Information processing device, information processing method, and program

Abstract

An information processing device (1) according to the present disclosure includes an estimation unit (12) that estimates an influence degree indicating the presence of a moving object when the moving object is in motion.

Description

[Technical field]

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

[0002] In recent years, mobile objects, including robots, have been increasingly introduced in various situations. It is expected that mobile objects will work together and coexist with humans in the future, and that mobile objects will become more familiar to humans. For this reason, various studies that take into account the presence of mobile objects will be necessary. Patent Document 1 discloses a technology that allows a mobile robot to wait at a specific position when passing through a narrow passage so as not to obstruct the passage of workers or other mobile robots. The technology described in Patent Document 1 makes it possible to prevent the mobile robot from obstructing the passage of workers. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2023-009850 A Summary of the Invention [Problem to be solved by the invention]

[0004] When humans and mobile objects coexist, if the presence of the mobile object is too strong, it may cause stress to the human, and conversely, if the mobile object does not have a presence when assisting a human, the mobile object may not be able to appropriately assist the human. Therefore, in order to appropriately control the mobile object according to the situation, it is desirable to first grasp the presence of the mobile object, but the technology described in Patent Document 1 does not disclose how to grasp the presence of the mobile object.

[0005] The present disclosure has been made in consideration of the above, and has an object to provide an information processing device capable of grasping the presence of a moving object. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the object, an information processing device according to the present disclosure includes an estimation unit that estimates an influence degree that indicates the presence of a moving body when the moving body operates, and a control processing unit that controls a control target device that is at least one of the moving body and a peripheral device around the moving body based on the influence degree, and the influence degree includes a first influence degree that indicates the degree of influence that the moving body has on the surroundings when it operates, and a second influence degree that indicates the degree of influence that an estimated target object that is at least one of a person and an object receives from the moving body. , regulation The control processing unit controls the control target device based on the first impact degree and the second impact degree. The estimation unit includes a first estimation unit that estimates a first influence degree and a second estimation unit that estimates a second influence degree. do. Effect of the Invention

[0007] The information processing device according to the present disclosure provides an effect of being able to grasp the presence of a moving object. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing a configuration example of an information processing system according to a first embodiment; [Diagram 2] 1 is a flowchart showing an example of a processing procedure in the information processing device according to the first embodiment. [Diagram 3] FIG. 1 is a diagram showing an example of data acquired by an experiment in the first embodiment. [Figure 4] FIG. 13 is a diagram showing another example of data acquired by an experiment in the first embodiment. [Diagram 5] FIG. 1 is a diagram showing a configuration example of a first estimation unit according to a first embodiment in the case where machine learning is used; [Figure 6] FIG. 1 is a diagram showing an example of a target influence degree according to facility information in the first embodiment; [Figure 7] FIG. 1 is a diagram showing an example of a target influence degree according to a person's behavior in the first embodiment; [Figure 8] FIG. 1 is a diagram showing an example of a change in a person's position in the first embodiment; [Figure 9] FIG. 1 is a diagram showing an example of a target influence degree according to a person's position in the first embodiment; [Figure 10] FIG. 1 is a diagram showing an example of the actions of a plurality of people according to the first embodiment; [Figure 11] FIG. 1 is a diagram showing an example of a target influence degree according to the content of a conversation in the first embodiment; [Figure 12] FIG. 1 shows an example of seating arrangement in the first embodiment. [Figure 13] FIG. 1 is a diagram showing an example of seat presence information according to the first embodiment; [Figure 14] FIG. 1 is a diagram for explaining control taking into account the line of sight direction according to the first embodiment; [Figure 15] FIG. 1 is a diagram showing an example of a target influence degree according to a person's behavior in the first embodiment; [Figure 16] FIG. 1 is a diagram for explaining a reduction in the degree of influence due to control of peripheral devices according to the first embodiment; [Figure 17] FIG. 1 is a diagram showing an example of the configuration of a computer system that realizes each of the information processing devices according to the first embodiment. [Figure 18] FIG. 13 is a diagram illustrating a configuration example of an information processing system according to a second embodiment. [Figure 19] 11 is a flowchart showing an example of a processing procedure in an information processing device according to a second embodiment. [Figure 20] FIG. 13 is a diagram showing an example of a display screen displayed on the display device of the second embodiment; [Figure 21] FIG. 13 is a diagram showing an example of a display screen displayed on the display device of the second embodiment; [Figure 22] FIG. 13 is a diagram showing an example of a display screen displayed on the display device of the second embodiment; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] An information processing device, an information processing method, and a program according to an embodiment will be described in detail below with reference to the drawings.

[0010] Embodiment 1 FIG. 1 is a diagram showing a configuration example of an information processing system 100 according to an embodiment. The information processing system 100 according to the embodiment includes an information processing device 1 and a control target device 2. The information processing device 1 is a control device that estimates the degree of influence when a moving object operates and controls the control target device 2 using the estimated degree of influence. Specifically, the degree of influence when a moving object operates is, for example, the degree of influence on a person or an object when the moving object operates, and is a numerical value indicating the presence of the moving object. The object referred to here is, for example, another moving object, a structure, furniture, equipment, etc., but is not limited to these. The operation of the moving object includes, for example, the movement of the moving object, the movement of the moving object other than the movement, the output of a sound by the moving object, and a display by the moving object (a moving object having a display function).

[0011] The moving body is, for example, a robot equipped with a moving mechanism, but is not limited thereto, and may be any moving body capable of moving autonomously or by remote control. When the moving body is a robot, the robot may be a robot having a function of performing a specific task, such as a transport robot, a cleaning robot, or a guide robot, or may be a robot intended to communicate with people, or may be a multi-functional robot having multiple functions, or may be other than these. In addition, the moving body may be a moving body equipped with a moving mechanism such as wheels or crawlers and moving on the ground or floor, or may be a moving body having two or four legs such as a humanoid robot or an animal robot, or may be a robot capable of flying in the air such as an unmanned aerial vehicle (drone). The moving mechanism in the moving body is not limited to these.

[0012] The control target device 2 is a device controlled by the information processing device 1 to change the influence degree of a moving object, and may be the moving object itself or a peripheral device around the moving object. Examples of the peripheral device include, but are not limited to, a display, a lighting device, a speaker, and the like.

[0013] The information processing device 1 includes an information storage unit 11, an estimation unit 12, a control processing unit 15, an acquisition unit 16, and a reception unit 17. The information storage unit 11 stores various information used in processing in the information processing device 1, such as first information used to estimate a first influence degree, which will be described later, and second information used to estimate a second influence degree, which will be described later.

[0014] The estimation unit 12 estimates the degree of influence when the moving body operates, and outputs the estimated degree of influence, i.e., the estimation result of the degree of influence, to the control processing unit 15. In detail, the estimation unit 12 includes a first estimation unit 13 that estimates a first degree of influence and outputs the estimated first degree of influence to the control processing unit 15, and a second estimation unit 14 that estimates a second degree of influence and outputs the estimated second degree of influence to the control processing unit 15.

[0015] The first degree of influence is an influence degree that indicates the degree of influence that a moving object has on the surroundings when it operates. The first degree of influence is an influence degree that depends on the moving object, and is an influence degree that does not depend on the person or object that is affected. On the other hand, the second degree of influence is an influence degree that indicates the degree of influence that a person or object receives from a moving object. The second degree of influence is an influence degree that depends on the person or object that is affected by the moving object. For example, when there is a large moving object that moves at high speed, people are generally more susceptible to the influence of the moving object. In this way, the degree of influence of a moving object may depend on the moving object itself. On the other hand, for example, when a stationary moving object enters the field of view, some people feel uncomfortable just by entering the field of view, while others do not particularly mind it. In addition, when a moving object generates a sound associated with movement or work, whether or not the sound is bothersome may differ from person to person. In this way, even if the same moving object performs the same operation, people may feel differently. The same is true for objects that are affected by a moving object. For example, a desk is not affected by a moving object passing nearby unless it collides with it, but a display device that displays advertisements around it is affected when a moving object passes near the display screen, as it interferes with the display of the advertisement.

[0016] From the above, the estimation unit 12 estimates both the degree of influence that depends on the moving body and the degree of influence that depends on the person or object. This allows the estimation unit 12 to obtain a more appropriate degree of influence than when only one of the degrees of influence is considered. In the following, an example in which the estimation unit 12 includes both the first estimation unit 13 and the second estimation unit 14 will be described, but the estimation unit 12 may include only one of the first estimation unit 13 and the second estimation unit 14. In other words, the estimation unit 12 only needs to estimate at least one of the first degree of influence and the second degree of influence.

[0017] Furthermore, the estimation unit 12 may estimate the first influence degree and the second influence degree using reference information for estimation acquired by the acquisition unit 16. The reference information for estimation includes, for example, at least one of surrounding information, facility information, equipment information, attribute information, and state information.

[0018] The surrounding information includes, for example, at least one of first surrounding information indicating information about the surroundings of a moving object and second surrounding information indicating information about the surroundings of a person or object. For example, the first surrounding information is used when estimating a first influence degree, and the second surrounding information is used when estimating a second influence degree. The first surrounding information is, for example, information indicating the situation about the surroundings of a moving object, and the second surrounding information is, for example, information indicating the situation about the surroundings of a person or object. The first surrounding information and the second surrounding information may be static information, dynamic information, i.e., information indicating a state, or a combination of these.

[0019] The first surrounding information includes, but is not limited to, information indicating at least one of the following: the position of a person or object existing around the moving body, the speed of a person or object existing around the moving body, the behavior of a person existing around the moving body, and the content of a conversation of a person existing around the moving body. The first surrounding information may also include, for example, at least one of image information obtained by photographing the surroundings of the moving body, biometric information of a person existing around the moving body, and sound information indicating a sound around the moving body. The position of a person or object may be calculated from the image information. Also, position information indicating a position detected by a position detection device such as a GPS (Global Positioning System) receiver provided in the mobile terminal carried by a person may be transmitted and received by the information processing device 1. Also, the photographing device that photographs the surroundings of the moving body may be provided on the moving body, or may be set in a facility where the moving body is used. A device such as a microphone that detects a sound around the moving body may be provided on the moving body, or may be set in the facility. The position of the person or object may be indicated by position coordinates, or may be indicated in relation to equipment, structures, etc. within the facility in the estimation target range, which is the range within which the influence of the moving object is estimated, such as, for example, sitting at a desk, away from the desk, or outside the room.

[0020] The second surrounding information is generated according to a person or object that may be affected by the moving object, that is, a person or object that is the subject of evaluation of the influence of the moving object (hereinafter, also referred to as an evaluation object). The second surrounding information includes, but is not limited to, information indicating at least one of the following: the position of the moving object existing around the evaluation object, the speed of the moving object existing around the evaluation object, the operation mode of the moving object existing around the evaluation object, the loudness (volume) of the sound emitted by the moving object existing around the evaluation object, and information on the object (other than the moving object) existing around the evaluation object. The second surrounding information may include, for example, at least one of image information obtained by photographing the surroundings of the evaluation object and sound information indicating the sound around the evaluation object. In addition, the photographing device that photographs the surroundings of the evaluation object may be provided on the object, may be provided on a mobile terminal carried by a person, or may be set in a facility. A device such as a microphone that detects the sound around the moving object may be provided on the object, may be provided on a mobile terminal carried by a person, or may be set in a facility. In addition, for example, image information photographed by a photographing device provided in a facility may serve as both the first surrounding information and the second surrounding information. In this way, the first peripheral information and the second peripheral information may include the same information.

[0021] The facility information includes, for example, information indicating the type of facility where the mobile object is used, i.e., the facility where the mobile object is present, but is not limited thereto. This facility is also a facility where an evaluation target object is present. The facility corresponds to, for example, an estimation target range, which is a range in which the information processing device 1 estimates the influence degree of the mobile object. Note that the estimation target range is not limited to one independent facility, and may be a part of a facility or a combination of multiple facilities. The facility may be indoors, outdoors, or a combination of indoors and outdoors.

[0022] The facility information is information about facilities in a facility where the mobile object is present. The facility information includes, for example, information indicating at least one of the position and shape of a wall and the position and shape of a road. In addition, the facility information may include, for example, information about an event held in a lobby or other facility in the hotel in the case where the facility in which the mobile object is used is a hotel, information about an elevator in the facility in which the mobile object is used, and seat occupancy information in an office or the like. The facility information is not limited to these. In addition, the facility information may be image information acquired from a photographing device such as a surveillance camera, or may be seat reservation information in a workplace operated in a free address system. The facility information and the facility information may be input by an operator or the like, or may be transmitted from another device not shown.

[0023] The attribute information includes at least one of first attribute information indicating an attribute of the moving object and second attribute information indicating an attribute of the evaluation target object. The first attribute information includes at least one of the type, size, color, shape, etc. of the moving object, but is not limited thereto. The first attribute information may be input by an operator or the like, or may be image information obtained by photographing the moving object. When the first attribute information is image information, for example, the acquisition unit 16 or the estimation unit 12 estimates the attribute of the moving object from the image information.

[0024] The second attribute information includes at least one of the following when the evaluation target is a person: sex, generation, age, information identifying whether the person is an adult or a child, personality, etc., and when the evaluation target is an object, includes, but is not limited to, the type and function of the object. For example, the first attribute information is used when estimating the first influence degree, and the second attribute information is used when estimating the second influence degree. The second attribute information may be input by an operator or the like, or may be transmitted from another device (not shown).

[0025] The second attribute information may be image information obtained by photographing the evaluation object, or may be input by the person himself / herself when the evaluation object is a person. When input by the person himself / herself, for example, when entering a facility, room, etc. where a mobile object is used, the person may input the second attribute information using an input device provided at an entrance or the like, and the acquisition unit 16 of the information processing device 1 may receive the second attribute information from the input device. When the second attribute information is image information obtained by photographing the evaluation object, for example, the acquisition unit 16 or the estimation unit 12 estimates the attribute of the evaluation object from the image information.

[0026] Alternatively, the information storage unit 11 may store in advance registration information associating face information obtained by photographing a person's face with information indicating the attributes of the person, and the acquisition unit 16 or the estimation unit 12 may identify the person by performing face recognition processing using the image information and face information. The acquisition unit 16 or the estimation unit 12 may acquire second attribute information by extracting information indicating attributes corresponding to the identified person from the registration information. Alternatively, the information storage unit 11 may store in advance registration information associating identification information of a mobile terminal such as a smartphone or tablet carried by a person with information indicating the attributes of the corresponding person, and the acquisition unit 16 of the information processing device 1 may receive, from the mobile terminal, identification information of the mobile terminal and location information indicating the location of the mobile terminal. In this case, when the acquisition unit 16 or the estimation unit 12 determines based on the received location information that the person corresponding to the mobile terminal is to be the evaluation target, information indicating the attributes of the person corresponding to the identification information of the mobile terminal may be extracted from the registration information. For example, when the acquisition unit 16 or the estimation unit 12 determines that the mobile terminal exists within the estimation target range, the acquisition unit 16 or the estimation unit 12 determines that the person corresponding to the mobile terminal is to be the evaluation target.

[0027] The status information includes at least one of first status information indicating the status of the moving object and second status information indicating the status of the evaluation object. The first status information includes, but is not limited to, at least one of the following: the operation mode of the moving object (cleaning, talking, transporting, guiding, dancing, etc.), the loudness (volume) of the sound generated by the moving object, the color of the moving object (when the color can be changed by the moving object having a display), the moving direction of the moving object, the speed of the moving object, the moving vector of the moving object, etc. The second status information includes, but is not limited to, at least one of the following: the position of the evaluation object, the type of the evaluation object's operation (working, sleeping, etc.), the speed of the evaluation object, and information indicating the emotion of the evaluation object. The first status information may be image information obtained by photographing the moving object, and the second status information may be image information obtained by photographing the evaluation object. The first status information may also be sound information that is a detection result of the sound generated by the moving object, and the second status information may also be sound information that is a detection result of the sound generated by the evaluation object. Moreover, the first state information is used when estimating the first influence degree, and the second state information is used when estimating the second influence degree. When the control processing unit 15 manages the operation mode, operation type, etc. of the moving object, the first attribute information may be input from the control processing unit 15 to the estimation unit 12. Details of the estimation reference information and details of the estimation method in the estimation unit 12 will be described later.

[0028] The control processing unit 15 controls the control target device 2 using the influence degree received from the estimation unit 12. In detail, for example, the control processing unit 15 calculates a total influence degree, which is a total influence degree, using the first influence degree and the second influence degree received from the estimation unit 12, generates a control signal for controlling the control target device 2 so as to bring the total influence degree closer to a target value (target influence degree) using the total influence degree, and outputs the control signal to the control target device 2. There may be a plurality of control target devices 2, and in this case, the control processing unit 15 generates a control signal corresponding to each of the plurality of control target devices 2, and outputs the generated control signal to the corresponding control target device 2.

[0029] In addition, when the estimation unit 12 estimates only the first influence or only the second influence, the control processing unit 15 does not need to calculate the total influence, and controls the controlled device 2 using the influence (the first influence or the second influence) received from the estimation unit 12. In addition, the control processing unit 15 may calculate the total influence by adding the first influence and the second influence, or may calculate the total influence by weighting and adding the first influence and the second influence, or may calculate the total influence by a method other than these. For example, the control processing unit 15 adds or weights and adds the value of the first influence and the value of the second influence corresponding to the same position using the first influence obtained as a distribution and the second influence obtained as a distribution.

[0030] Furthermore, the control processing unit 15 may control the controlled device 2 using control reference information acquired by the acquisition unit 16 in addition to the influence degree received from the estimation unit 12. The control reference information includes, for example, at least one of surrounding information, facility information, equipment information, attribute information, and state information, similar to the above-mentioned estimation reference information. The estimation reference information and the control reference information may be the same or different, or may be partially overlapping and the remaining parts different. Details of the processing in the control processing unit 15 will be described later.

[0031] The acquisition unit 16 acquires information such as estimation reference information and control reference information. The acquisition unit 16 outputs the acquired estimation reference information to the estimation unit 12, and outputs the acquired control reference information to the control processing unit 15. As described above, the estimation reference information and the control reference information may be input by an operator or may be transmitted from another device. That is, the acquisition unit 16 may acquire the estimation reference information, the control reference information, and the like by accepting an input from an operator, or by receiving the information from another device.

[0032] The reception unit 17 receives various instructions. For example, the reception unit 17 receives an instruction to start control of the impact degree. The reception unit 17 may receive the instruction by receiving an input from an operator, or may receive the instruction by receiving an instruction from another device.

[0033] Next, the operation of this embodiment will be described. Fig. 2 is a flowchart showing an example of a processing procedure in the information processing device 1 of this embodiment. For example, when the information processing device 1 receives an instruction to start control of the impact degree, it starts the processing shown in Fig. 2, but the trigger for starting the processing is not limited to this example.

[0034] 2, the information processing device 1 estimates a first influence degree by using the first information (step S1). Specifically, the first estimation unit 13 estimates the first influence degree by using the first information, and outputs the estimation result to the control processing unit 15.

[0035] The estimation result of the first influence is, for example, information indicating the influence for each position of the moving body in the estimation target range, that is, the distribution (planar distribution or spatial distribution) of the first influence, but is not limited thereto, and may be one or more values ​​(values ​​of the influence) according to the position of the moving body at that time. The one or more values ​​according to the position of the moving body at that time are, for example, one influence corresponding to the position of the moving body at that time, or a predetermined number of influences of the position of the moving body at that time and its surroundings. Whether to obtain a distribution as the estimation result of the first influence or to obtain one or more values ​​according to the position of the moving body at that time may be determined according to the calculation method of the influence and the contents of the control of the influence described later. For example, when both the first influence and the second influence are estimated as the influence, the first estimation unit 13 may output information indicating the distribution of the first influence as the estimation result. Also, for example, when only the first influence is estimated as the influence and the sound generated by the moving body is controlled, the first estimation unit 13 may output one or more values ​​according to the position of the moving body at that time as the estimation result. In addition, the first estimation unit 13 may output information indicating the distribution of the first influence degree to the control processing unit 15, and when the control processing unit 15 controls the control target device 2, the control processing unit 15 may use the information indicating the distribution of the first influence degree to determine one or more values ​​corresponding to the position of the moving body at that time, and perform the control described below based on the determined one or more values.

[0036] The first information is information calculated using data acquired, for example, by an experiment to investigate the influence of a moving object, and is information for estimating the first influence. Here, a calculation method of the first information will be described. For example, in an experiment to investigate the influence of a moving object, the influence of the evaluation object is acquired in a state where at least one of the position of the moving object and the position of the evaluation object is different. If the evaluation object is a person, the person determines the influence. If the evaluation object is an object, for example, an operator evaluates the state of the object and determines the influence. This is performed for multiple evaluation objects, and multiple data sets including the positions of the moving object and the evaluation object and the acquired influence are recorded.

[0037] In addition, when various conditions within the estimation target range are uniform, the relative positions of the moving body and the evaluation object may be recorded instead of recording the position of the moving body and the position of the evaluation object as a data set. For example, the relative position may be expressed by indicating the position of the evaluation object in an XY coordinate system with a fixed reference point on the moving body as the origin. The method of expressing the relative position is not limited to this example. In addition, when various conditions within the estimation target range are not uniform and the degree of influence differs depending on the absolute positions of the moving body and the evaluation object, the position of the moving body and the evaluation object are used without using the relative position. In this case, it is desirable to conduct the experiment in the actual estimation target range. When using the relative position as the data set, the estimation target range and the location of the experiment may be different, but it is desirable that the location of the experiment is similar to the estimation target range in various conditions. In addition, when the moving body is a flying moving body, the positions, relative positions, etc. of the moving body and the evaluation object are expressed in a three-dimensional coordinate system, for example, an XYZ coordinate system, rather than a two-dimensional XY coordinate system.

[0038] FIG. 3 is a diagram showing an example of data acquired by an experiment in this embodiment. In the example shown in FIG. 3, #1, #2, #3, etc. indicate the identification information of a person, and indicate the degree of influence felt by each person, i.e., evaluated by each person, for each relative position (the relative position between the moving object and the person). For example, the degree of influence is indicated on a scale of 10 from 1 to 10, and the person participating in the experiment selects the degree of influence from the values ​​from 1 to 10. Note that the quantification of the degree of influence is not limited to the example shown on a scale of 10, and may be indicated by any number of levels. Also, here, an example is described in which the larger the numerical value of the degree of influence, the greater the influence, but the degree of influence may be defined so that the smaller the numerical value of the degree of influence, the greater the influence.

[0039] The first information is calculated using the degree of influence evaluated by a plurality of people, for example, as shown in FIG. 3. Here, an example in which the first estimation unit 13 calculates the first information will be described, but the calculation of the first information may be performed by another device (not shown). When the other device calculates the first information, the first information calculated by the other device is stored in the information storage unit 11. For example, the acquisition unit 16 may acquire the first information from the other device and store the first information in the information storage unit 11, or the acquisition unit 16 may acquire the first information by inputting the first information by an operator and store the first information in the information storage unit 11. When the first estimation unit 13 calculates the first information, data (data set) obtained by an experiment is stored in the information storage unit 11, and the first estimation unit 13 calculates the first information using the data stored in the information storage unit 11.

[0040] FIG. 4 is a diagram showing another example of data acquired by an experiment in this embodiment. In FIG. 3, the relative position is changed to evaluate the degree of influence, but the present invention is not limited to this, and an experiment may be performed by changing the value of the information used as the estimation reference information. In the example shown in FIG. 4, the relative position and the loudness (volume) of the sound generated by the moving object are changed to perform an experiment, and a person evaluates the degree of influence for each combination of the relative position and the volume. Note that, in FIG. 3 and FIG. 4, the data is shown in a table format for illustration, but the data storage format is not limited to this and may be any format. The estimation reference information is not limited to the loudness of the sound generated by the moving object, and may include, for example, at least one of the moving direction of the moving object and facility information. The estimation reference information may also include at least one of the color, size, and operation mode of the moving object.

[0041] For example, when the data shown in FIG. 3 is obtained by an experiment, the first estimation unit 13 generates first information indicating the degree of influence for each relative position. Specifically, for example, the first estimation unit 13 calculates a representative value such as an average value or a median value of the degree of influence evaluated by each of the relative positions. As a result, the representative value of the degree of influence for each relative position is obtained as a planar distribution. For example, a rectangle of a predetermined size is set as one mesh, the degree of influence for each mesh is obtained by an experiment, and the first estimation unit 13 sets the representative value for each mesh as the degree of influence, thereby obtaining a planar distribution of the degree of influence. The first estimation unit 13 may use this planar distribution as the first information. Note that, when experimental data is obtained by changing the position in the three-dimensional coordinate system, a spatial distribution is obtained instead of a planar distribution.

[0042] Alternatively, the first estimation unit 13 may use the representative value for each relative position to calculate an approximation formula indicating the degree of influence according to the relative position by regression analysis or the like, and use the approximation formula as the first information. The approximation formula may be a polynomial, or a formula using logarithms, exponents, or the like, and is not particularly limited. The method of calculating the approximation formula is not limited to these examples.

[0043] For example, when the data shown in FIG. 4 is obtained by an experiment, the first estimation unit 13 may divide the volume into a plurality of ranges of levels, calculate the first information for each level in the same manner as when the data shown in FIG. 3 is used, and store the first information for each level in the information storage unit 11. Alternatively, the first estimation unit 13 may obtain a representative value for each relative position and volume, calculate an approximation formula indicating the degree of influence according to the relative position and volume by regression analysis or the like, and use the approximation formula as the first information. As in the above example, the approximation formula may be a polynomial, or may be a formula using logarithms, exponents, or the like, and is not particularly restricted. The method of calculating the approximation formula is not limited to these examples.

[0044] Alternatively, the first estimation unit 13 may use a certain volume as a reference, calculate information similar to the first information in the case of using the data shown in FIG. 3 described above using data corresponding to the reference volume as reference information, and calculate correction information for performing correction according to the volume. For example, a representative value such as an average value or a median value of the influence degree obtained by an experiment may be calculated for each volume, and a difference or ratio between the representative value of the reference volume and the representative value of the volume other than the reference volume may be calculated, and the calculated difference or ratio may be used as the correction information. Alternatively, the first estimation unit 13 may use the representative value for each volume to calculate an approximation formula indicating the influence degree according to the volume by regression analysis or the like, and use the calculated approximation formula as the correction information. In addition, the first estimation unit 13 may calculate the correction information as common information regardless of the relative position, or may divide the relative position into a plurality of sections and calculate the correction information for each section. The first estimation unit 13 stores the reference information and correction information calculated in this way in the information storage unit 11 as first information.

[0045] In addition, when the position of the moving body and the position of the object to be evaluated are used instead of the relative positions, the first estimation unit 13 calculates the first information by calculating the influence for each mesh or an approximation formula, for example, by calculating a representative value such as the average value or median value of the influence evaluated for each position of the moving body and similarly for each position of the object to be evaluated.

[0046] The first estimation unit 13 may also perform an experiment by changing the position of the moving object, and record a data set in which the position of the moving object is associated with the degree of influence evaluated by people at various positions. In this case, a representative value such as an average value or a median value of the degree of influence is calculated for each position of the moving object, thereby calculating the degree of influence according to the position of the moving object as a distribution. The first estimation unit 13 stores the degree of influence according to the position of the moving object in the information storage unit 11 as first information.

[0047] 3 and 4 are illustrative, and are not limited to these examples. Experiments are performed according to the information used as the estimation reference information. For example, when the color of a moving body is used as the estimation reference information, experiments are performed by changing not only the position of the moving body and the position of the evaluation object but also the color of the moving body, and the first information may be calculated for each color of the moving body, or the reference information and correction information for correcting the difference due to color may be generated as the first information. The same applies when other information (other types of information) is used as the estimation reference information. Similarly, when multiple types of information are used as the estimation reference information, the first information may be calculated for each combination of values ​​of multiple types of information, or the reference information and correction information for each type of information may be calculated as the first information, or an approximation formula showing the relationship between the value of multiple types of information and the degree of influence may be generated as the first information.

[0048] The first information may be a trained model generated by machine learning. FIG. 5 is a diagram showing a configuration example of the first estimation unit 13 of the present embodiment when machine learning is used. In the example shown in FIG. 5, the first estimation unit 13 includes a model generation unit 131 and an inference unit 132. The model generation unit 131 generates a trained model by, for example, supervised learning, and stores the generated trained model in the information storage unit 11 as the first information. When estimating the first influence degree, the inference unit 132 estimates (infers) the first influence degree using the trained model. The trained model is a trained model for inferring the first influence degree from a feature amount, and the feature amount may be a relative position, a position of a moving body, or reference information for estimation, or the relative position or the position of a moving body and the reference information for estimation.

[0049] When learning is performed using data obtained by the experiment illustrated in Fig. 3 above, for example, the model generation unit 131 generates a trained model by supervised learning using multiple data sets including relative positions and influences (corresponding to the first influences obtained by the experiment) that are ground truth data corresponding to the relative positions. The inference unit 132 inputs the relative positions to the trained model to obtain an estimate of the first influence for each relative position. The inference unit 132 obtains a distribution of the first influences by performing the same process for each of the multiple relative positions.

[0050] Alternatively, when learning is performed using data obtained by the experiment illustrated in Fig. 3, the model generation unit 131 may generate a trained model by supervised learning using a plurality of data sets including the positions of the moving object and the distribution of influences that are ground truth data corresponding to the positions. In this case, the inference unit 132 obtains the first distribution of influences by inputting the positions of the moving object to the trained model.

[0051] Furthermore, when learning is performed using data obtained by the experiment illustrated in FIG. 4, the model generation unit 131 uses the relative position and the estimation reference information (volume in the example illustrated in FIG. 4) as features, and generates a trained model by supervised learning using multiple data sets including the features and the influences that are the corresponding ground truth data. The inference unit 132 inputs the relative position and the estimation reference information to the trained model to obtain an estimate of the first influence for each relative position. The inference unit 132 obtains a distribution of the first influences by performing the same process for each of the multiple relative positions.

[0052] Alternatively, when learning is performed using data obtained by the experiment illustrated in Fig. 4, the model generation unit 131 may generate a trained model by supervised learning using a plurality of data sets including the estimation reference information and the distribution of influences that are the correct answer data corresponding to the estimation reference information. In this case, the inference unit 132 obtains the first influence distribution by inputting the estimation reference information to the trained model.

[0053] Examples of machine learning used to generate the trained model include neural networks and support vector machines, but the machine learning algorithm is not limited to these. The specific machine learning methods described above are merely examples and are not limited to these, and machine learning may be performed by any method as long as a trained model for inferring the first influence degree is generated.

[0054] 5 shows an example in which the first estimation unit 13 includes the model generation unit 131, but the present invention is not limited to this. A learning device other than the information processing device 1 may include the model generation unit 131, and the learning device may generate the trained model. In this case, the trained model generated by the learning device is stored in the information storage unit 11, and the inference unit 132 of the first estimation unit 13 estimates the first influence degree using the trained model stored in the information storage unit 11.

[0055] In addition, when data is acquired for each relative position, in estimating the first influence degree in the above-mentioned step S1, the first estimation unit 13 can estimate the distribution of the first influence degree centered on the position of the moving body by setting the position of the moving body as the origin of the relative position based on the position (current position) of the moving body. The position of the moving body is acquired from the moving body as, for example, state information. In addition, as shown in FIG. 4, in the experiment, when data is acquired for each volume in the experiment, in estimating the first influence degree in the above-mentioned step S1, the first estimation unit 13 calculates the first influence degree according to the volume by using sound information indicating the loudness (volume) of the sound generated by the moving body detected by a sound detector or the like and the first information.

[0056] In addition, when experimental data is obtained using the position of the moving body and the position of the object to be evaluated instead of the relative position, the first estimation unit 13 reads out first information from the information storage unit 11 based on the position of the moving body (current position), and estimates the first influence by setting the read out first information as the first influence.

[0057] In addition, when a first influence degree according to the position of the moving body is stored as first information in the information storage unit 11, the first estimation unit 13 reads out the first information using the first information and estimates the first influence degree by setting the read out first information as the first influence degree.

[0058] For example, the first estimation unit 13 may estimate the first influence without using a part of the estimation reference information considered when generating the first information. For example, when generating reference information and correction information corresponding to the color, size, and volume of the moving body by changing the color, size, and volume of the moving body (the volume of the sound generated by the moving body) of each moving body and performing an experiment, the first estimation unit 13 may correct the reference information using only the correction information related to the color and size. Also, when an approximation formula is calculated as the first information, the first estimation unit 13 may generate an approximation formula that considers all of the color, size, and volume, an approximation formula that considers two types of the color, size, and volume, and an approximation formula that considers one type of the size and volume, and select the approximation formula to be used according to the type of information to be considered when estimating the second influence. Also, when the first information is a trained model, a trained model considering all of color, size, and volume, a trained model considering two of color, size, and volume, and a trained model considering one of size and volume may be generated, and the trained model to be used may be selected according to the type of information to be considered when estimating the second influence. This makes it possible to estimate the first influence taking into account only the information necessary for estimation, such as obtaining an estimation result that does not consider the influence of hearing when it is not necessary to consider the influence of hearing.

[0059] Furthermore, when multiple types of moving objects are used, the first information may be generated for each moving object, or the first information may be generated for each model of the moving object. Furthermore, the moving objects may be grouped according to size, shape, type (drone, humanoid, vehicle, etc.), and the first information may be generated for each group. Furthermore, when there are multiple estimated target ranges, the first information may be generated for each estimated target range, or the first information may be generated for each type of facility (library, hotel, office, etc.).

[0060] Furthermore, when estimating the first influence degree, the first estimation unit 13 may use facility information in addition to the first information, and for a first influence degree corresponding to a position of a moving body that is not visible to people in any position because the moving body is surrounded by fixtures, furniture, etc., the first estimation unit 13 may correct the value calculated using the first information to obtain an estimated result of the first influence degree. Specifically, for a first influence degree corresponding to a position of a moving body that is not visible to people in any position, the first estimation unit 13 may correct the first influence degree to lower the value, for example, by subtracting a determined value from the value calculated using the first information or by setting the influence degree to a minimum value.

[0061] Returning to the description of FIG. 2, the information processing device 1 estimates the second influence degree using the second information (step S2). Specifically, the second estimation unit 14 estimates the second influence degree for each estimation target of the second influence degree using the second information, and outputs the estimation result to the control processing unit 15. The estimation target is an evaluation target of the estimation target, and includes at least one of a person and an object that are the estimation target of the influence degree. The estimation target of the second influence degree may be specified by, for example, the reception unit 17 receiving an input from the operator. In addition, the acquisition unit 16 may acquire image information obtained by photographing the estimation target range and output it to the second estimation unit 14, and the second estimation unit 14 may use the image information and the above-mentioned registration information to identify a person present within the estimation target range, and the identified person may be the estimation target. In addition, the acquisition unit 16 may acquire location information indicating the location of the mobile terminal and output it to the second estimation unit 14, and the second estimation unit 14 may use the location information to identify a person corresponding to the mobile terminal present within the estimation target range, and the estimation target may be the estimation target. When the evaluation target is another moving object, the acquisition unit 16 or the control processing unit 15 may acquire position information indicating the position of the other moving object and output it to the second estimation unit 14, and the second estimation unit 14 may determine the moving object present within the estimation target range based on the position information as the estimation target. When the estimation target is an object other than a moving object, the estimation target may be determined in advance, or may be specified by the reception unit 17 receiving an input from an operator, or an object present within the estimation target range based on image information may be determined as the estimation target.

[0062] The estimation result of the second influence is, for example, information indicating the influence for each position of the estimation object in the estimation target range, that is, the distribution (planar distribution or spatial distribution) of the second influence, as with the estimation result of the first influence, but is not limited thereto and may be one or more values ​​(values ​​of the influence) according to the position of the estimation object at that time. For example, when both the first influence and the second influence are estimated as the influence, the second estimation unit 14 may output information indicating the distribution of the second influence as the estimation result. Also, for example, when only the second influence is estimated as the influence and the sound generated by the moving object is controlled, the second estimation unit 14 may output one or more values ​​according to the position of the estimation object at that time as the estimation result. Also, the second estimation unit 14 may output information indicating the distribution of the second influence to the control processing unit 15, and the control processing unit 15 may use the information indicating the distribution of the second influence during control to obtain one or more values ​​corresponding to the position of the estimation object at that time, and perform control as described later based on the obtained one or more values.

[0063] The second information, like the first information, is information calculated using data acquired by an experiment to investigate the degree of influence of a moving object, for example, and is information for estimating the second degree of influence. This experiment may be the same as the experiment conducted to calculate the first information, or may be conducted separately from the experiment to calculate the first information.

[0064] Here, an example will be described in which an experiment conducted to calculate the first information also serves as an experiment to calculate the second information. In the calculation of the first information, the first information is calculated without distinguishing between individuals. In the calculation of the second information, the second information is generated by distinguishing between individuals, that is, for each evaluation object, and when a relative position is used to obtain a distribution of the second influence degree, a person is used as the reference for the relative position instead of a moving object. Also, a distribution according to the position of the evaluation object instead of the relative position may be calculated as the second information.

[0065] For example, as the second information, a representative value for each mesh may be calculated in the same manner as the first information. In this case, the second estimation unit 14 divides the data for each evaluation object and generates the second information for each evaluation object. The second information may be a distribution indicating the second influence degree for each mesh, or may be an approximate formula, in the same manner as the first information. Also, the second information may be a trained model generated by machine learning, in the same manner as the first information. In this case, for example, the second estimation unit 14 may include a model generation unit and an inference unit, in the same manner as the first estimation unit 13 shown in FIG. 5, or a learning device including the model generation unit may be provided separately from the information processing device 1. When a learning device including the model generation unit is provided separately from the information processing device 1, the trained model generated by the learning device is stored in the information storage unit 11.

[0066] For example, the model generation unit of the second estimation unit 14 generates a trained model for each evaluation object using data corresponding to the evaluation object in the same manner as the model generation unit 131, and the inference unit of the second estimation unit 14 infers the second impact degree using the trained model corresponding to the estimation object when estimating the second impact degree. Alternatively, the model generation unit of the second estimation unit 14 may perform learning by including identification information for identifying the evaluation object in the feature amount, and the inference unit of the second estimation unit 14 may estimate the second impact degree by including identification information for identifying the estimation object in the feature amount and inputting it into the trained model.

[0067] Also, similarly to the case of estimating the first influence, the second estimation unit 14 may estimate the second influence without using a part of the estimation reference information considered when generating the second information. In the above example, the second information is generated for each evaluation object, but the evaluation objects may be grouped and the second information may be generated for each group. The index for grouping may be, for example, an attribute of the evaluation object. That is, for example, when the evaluation object is a person, the evaluation object may be grouped based on at least one of gender, age, personality, and the like, and the second information may be generated for each group. In addition, when a trained model is used as the second information, learning may be performed by including the attribute of each group in the feature, and the inference unit of the second estimation unit 14 may estimate the second influence by including the attribute of the estimation object in the feature and inputting it into the trained model.

[0068] In addition, when estimating the second influence degree, the second estimation unit 14 may correct the value calculated using the second information for the second influence degree corresponding to the position of the estimated object where the moving body is not visible due to the presence of fixtures, furniture, walls, etc. between the moving body and the person who is the estimation object, to obtain the estimation result of the second influence degree. Specifically, the second estimation unit 14 uses the position of the moving body and the position of the estimated object, and at least one of equipment information and facility information in addition to the second information to identify the estimated object corresponding to the position of the estimated object where the moving body is not visible. Then, the second estimation unit 14 may correct the second influence degree of the identified estimated object so as to reduce the value, for example, by subtracting a determined value from the value calculated using the second information, or by minimizing the second influence degree.

[0069] After step S2, the information processing device 1 judges whether or not to execute control (step S3). In detail, for example, the control processing unit 15 judges not to execute control of the control target device 2 when the degree of influence is within the range of the target degree of influence. On the other hand, the control processing unit 15 judges to execute control of the control target device 2 when the degree of influence is expected to deviate from the range of the target degree of influence within a certain time. The control of the control target device 2 is a control for changing the degree of influence. The certain time may be 0 (0 hours). That is, the control processing unit 15 may judge to execute control for changing the degree of influence when the degree of influence deviates from the range of the target degree of influence. The certain time is appropriately set based on the type of moving body, the contents of the control for changing the degree of influence, and the like. The certain time may be a control period, or may be a time longer than the control period. When the certain time is not 0, the estimation unit 12 estimates the degree of influence up to the certain time ahead. The degree of influence may be a first degree of influence, a second degree of influence, or a total degree of influence calculated by the control processing unit 15 from the first degree of influence and the second degree of influence.

[0070] The target influence degree is, for example, determined in advance and held by the control processing unit 15. Alternatively, the target influence degree may be stored in the information storage unit 11, and the control processing unit 15 may read it out from the information storage unit 11. The target influence degree may be determined according to the control reference information, as described later. That is, the control processing unit 15 may perform control based on the control reference information. For example, the target influence degree may be determined according to the surrounding information. Note that the moving object is assumed to perform an operation autonomously or by remote control, separate from the control of the influence degree. The operation of the moving object may be a task such as cleaning or transportation, or may be a conversation with a person, but is not limited to these. The details of the target influence degree will be described later.

[0071] When it is determined that control is not to be performed (step S3 No), the information processing device 1 ends the process. When it is determined that control is to be performed (step S3 Yes), the information processing device 1 controls the control target device 2 to change the degree of influence (step S4), and ends the process. In detail, the control processing unit 15 generates a control signal for changing the degree of influence so that the degree of influence becomes the target degree of influence, and transmits the generated control signal to the control target device 2. The degree of influence is changed by at least one of, for example, moving the position of the moving object, changing the volume of the moving object, displaying on a display, outputting sound from a speaker, turning on or off lighting from a lighting device, and the like.

[0072] The information processing device 1 performs the process shown in FIG. 2, for example, at every predetermined control period. This allows the information processing device 1 to grasp the presence of the moving object. Furthermore, when the degree of influence on the evaluation object deviates from the target degree of influence, the information processing device 1 controls the degree of influence on the evaluation object to be within the range of the target degree of influence. This allows the degree of influence of the moving object to be adjusted according to the situation. For example, the information processing device 1 sets the upper limit of the target degree of influence low in a situation where a person is concerned about the presence of the moving object, and sets the lower limit of the influence high in a situation where it is better for the moving object to be noticeable. This allows the information processing device 1 to lower the target degree of influence in a situation where a person is concerned about the presence of the moving object, and to raise the target degree of influence in a situation where it is better for the moving object to be noticeable.

[0073] In Fig. 2, the control of the influence degree is performed after the estimation of the first influence degree and the estimation of the second influence degree, but the control of the influence degree does not have to be performed. Even in this case, the effect of being able to grasp the presence of the moving object by estimating the influence degree can be achieved.

[0074] 2, an example has been described in which the control processing unit 15 performs control to change the degree of influence when the estimated degree of influence deviates from the target degree of influence, but the present invention is not limited to this, and the control processing unit 15 may control the control target device 2 so that the degree of influence satisfies a determined condition based on the estimated degree of influence. The determined condition may be that the degree of influence is within the range of the target degree of influence, or that the degree of influence is minimized or maximized.

[0075] A specific example of the control of the influence in the information processing device 1 will be described below. For example, the target influence may be set to a threshold value or less regardless of the situation. In this case, for example, the control processing unit 15 of the information processing device 1 uses the estimated influence to perform control to reduce the influence when the estimated influence exceeds the threshold. Examples of the control to reduce the influence include changing the position of the moving body, changing the operation mode of the moving body, changing the moving route of the moving body to move on a smooth floor surface that is less likely to generate sound, reducing the volume of the sound generated by the moving body, and controlling peripheral devices present near the moving body to direct people's attention to the peripheral devices. The type of control to be performed as the control to reduce the influence may be determined in advance or may be determined based on the above-mentioned control reference information. For example, the type of control to be performed according to the type of moving body may be determined in advance, and the control processing unit 15 may determine the content of the control based on the type of moving body. Also, for example, the type of control to be performed based on the type of behavior of the estimated object may be determined in advance, and the control processing unit 15 may estimate the behavior of the estimated object based on image information obtained by photographing the estimated object, and determine the content of the control based on the estimated behavior.

[0076] Furthermore, the control processing unit 15 of the information processing device 1 is not limited to the control of changing the degree of influence, and may control the moving object using the degree of influence. For example, when determining a route for moving the moving object, the route may be determined so as to be a route with a low degree of influence, for example, a route with a degree of influence equal to or less than a threshold value.

[0077] Also, for example, the target influence degree may be set according to facility information indicating the type of facility corresponding to the estimation target range. FIG. 6 is a diagram showing an example of the target influence degree according to facility information in this embodiment. In the example shown in FIG. 6, for example, if the facility is a library, the target influence degree is 2 or less, if the facility is a supermarket, the target influence degree is 5 or more, and if the facility is a high-end restaurant, the target influence degree is 3 or less. For example, in libraries and high-end restaurants, it is preferable for the moving object to be inconspicuous, whereas in supermarkets, it is preferable for the moving object to be conspicuous. In such a case, for example, by determining the target influence degree according to the type of facility as shown in FIG. 6, the presence of the moving object can be adjusted according to the facility.

[0078] Also, the target influence level may be set according to the surrounding information. FIG. 7 is a diagram showing an example of the target influence level according to the behavior of a person in this embodiment. In the example shown in FIG. 7, information showing the behavior of a person is used as an example of the surrounding information. In the example shown in FIG. 7, when a person in the vicinity of the moving object is working or studying, the target influence level is set low, and when the person is walking, the upper limit of the target influence level is set higher than when the person is working or studying. This makes it possible to reduce the possibility that the moving object will affect a person concentrating on work or study. For example, the control processing unit 15 can determine the behavior of a person using image information obtained by photographing a person.

[0079] Also, a target influence level may be set according to the position of the person. Fig. 8 is a diagram showing an example of a change in the position of the person 4 in this embodiment. The top row of Fig. 8 shows a state in which the person 4 present in the vicinity of the moving object 3 is sitting at a desk and working, the middle row shows a state in which the person 4 has left the desk and started walking, and the bottom row shows a state in which the person 4 has gone outside the room.

[0080] FIG. 9 is a diagram showing an example of the target influence level according to the position of the person 4 in this embodiment. In the example shown in FIG. 9, the target influence level is shown when the moving object 3 is in a room, and the target influence level is set according to whether the position of the person 4 is sitting in front of a desk, in a room away from the desk, or outside the room. For example, when the person 4 existing around the moving object is sitting in front of a desk, the person 4 is likely to be working, studying, or the like, so the target influence level is set low, and when the person 4 is in a room away from a desk, the upper limit of the target influence level is set higher than when the person 4 is sitting in front of a desk. Furthermore, when the person 4 is outside the room, the upper limit of the target influence level is set higher than when the person 4 is in a room away from a desk. As a result, for example, as shown in the upper part of FIG. 8, when the person 4 is working, the influence of the moving object 3 on the person 4 can be suppressed by lowering the target influence level. Also, for example, it is assumed that the control of the influence level includes stopping the specified operation, cleaning the room is specified as the operation of the moving object 3, and the influence level in the operation mode for cleaning the room exceeds the target influence level. In this case, the control processing unit 15 may transmit a control signal to the moving object 3 to stop the cleaning operation when the person 4 is in the room based on the degree of influence, and transmit a control signal to cancel the stop of the cleaning operation when the person 4 leaves the room. In this way, the control processing unit 15 can stop cleaning by the moving object 3 when a person is in the room, and cause the moving object 3 to perform cleaning when the person leaves the room.

[0081] Also, the target influence degree may be set according to the facility information, the surrounding information, and the attribute information. For example, when the facility information is a hotel, the position of the person 4 around the moving object 3 is a position within a certain distance from the moving object 3, and the attribute of the person 4 around the moving object 3 included in the attribute information is a guest, the target influence degree may be set to a minimum value. In this case, as a control for reducing the influence degree, it may be set to move the moving object 3 to a specified position that is not visible to the guests. In this way, the moving object 3 can be moved to a position that is not visible to the guests of the hotel. The position of the person 4 around is included in the surrounding information as described above. Also, in this example, the attribute information includes whether the person 4 is a guest, but for example, for employees other than guests, the face information described above can be registered to determine whether the person 4 is a guest or an employee. Then, for example, the acquisition unit 16 or the control processing unit 15 determines whether the person 4 is an employee based on the image information of the person 4 and the face information, and if it is determined that the person 4 is not an employee, it is determined that the person 4 is a guest.

[0082] Also, the target influence level corresponding to studying or working may be set low as in the example shown in FIG. 7, and when walking while looking at a smartphone, the target influence level may be set to a certain value or more, such as 5 or more, to increase the influence level. For example, the control processing unit 15 increases the influence level by transmitting a control signal to the moving body 3 to instruct the moving body 3 to talk to the person 4. This allows the person 4 to pay attention to the moving body 3 when walking while looking at the smartphone. Note that the control processing unit 15 may control to increase the influence level when the person 4 is looking away, not limited to the example of the person 4 walking while looking at the smartphone. That is, the control processing unit 15 may control to increase the influence level when it is determined that the person 4 is looking away based on image information obtained by photographing the surroundings of the moving body 3. For example, the control processing unit 15 may use the image information to determine the head direction, face direction, and whether or not the person 4 is walking, and may determine that the person 4 is looking away when it is determined that the head direction is the same as the walking direction but the face is facing downward.

[0083] Fig. 10 is a diagram showing an example of the actions of a plurality of people in this embodiment. For example, as shown in the upper part of Fig. 10, assume that a person 4-1 who is studying or working and a person 4-2 who is walking while looking at a smartphone are both around a moving object 3. In this case, the control of the influence degree on the person 4-1 may be prioritized, and as shown in the lower part of Fig. 10, after the person 4-2 moves away from the person 4-1, a control signal may be transmitted to the moving object 3 to generate a sound to call attention or to talk to the person 4-2.

[0084] Also, as an example of human behavior, the target influence level may be set according to the content of a person's conversation. FIG. 11 is a diagram showing an example of the target influence level according to the content of a conversation in this embodiment. As shown in FIG. 11, when a word (keyword) related to the content of work is included in the conversation, the target influence level is set low, and when a word related to leisure is included in the conversation, the upper limit of the target influence level is set higher than when a word related to the content of work is included. Also, when there is no conversation, the target influence level may be set low. Words related to the content of work are, for example, but not limited to, "business," "mass production," and "profit," and are determined in advance. Words related to leisure are also determined in advance. Note that the specific contents of the words related to the content of work and the words related to leisure may be determined according to the facility in question, or may be changeable by the operator. In this way, when a situation that becomes unsafe due to contact between the moving object 3 and the person 4 is predicted, the control processing unit 15 may perform control to increase the influence level.

[0085] Furthermore, the control processing unit 15 may grasp the position of the person according to the facility information and control the degree of influence. For example, a first degree of influence for each relative position is estimated as the degree of influence, the closer to the moving body the higher the degree of influence, the target degree of influence is set to a threshold value or less, and the facility information includes information indicating the arrangement positions of seats in the facility and seat occupancy information indicating whether or not a person is present at the seat. In such a case, the control processing unit 15 may perform control so as to reduce the total degree of influence on multiple people or objects, instead of using the target degree of influence.

[0086] FIG. 12 is a diagram showing an example of seating arrangement in this embodiment. In the example shown in FIG. 12, four seats are provided at each of six desks, A-1 to A-3 and B-1 to B-3. In FIG. 12, vacant seats are shown as outlined figures, and seats where people are seated are shown as black hatched figures. FIG. 13 is a diagram showing an example of seating information in this embodiment. In the example shown in FIG. 13, the seating information includes the number of people seated at each desk, that is, the number of people who are seated. The seating information shown in FIG. 13 corresponds to the state shown in FIG. 12. The seating information may be generated from image information captured by a photographing device, or may be generated based on reservation information indicating the reservation of seats. For example, a management device that manages a facility manages the reservation information, and the information processing device 1 acquires the reservation information from the management device. Alternatively, the acquisition unit 16 or the control processing unit 15 in the information processing device 1 may calculate the number of people seated from the image information.

[0087] In the state illustrated in Fig. 12, it is assumed that the moving body 3 is instructed to move to the destination 5 via the route R1. In such a case, the control processing unit 15 may determine that the route R2, which passes near the desk A-3 where someone is present and the three desks A-1, A-2, and B-1 where no one is present, has a lower impact on all the people present than the route R1, which passes near the three desks A-3, B-2, and B-3 where someone is present and the desk B-1 where no one is present, and transmit a control signal to the moving body 3 to instruct the route R1 to be changed to the route R2. In the example illustrated in Fig. 13, the presence information indicates the number of people present at each desk, but the presence information may indicate whether each seat is occupied or not.

[0088] The control processing unit 15 may also perform control to change the degree of influence in consideration of the line of sight of the person. FIG. 14 is a diagram for explaining the control in consideration of the line of sight of the present embodiment. For example, the control processing unit 15 may estimate the line of sight 52 of the person from image information captured by the imaging device 51, which is obtained as peripheral information, and may change the position of the moving object 3 when the moving object 3 is present in the estimated line of sight 52, thereby reducing the degree of influence on the person. The control processing unit 15 may perform this control based on the line of sight in addition to the control using the degree of influence estimated by the estimation unit 12, or may perform only this control based on the line of sight. In the example shown in FIG. 14, the moving object 3 is present on the extension line of the line of sight 52 of the person sitting at the lower left seat of the desk B-3, so the control processing unit 15 may transmit a control signal to the moving object 3 instructing it to move to the left. Also, while Figure 14 shows an example in which control is performed to prevent the moving body from entering the field of view of a seated person, this is not limited to the above, and the control processing unit 15 may control the moving body 3 so that it does not enter the field of view based on the line of sight of a person walking, standing, etc.

[0089] For example, assume that the facility is a hotel, and that the target influence level of the hotel is set low in the target influence level according to the facility information as illustrated in Fig. 6, thereby controlling the moving object 3 so as to be less noticeable to guests. Assume also that the facility information includes event information indicating a schedule of events in the lobby. In this case, during the time period when a glamorous event such as a piano performance or a lively event is being held in the lobby, the control processing unit 15 may control the moving object 3 to pass through the lobby by raising the upper limit of the target influence level.

[0090] In addition, an example of determining the target influence level for each person's behavior is shown using FIG. 7, but the person's behavior is not limited to an example in which the person is active, and may include a state such as sleeping or feeling unwell. FIG. 15 is a diagram showing another example of the target influence level according to the person's behavior in this embodiment. The person's behavior is determined by the acquisition unit 16 or the control processing unit 15 using, for example, image information. As shown in FIG. 15, for example, the target influence level may be set high, such as a target influence level for when a person has lost something being a certain value or more. This makes it easier for people to notice the lost item. Similarly, the target influence level may be set high, such as a target influence level for when a person is in poor health being a certain value or more. This makes it easier for people around them to notice that a person is in poor health. In addition, when a person is sleeping, the target influence level may be set to a threshold value or less to lower the target influence level so as not to disturb the person's sleep. In addition, when vital data can be acquired from a person's mobile terminal or the like, the determination of whether or not the person is in poor health and the determination of whether or not the person is sleeping may be performed based on vital data.

[0091] 15, the target influence level may be set high, for example, to a certain value or more when a person's behavior is suspicious. For example, by defining the contents of the control corresponding to suspicious behavior as turning on the lighting devices around the moving object 3 or turning on the lighting devices equipped in the moving object 3, having the moving object 3 talk to people, making the moving object 3 emit a sound, etc., the presence of the moving object 3 is made more noticeable, and thus it is possible to deter people who behave suspiciously.

[0092] In addition, the control processing unit 15 may generate a control signal for displaying an image on a display, which is a peripheral device, as a control for reducing the degree of influence, and transmit the generated control signal to the display. FIG. 16 is a diagram for explaining the reduction in the degree of influence by controlling the peripheral device in this embodiment. For example, when the person 4 approaches the moving object 3 by passing by it, the control processing unit 15 generates a control signal for displaying an image on the display 6 and transmits the generated control signal to the display 6 if it is expected that the degree of influence will deviate from the target degree of influence due to the person 4 approaching the moving object 3. Note that the image referred to here includes not only a still image but also a video. As a result, an image is displayed on the display 6, and the person 4 looks at the display 6, thereby reducing the degree of influence of the moving object 3 on the person 4.

[0093] The control of displaying an image on the display 6 is an example of control for changing the degree of influence, and the specific content of the control may be determined in advance by experiment, for example. For example, experiments may be performed in various cases, such as displaying an image on the display 6 or outputting a sound from a speaker, to evaluate the change in the degree of influence, and an effective measure may be determined as a control for reducing the degree of influence. Even if the same image is displayed on the display 6, whether the degree of influence of the moving object 3 changes or not may differ depending on the person 4, and the image (content of the image) that interests the person 4 may also differ. Therefore, effective control content may be determined in advance for each person 4. Content of the image to be displayed may be determined for each person 4. Instead of for each person 4, the people 4 may be grouped by attributes, and the control content, content of the image, etc. may be determined for each group. In this way, when it is determined to reduce the degree of influence based on the estimation result of the estimation unit 12, the control processing unit 15 may display an image on the display 6 and determine the image to be displayed based on the second attribute information.

[0094] Next, the hardware configuration of the information processing device 1 of this embodiment will be described. In the information processing device 1 of this embodiment, a computer program in which the processing in each of the information processing devices 1 is described is executed on a computer system, so that the computer system functions as the information processing device 1. FIG. 17 is a diagram showing an example of the configuration of a computer system that realizes each of the information processing devices 1 of this embodiment. As shown in FIG. 17, this computer system includes a control unit 101, an input unit 102, a storage unit 103, a display unit 104, a communication unit 105, and an output unit 106, which are connected via a system bus 107.

[0095] In FIG. 17, the control unit 101 is, for example, a processor such as a CPU (Central Processing Unit), and executes a program in which the processing in the information processing device 1 of the present embodiment is described. The input unit 102 is, for example, composed of a keyboard, a button, a mouse, and the like, and is used by a user of the computer system to input various information. The storage unit 103 includes various memories such as a RAM (Random Access Memory), a ROM (Read Only Memory), and a storage device such as a hard disk, and stores the program to be executed by the control unit 101, necessary data obtained in the process of processing, and the like. The storage unit 103 is also used as a temporary storage area for the program. The control unit 101 and the storage unit 103, for example, constitute a processing circuit. The processing circuit may be one circuit or multiple circuits. The display unit 104 is composed of a display, an LCD (Liquid Crystal Display), and the like, and displays various screens to the user of the computer system. Note that a touch panel in which the input unit 102 and the display unit 104 are integrated may be used. The communication unit 105 is a receiver and a transmitter that perform communication processing. The output unit 106 is a speaker or the like. Note that Fig. 17 is just an example, and the configuration of a computer system that realizes each of the information processing devices 1 is not limited to the example shown in Fig. 17. For example, the output unit 106 does not necessarily have to be provided.

[0096] Here, an example of the operation of the computer system until the program of this embodiment is in an executable state will be described. In the computer system having the above-mentioned configuration, for example, a program is installed in the storage unit 103 from a CD-ROM or DVD-ROM set in a CD (Compact Disc)-ROM drive or DVD (Digital Versatile Disc)-ROM drive (not shown). Then, when the program is executed, the program read from the storage unit 103 is stored in the main storage area of ​​the storage unit 103. In this state, the control unit 101 executes the processes as each of the information processing device 1 of this embodiment according to the program stored in the storage unit 103.

[0097] In the above description, a program describing the processing in each of the information processing devices 1 is provided using a CD-ROM or DVD-ROM as a recording medium. However, this is not limited to this, and depending on the configuration of the computer system, the capacity of the program to be provided, etc., it is also possible to use a program provided over a transmission medium such as the Internet via the communication unit 105.

[0098] The program of the present embodiment causes a computer system to execute, for example, an estimation step of estimating the degree of influence when the moving object 3 moves.

[0099] The estimation unit 12 and the control processing unit 15 shown in FIG. 1 are realized by executing a program stored in the storage unit 103 shown in FIG. 17 by the control unit 101 shown in FIG. 17. The estimation unit 12 and the control processing unit 15 are also realized by the storage unit 103. The control processing unit 15 is also realized by the communication unit 105 shown in FIG. 17. The acquisition unit 16 and the reception unit 17 shown in FIG. 1 are each realized by at least one of the input unit 102 and the communication unit 105 shown in FIG. 17. Some functions of the acquisition unit 16 may be executed by the control unit 101. The information storage unit 11 shown in FIG. 1 is a part of the storage unit 103 shown in FIG. 17. The information processing device 1 may be realized by a plurality of computer systems. For example, the information processing device 1 may be realized by a cloud computer system.

[0100] As described above, the information processing device 1 of this embodiment estimates the degree of influence when the moving body 3 moves. This makes it possible to grasp the presence of the moving body 3. Furthermore, the information processing device 1 uses the estimated degree of influence to perform control so that the degree of influence satisfies a defined condition, thereby making it possible to appropriately maintain the degree of influence of the moving body 3.

[0101] Embodiment 2 18 is a diagram showing a configuration example of an information processing system 100a according to the second embodiment. The information processing system 100a according to the present embodiment includes an information processing device 1a and a display device 7. Hereinafter, components having the same functions as those in the first embodiment are given the same reference numerals as those in the first embodiment, and duplicated explanations will be omitted. Below, differences from the first embodiment will be mainly explained.

[0102] The information processing device 1a of this embodiment is similar to the information processing device 1 of the first embodiment, except that it includes a display information generating unit 18 instead of the control processing unit 15. In this embodiment, the estimation unit 12 outputs the estimation result of the influence degree to the display information generating unit 18, and the display information generating unit 18 generates display information showing the estimation result received from the estimation unit 12 as a distribution map, and outputs the display information to the display device 7. The display information is information for displaying the estimation result of the influence degree as a distribution map on the display device 7. As a result, the display device 7 displays the distribution map of the estimated influence degree. In this embodiment, the estimation unit 12 also estimates at least one of the first influence degree and the second influence degree. The distribution map may be a distribution map on a two-dimensional plane or a distribution map in a three-dimensional space.

[0103] 19 is a flowchart showing an example of a processing procedure in the information processing device 1a of this embodiment. The information processing device 1a judges whether or not a display instruction has been received (step S11). In detail, for example, when the reception unit 17 receives an input of a display instruction from an operator or the like, or receives a display instruction from another device (not shown), it judges that a display instruction has been received. If there is no display instruction (step S11 No), the information processing device 1a repeats step S11.

[0104] When a display instruction is received (Yes in step S11), the information processing device 1a performs the processes of steps S1 and S2. Steps S1 and S2 are the same as those in the first embodiment. After step S2, the information processing device 1a generates display information (step S12). In detail, the display information generation unit 18 uses the estimation result of the impact degree received from the estimation unit 12 to generate display information showing a distribution map of the estimated impact degree.

[0105] Next, the information processing device 1a outputs the display information (step S13) and ends the process. In detail, in step S13, the display information generating unit 18 outputs the display information to the display device 7. The display device 7 may be a display, a monitor, or the like, or may be a terminal device that is a computer system. In this case, the display instruction may be transmitted from the terminal device, and the receiving unit 17 may receive the display instruction from the terminal device.

[0106] 20 to 22 are diagrams showing an example of a display screen displayed on the display device 7 of the present embodiment. In Fig. 20 to Fig. 22, the distribution of the estimated influence degree in a two-dimensional plane is shown as a contour diagram, but the display format of the distribution diagram is not limited to the examples shown in Fig. 20 to Fig. 22.

[0107] FIG. 20 shows an example in which a diagram showing a distribution 32 of the estimation result of the first influence is displayed as a distribution diagram of the estimation result of the influence. In the example shown in FIG. 20, the influence is widely distributed in the moving direction 31 of the moving body 3. For example, the influence taking into account the influence of the moving direction may be estimated by performing an experiment while changing the moving direction. Alternatively, for example, the display information generating unit 18 may generate a distribution diagram as shown in FIG. 20 by taking into account the movement from the current processing timing to the next processing timing for each processing cycle and superimposing the distribution of the influence of each time period during that period. In this case, instead of adding the influence as it is, the value of the influence may be normalized by a method such as multiplying by the time interval and adding.

[0108] Fig. 21 shows an example in which a diagram showing a distribution 41 of the estimation result of the second influence degree is displayed as a distribution diagram of the estimation result of the influence degree. In the example shown in Fig. 21, an example in which the estimation target object is a person 4 is shown.

[0109] FIG. 22 shows an example in which a diagram showing both the distribution of the estimation result of the first influence and the estimation result of the second influence is displayed as a distribution diagram of the estimation result of the influence. In the example shown in FIG. 22, the estimation target object is person 4-1, 4-2, and the second influence corresponding to person 4-1, 4-2 is displayed as distribution 41-1, 41-2. In FIG. 22, in the area 42, the distribution 41-1 of the second influence corresponding to person 4-1 and the distribution 32 of the first influence overlap. With regard to such an area, it may be displayed in a display mode corresponding to either the distribution 41-1 of the first influence or the distribution 41-2 of the second influence. That is, in the area 42, the distribution 41-1 or the distribution 41-2 may be displayed. For example, when the distributions of the first influence and the second influence overlap, which display is to be prioritized may be specified in advance, and the display may be performed based on the specification. Also, although not shown in FIG. 22, the total influence obtained by adding the first influence and the second influence may be further displayed as a numerical value or the like. For example, the total influence regarding the person 4-1 may be a value obtained by adding the value of the first influence at the position of the person 4-1 in FIG. 22 and the second influence at the position of the moving object 3. That is, for example, the total influence regarding the person 4-1 is the sum of the value at the intersection of the distribution 32 of the first influence and the position of the person 4-1, and the value at the intersection of the distribution 41-1 of the second influence regarding the person 4-1 and the position of the moving object 3. Also, the total influence regarding the person 4-2 may be a value obtained by adding the value of the first influence at the position of the person 4-2 in FIG. 22 and the second influence at the position of the moving object 3. Also, instead of adding the first influence and the second influence, the first influence and the second influence may be weighted and added. Note that the calculation information of the total influence is not limited to these examples.

[0110] The information processing device 1a of this embodiment is realized, for example, by a computer system illustrated in Fig. 17, similar to the information processing device 1 of the first embodiment. The display information generating unit 18 illustrated in Fig. 18 is realized by executing a program stored in the storage unit 103 illustrated in Fig. 17 by the control unit 101 illustrated in Fig. 17. The storage unit 103 is also used to realize the display information generating unit 18.

[0111] Note that, while FIG. 18 shows an example in which a display information generating unit 18 is provided instead of the control processing unit 15, this is not limited thereto, and a display information generating unit 18 may be added to the information processing device 1 of embodiment 1, and both the operation of embodiment 1 and the operation of this embodiment may be performed.

[0112] As described above, in this embodiment, since the estimated degree of influence is displayed as a distribution map, for example, an operator who controls the moving object 3 can visually and easily grasp the degree of influence of the moving object 3. Furthermore, when creating a movement plan, a work plan, etc. for the moving object 3, the operator can easily create a plan that takes into account the degree of influence of the moving object 3. Furthermore, the distribution map may be displayed superimposed on map information of the facility in which the moving object 3 is located. This makes it easier for the operator to determine the movement route of the moving object 3 that takes into account the degree of influence.

[0113] The configurations shown in the above embodiments are merely examples, and may be combined with other known technologies, or the embodiments may be combined with each other. Also, parts of the configurations may be omitted or modified without departing from the spirit of the invention. [Explanation of symbols]

[0114] 1,1a information processing device, 2 controlled device, 3 moving object, 4,4-1,4-2 person, 6 display, 7 display device, 11 information storage unit, 12 estimation unit, 13 first estimation unit, 14 second estimation unit, 15 control processing unit, 16 acquisition unit, 17 reception unit, 18 display information generation unit, 51 imaging device, 52 line of sight direction, 100,100a information processing system, 131 model generation unit, 132 inference unit.

Claims

1. An estimation unit that estimates the degree of influence indicating the presence of the moving object when the moving object is in motion, Based on the degree of influence, a control processing unit controls the controlled device which is at least one of the mobile body and peripheral equipment surrounding the mobile body, Equipped with, The aforementioned influence level includes a first influence level indicating the degree of influence the moving body has on its surroundings when it is in motion, and a second influence level indicating the degree of influence that a presumed object, which is at least one of a person and an object, receives from the moving body. The estimation unit estimates at least one of the first influence level and the second influence level, The information processing apparatus is characterized in that the control processing unit controls the controlled device based on the first degree of influence and the second degree of influence.

2. The estimation unit estimates the degree of influence that the estimated object receives from the moving object based on attribute information indicating the attributes of the estimated object, which is at least one of a person and an object. The information processing apparatus according to claim 1, characterized in that the control processing unit controls a control target device which is at least one of the mobile body and peripheral equipment surrounding the mobile body, based on the estimation result of the estimation unit.

3. The information processing apparatus according to claim 2, wherein the control processing unit further controls the controlled device based on surrounding information indicating the conditions around the moving object.

4. The information processing apparatus according to claim 3, characterized in that the surrounding information includes at least one of image information obtained by photographing the area around the moving object, biometric information of the person who is the estimated target object, and sound information indicating the sound around the moving object.

5. The information processing apparatus according to any one of claims 2 to 4, wherein the control processing unit further controls the controlled device based on at least one of facility information indicating the type of facility in which the mobile body is located and equipment information relating to the equipment in the facility.

6. The information processing apparatus according to any one of claims 2 to 4, characterized in that the control processing unit further controls the controlled device using the attribute information.

7. The aforementioned peripheral device includes a display, The information processing apparatus according to any one of claims 2 to 4, characterized in that the control processing unit, based on the estimation result of the estimation unit, determines to reduce the degree of influence and displays an image on the display.

8. The information processing apparatus according to any one of claims 2 to 4, characterized in that the control processing unit controls the controlled device to increase the degree of impact when a situation that would become unsafe due to contact between the moving object and a person is predicted.

9. The information processing apparatus according to claim 8, characterized in that the control processing unit controls the controlled device to increase the degree of influence when it determines, based on image information obtained by photographing the surroundings of the moving object, that a person is looking away.

10. The information processing apparatus according to claim 7, characterized in that the aforementioned image is determined based on the attribute information.

11. The estimation unit is, A first estimation unit that estimates the first degree of influence, A second estimation unit for estimating the second degree of influence, An information processing apparatus according to any one of claims 1 to 4, characterized by comprising:

12. A display information generation unit generates display information that shows the estimation results of the estimation unit as a distribution map, and outputs the display information to a display device. An information processing apparatus according to any one of claims 1 to 4, characterized by comprising:

13. The aforementioned influence level includes a first influence level indicating the degree of influence the moving body has on its surroundings when it is in motion, and a second influence level indicating the degree of influence that a presumed object, which is at least one of a person and an object, receives from the moving body. The information processing apparatus according to claim 12, characterized in that the display information generation unit generates the display information based on the first degree of influence and the second degree of influence.

14. The information processing apparatus according to claim 11, characterized in that the first estimation unit estimates the first degree of influence based on at least one of the direction of movement of the moving body and equipment information relating to the equipment in the facility where the moving body is located.

15. The information processing apparatus according to claim 11, characterized in that the first estimation unit estimates the first degree of influence based on at least one of the color, size, and operating mode of the moving object.

16. The information processing device according to claim 14, characterized in that the equipment information includes information indicating at least one of the location and shape of walls and the location and shape of roads in the facility.

17. The information processing apparatus according to claim 11, characterized in that the second estimation unit estimates the second degree of influence based on attribute information indicating the attributes of the object to be estimated.

18. An estimation unit that estimates the degree of influence indicating the presence of the moving object when the moving object is in operation, A display information generation unit generates display information that shows the estimation results of the estimation unit as a distribution map, and outputs the display information to a display device. Equipped with, The aforementioned influence level includes a first influence level indicating the degree of influence the moving body has on its surroundings when it is in motion, and a second influence level indicating the degree of influence that a presumed object, which is at least one of a person and an object, receives from the moving body. The estimation unit estimates at least one of the first influence level and the second influence level, The information processing apparatus is characterized in that the display information generation unit generates the display information based on the first degree of influence and the second degree of influence.

19. An information processing method in an information processing device, An estimation step for estimating the degree of influence indicating the presence of the moving object when the moving object is in operation, A control step of controlling a controlled device which is at least one of the mobile body and peripheral equipment surrounding the mobile body, based on the degree of influence, Includes, The aforementioned influence level includes a first influence level indicating the degree of influence the moving body has on its surroundings when it is in motion, and a second influence level indicating the degree of influence that a presumed object, which is at least one of a person and an object, receives from the moving body. In the estimation step described above, at least one of the first influence and the second influence is estimated. The information processing method is characterized in that, in the control step, the controlled device is controlled based on the first degree of influence and the second degree of influence.

20. In the computer system, An estimation step for estimating the degree of influence indicating the presence of the moving object when the moving object is in operation, A control step of controlling a controlled device which is at least one of the mobile body and peripheral equipment surrounding the mobile body, based on the degree of influence, Make it run, The aforementioned influence level includes a first influence level indicating the degree of influence the moving body has on its surroundings when it is in motion, and a second influence level indicating the degree of influence that a presumed object, which is at least one of a person and an object, receives from the moving body. In the estimation step described above, at least one of the first influence and the second influence is estimated. The program is characterized in that, in the control step, the controlled device is controlled based on the first degree of influence and the second degree of influence.

Images