attribute values ​​of each attribute of the predetermined area; a process of transmitting the generated map information to the mobile object; A computer-readable recording medium that records a program that causes a computer to execute the above. [Explanation of symbols]

[0140] 1 System 2. System 10. Information processing equipment 20 Information processing equipment 21. Robot 22 Robot Management Device 23 Communication Network 30 Information processing equipment 31 Robot 40 Computer Equipment 43 Communication Network 101 Acquisition Department 102 Generation part 103 Transmitter 104 Rule Memory 105 Attribute value storage unit 201 Work Acquisition Department 202 Generation part 203 Transmitter 204 Rule Memory 205 Attribute Value Storage Unit 206 Data Acquisition Department 207 Specific section 208 Memory section 211 Work Management Department 212 Map Acquisition Department 213 Movement control unit 301 Work Acquisition Department 302 Generation part 303 Transmission Unit 304 Rule Memory 305 Attribute Value Storage Unit 306 Data Acquisition Department 307 Specific section 308 Storage section 309 Selection Section 401 processor 402 ROM 403 RAM 404 Storage device 405 Communication Interface 406 Output Interface 407 Bus

Claims

1. a rule storage means for storing rules indicating whether or not a mobile object can move to an area having an attribute value corresponding to each attribute of each area for each task that can be assigned to the mobile object; an attribute value storage means for storing attribute values ​​of each attribute in a predetermined area; an acquisition means for acquiring a task assigned to the mobile body in the predetermined area; a generating means for generating map information indicating whether the mobile object can move into the predetermined area based on the acquired rule corresponding to the work and the attribute value of each attribute of the predetermined area; a specifying means for specifying a difference between map information already transmitted to the mobile unit and the generated map information; a transmitting means for transmitting the generated map information to the mobile body, and, if map information has already been transmitted to the mobile body, transmitting the identified difference; Equipped with the attributes of the predetermined area include at least one of an attribute representing an environment, an attribute representing whether or not there is a pregnant woman, an attribute representing whether or not there is a child, an attribute representing whether or not there is a person in a wheelchair, and an attribute representing whether or not there is an important person; the predetermined region includes a plurality of small regions, the attribute value storage means stores an attribute value of each of the attributes in each of the plurality of small regions; the generating means generates the map information indicating whether the mobile object can move to each of the plurality of small areas based on the acquired rule corresponding to the task and the attribute value of each of the attributes in the plurality of small areas. system.

2. the specifying means specifies a small area to which movement is prohibited in the generated map information from among small areas to which movement is not prohibited in the transmitted map information; the transmitting means transmits information indicating that movement to the identified small area is prohibited. The system of claim 1 .

3. the specifying means specifies a small area to which movement is not prohibited in the generated map information from among small areas to which movement is prohibited in the transmitted map information; the transmitting means transmits information indicating that movement to the identified small area is not prohibited. The system of claim 1 .

4. the specifying means specifies a difference between the map information already transmitted to the mobile body and the generated map information, regarding the small area in the traveling direction of the mobile body; A system according to any one of claims 1 to 3.

5. a rule storage means for storing rules indicating whether or not a mobile object can move to an area having an attribute value corresponding to each attribute of each area for each task that can be assigned to the mobile object; an attribute value storage means for storing attribute values ​​of each attribute in a predetermined area; an acquisition means for acquiring a task assigned to the mobile body in the predetermined area; a generating means for generating map information indicating whether the mobile object can move into the predetermined area based on the acquired rule corresponding to the work and the attribute value of each attribute of the predetermined area; a transmitting means for transmitting the generated map information to the mobile object; Equipped with the attributes of the predetermined area include at least one of an attribute representing an environment, an attribute representing whether or not there is a pregnant woman, an attribute representing whether or not there is a child, an attribute representing whether or not there is a person in a wheelchair, and an attribute representing whether or not there is an important person; the predetermined region includes a plurality of small regions, the attribute value storage means stores an attribute value of each of the attributes in each of the plurality of small regions; the generating means generates the map information indicating whether the mobile object can move to a small area in a traveling direction of the mobile object among the plurality of small areas based on the acquired rule corresponding to the task and the attribute value of each of the attributes in the plurality of small areas. system.

6. a selection means for selecting a rule; Equipped with the rule storage means stores, for each attribute value of a predetermined attribute, a rule indicating whether or not the attribute value of each attribute can be moved to an area of ​​the attribute value for each task; the selection means selects a rule from the rule storage means based on the attribute value of the predetermined attribute stored in the attribute value storage means; the generating means generates the map information indicating whether the moving object can move into the predetermined area based on the selected rule and the attribute value of each attribute in the predetermined area.

6. A system according to any one of claims 1 to 5.

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