JP2019000940A - Robot control system, platform, robot, and method of controlling robot - Google Patents

Abstract

To positively make good use of a robot while preventing an influence on a site where service is provided.SOLUTION: A robot control system comprises: an autonomously movable robot which provides service for a person in a service provision area; and a platform which communicates with the robot, stores congestion history information as information representing a degree of congestion in every past predetermined time in the service providing area, and then generates, based upon the congestion history information, congestion prediction information as information generated by predicting a degree of congestion for each predetermined time. The robot sets itself to one of a plurality of operation modes, differing in influence on the degree of congestion in the service providing area, which is selected according to the present or future degree of congestion of the service providing area acquired from the congestion prediction information.SELECTED DRAWING: Figure 5

Description

  The present invention relates to a robot control system, a platform, a robot, and a robot control method.

  In Patent Document 1, “the robot system recognizes whether or not a person is looking at an exhibit or a guide board, whether it is waiting for viewing, etc., and the robot provides a guidance service at an appropriate timing”. “In a robot guidance system that includes one or more cameras that capture one or more humans and a mobile robot that guides humans, a position calculation device that calculates the human position, and measures the time during which the human stayed in a predetermined area. An area stay time measuring device, a behavior identification device for identifying human behavior content, and a robot control platform for controlling a robot based on a behavior identification result by the behavior identification device, and placing an article in an article peripheral region A first area in contact with the area and a second area in contact with the first area are defined, the camera tracks a person, and the mobile robot stays in the first and second areas or A guidance to a human to stop "that have been described.

  Patent Document 2 states that “adults, dwarfs, infants, etc. are detected based on the height and face height of the customer when the robot visits the store, etc., and the degree of congestion is detected. “Selected (or created) from the table, displayed, uttered voice, expressed in gesture, and moved further for efficient explanation and guidance”.

  Patent Document 3 states that “one or more robots arranged in a space, a robot router for controlling the robot, state management of the robot in the space, and collecting environmental information in the space. A network robot service system in which a space manager to be managed is connected by a communication network, and is stored in the robot router in any space where the robot router has a user attribute and a means for holding the user attribute. And a means for providing a service based on user attributes and environmental information. "

  Patent Document 4 states that “in a service robot system for providing services to a person, the robot system includes one or more robots that can move autonomously, and a plurality of service target persons around the robots correspond to the robots. A position identification device capable of simultaneously identifying the positional relationship is provided, and the robot performs service for the service target person using the positional relationship information identified by the position identification device as service operation control information. Is described.

JP 2007-152442 A JP 2008-55578 A JP 2005-1111637 A JP 2005-329515 A

With the advancement of IT infrastructure technology and artificial intelligence (AI technology) related technology, research / development of robots that provide advanced interpersonal services while moving autonomously is underway. Here, in the practical application of robots that perform interpersonal services while moving autonomously, the robots actively engage in interpersonal services while preventing the robot's impact on the site according to changes in the environment where the robots perform interpersonal services. It is required to be able to provide.

  As an example, a robot (for example, a humanoid robot) that provides interpersonal services (such as route guidance, facility introduction, interpretation, etc.) to passers-by in a service provision area such as a floor of a commercial facility or a concourse is taken up. For example, if the robot enters the lunch time zone while providing interpersonal services in the middle of the service provision area, and the service provision area suddenly starts to become crowded, the robot cannot move. You may get stuck. In this case, the robot cannot efficiently provide the interpersonal service, and it becomes an obstacle to traffic and causes congestion and traffic congestion in the service providing area.

  In order to avoid such a situation here, for example, it may be possible to predict the congestion in advance and restrict the robot's movement (action or movement). However, if the robot movement is restricted more than necessary, The operating rate will decrease. Therefore, it is desirable to predict the time when the robot operation is restricted as accurately as possible, but the situation on the site changes depending on various factors such as the time of day, day of the week, season, climate, site characteristics, etc. Proper restriction is not always easy.

  The present invention has been made in view of such a background, and the robot control system, the platform, the robot, and the robot that can actively use the robot while preventing the influence on the site where the service is provided are provided. An object is to provide a control method.

  One aspect of the present invention for achieving the above object is a robot control system, which shows a degree of congestion at a predetermined time interval in a service providing area in which a robot capable of autonomous movement provides an interpersonal service. An information storage unit that stores congestion history information that is information, a congestion status prediction unit that generates congestion prediction information that is information that predicts the degree of congestion for each predetermined time of the service providing area based on the congestion history information, and The operation mode is selected from the current or future congestion level of the service providing area acquired from the congestion prediction information, and the operation mode is any one of a plurality of operation modes having different effects on the congestion level of the service providing area. An operation mode setting unit for setting the robot.

  In addition, the subject which this application discloses, and its solution method are clarified by the column of the form for inventing, and drawing.

  ADVANTAGE OF THE INVENTION According to this invention, a robot can be actively utilized, preventing the influence which the service provision is performed on.

It is a figure which shows the schematic structure of a robot control system. It is a figure which shows the main hardware with which a robot is provided. It is a figure which shows the main functions with which a robot is provided. It is a figure which shows the main hardware with which a platform is provided. It is a figure which shows the main functions with which a platform is provided. It is an example of congestion history information. It is an example of congestion prediction information. It is a figure explaining "search mode". It is a figure explaining "remote mode". It is a figure explaining "standby mode". It is a figure explaining the outline | summary of the process regarding the setting of an operation mode. It is a flowchart explaining a congestion prediction information generation process. It is a flowchart explaining an operation mode setting process (present). It is a flowchart explaining an operation mode setting process (future). It is a flowchart explaining the operation mode setting process (present and future).

  In the following, autonomous movement that provides services (passage guidance, facility introduction, interpretation, etc., hereinafter also referred to as interpersonal services) to people such as passersby in service provision areas such as floors and concourses in commercial facilities, etc. A control system of a possible robot (personal service providing apparatus) will be described as an embodiment. In the following description, the same or similar components may be omitted by using the same reference numerals.

  FIG. 1 shows a schematic configuration of the robot control system (hereinafter referred to as a robot control system 1). As shown in the figure, the robot control system 1 includes one or more robots 10, a robot platform (hereinafter referred to as a platform 20), and a congestion status sensor 30.

The robot 10 is a robot (such as a humanoid robot) that provides an interpersonal service while autonomously moving in the service providing area 2. The robot 10 communicates with the platform 20 as needed, and transmits and receives information used for monitoring and control of the robot 10 to and from the platform 20. For example, the robot 10 can respond to provision of various interpersonal services by setting configuration information for the robot 10 itself and the platform 20. For example, the robot 10 can detect the motion of the person 3, determine a service to be provided according to the detected result, and provide the determined service to the person 3. The robot 10 may be realized, for example, by hardware or software provided in the robot 10 itself, or all or part of its functions may be realized by the platform 20. It may be.

  The platform 20 communicates with one or more robots 10 existing in the service providing area 2 to monitor and control the robots 10. The platform 20 is realized using, for example, an information processing apparatus (computer), a cloud server in a cloud system, or the like. For example, the platform 20 may have a function of communicating with an information processing apparatus provided at a remote location via the Internet or the like. In addition, the platform 20 may provide a monitoring control function of the robot 10 in cooperation with an information processing service related to artificial intelligence realized using a cloud system or the like.

The congestion status sensor 30 provides the platform 20 with information for grasping the status in the service providing area 2 and the congestion status around the robot 10 (hereinafter also referred to as the degree of congestion). The congestion state sensor 30 includes, for example, a camera, a time of flight (TOF) camera, a stereo camera, a laser radar (LIDAR: Laser Imaging Detection and Ranging), a millimeter wave radar, an infrared depth sensor, an ultrasonic sensor, and the like. Constructed using. Note that, for example, an environmental camera installed in advance in the service providing area 2 or in the vicinity thereof may be used as the congestion status sensor 30. Moreover, it is good also as a structure which the platform 20 grasps | ascertains the congestion condition of the service provision area 2 using the radio signal transmitted, for example from portable communication terminals, such as a smart phone.

FIG. 2 shows main hardware included in the robot 10. As shown in the figure, the robot 10 includes a processor 11, a storage device 12, a communication device 13, an input / output interface (hereinafter referred to as an input / output I / F 14), various sensors 15, an operation control device 16, and a movement control device. 17 and a timing device 18.

  The processor 11 is configured using, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a DSP (Digital Signal Processor), a GPU (Graphics Processing Unit), and the like.

  The storage device 12 is, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a nonvolatile memory (NVRAM (Non Volatile RAM)), a hard disk drive, an SSD (Solid State Drive), or the like.

  The communication device 13 is a wireless (or wired) communication interface that realizes bidirectional communication with the platform 20, and is configured using, for example, a wireless communication module or a NIC (Network Interface Card).

  The input / output I / F 14 includes an input interface that receives input of information from the outside and an output interface that provides information to the outside. The input interface, for example, receives information sent from various sensors 15, accepts input from a user interface such as a touch sensor, and recording medium (nonvolatile memory, optical recording medium, magnetic recording medium, magneto-optical recording medium) Etc.). For example, the input / output I / F 14 reads the configuration information described above from the recording medium. The output interface is, for example, a speaker, an LED (Light Emitting Diode), a screen display device (liquid crystal display, projector, etc.), a printing device, a data recording device on a recording medium, or the like.

The various sensors 15 are, for example, a microphone, an optical sensor, a camera, an acceleration sensor, a gyro sensor, a gravity sensor, a magnetic sensor, a GPS sensor (GPS: Global Positioning System).
) Etc. The microphone is used, for example, for acquiring a human voice. An optical sensor and a camera are used, for example, for acquiring information related to human behavior and actions. The acceleration sensor and the gyro sensor are used for grasping the posture of the robot 10, for example. The GPS sensor is used for grasping the current position of the robot 10, for example.

The motion control device 16 includes a control circuit (servo motor, actuator) for controlling the motion of the robot 10 (movements of limbs and joints, facial expressions, speech, etc.) and mechanical parts (gear mechanism, link mechanism, etc.). The movement control device 17 includes a drive circuit (such as a motor drive circuit) and a drive mechanism (such as a motor, a servo motor, and a gear mechanism) for moving the robot 10.

The time measuring device 18 is configured using, for example, an RTC (Real Time Clock), and generates information related to time such as the current date and time. Note that the robot 10 may acquire information on time such as the current date and time from an external device such as an NTP server (NTP: Network Time Protocol) on the Internet.

  FIG. 3 shows main functions of the robot 10. As shown in the figure, the robot 10 includes an information storage unit 110, a communication processing unit 111, an operation control unit 112, a movement control unit 113, a service providing unit 114, a congestion prediction information receiving unit 115, an operation mode setting unit 116, and Each function of the human motion recognition unit 117 is provided.

  The information storage unit 110 stores information such as service information 151, congestion prediction information 152, and operation mode information 153.

  The service information 151 includes information for realizing a service provided by the robot 10 (for example, information regarding the operation of the robot 10 when providing a service or information output to a display device or the like when providing a service).

  The congestion prediction information 152 includes information based on the congestion prediction information 252 acquired by the robot 10 from the platform 20.

  The operation mode information 153 includes information for specifying the type of operation mode (“standby mode”, “remote mode”, “search mode”) to be described later of the robot 10.

  The communication processing unit 111 transmits various information to the platform 20 and receives various information (control command, mode information, etc.) from the platform 20.

  The operation control unit 112 controls the operation of the robot 10. Note that the operation control unit 112 controls the operation of the robot 10 according to the content of the operation mode information 153, for example. The movement control unit 113 controls the movement of the robot 10. The movement control unit 113 controls the movement of the robot 10 according to the contents of the operation mode information 153, for example. The operation control unit 112 and the movement control unit 113 perform control related to the autonomous movement of the robot 10.

  The service providing unit 114 controls the operation control unit 112 and the movement control unit 113 to perform processing related to provision of interpersonal services by the robot 10. For example, the service providing unit 114 performs processing related to provision of interpersonal services according to the configuration information described above.

  The congestion prediction information receiving unit 115 communicates with the platform 20 to receive the contents of congestion prediction information 252 described later as needed, and stores the acquired contents as congestion prediction information 152.

  The operation mode setting unit 116 is selected according to the congestion degree of the current or future service provision area 2 acquired from the congestion prediction information 152 and has a plurality of operation modes having different influences on the congestion degree of the service provision area 2. The robot 10 is set to one of the operation modes. The operation mode setting unit 116 stores information indicating the operation mode currently set for the robot 10 as the operation mode information 153.

  The person action recognition unit 117 recognizes the action of the person 3 existing in the service providing area 2 (the action or movement of the person 3). The person motion recognition unit 117 recognizes the action and motion of the person 3 using, for example, a known image recognition technology or video recognition technology. The result recognized by the human motion recognition unit 117 is used, for example, for providing an interpersonal service by the service providing unit 114, controlling the operation of the robot 10 by the operation control unit 112, and controlling the movement of the robot 10 by the movement control unit 113.

  FIG. 4 shows main hardware included in the platform 20. As shown in the figure, the platform 20 includes a processor 21, a storage device 22, a communication device 23, an input / output interface (hereinafter referred to as an input / output I / F 24), and a timing device 25. Note that all or part of the hardware of the platform 20 may be realized by a cloud server in a cloud system, for example.

  The processor 21 is configured using a CPU, MPU, DSP, GPU or the like. The storage device 22 is a ROM, RAM, nonvolatile memory, hard disk drive, SSD, or the like.

The communication device 23 includes a wireless (or wired) communication interface that realizes communication with the robot 10 and the congestion status sensor 30. The communication device 23 may have a function of connecting to the Internet. The communication device 23 is, for example, a wireless communication module, NIC
(Network Interface Card), USB module (USB: Universal Serial Bus), serial communication module, and the like.

  The input / output I / F 24 is an input interface (touch panel, keyboard, mouse, recording medium (nonvolatile memory, optical recording medium, magnetic recording medium, magneto-optical recording medium, etc.) for receiving input of information from the user or other devices. As well as an output interface (liquid crystal display, printing device, data recording device on a recording medium, etc.) for providing information to the user and other devices. For example, the input / output I / F 24 reads the configuration information described above from the recording medium.

  The time measuring device 25 is configured using, for example, an RTC, and generates information related to time such as the current date and time. Note that the platform 20 may acquire information on time such as the current date and time from an external device such as an NTP server on the Internet, for example.

  FIG. 5 shows the main functions of the platform 20. As shown in the figure, the platform 20 includes functions of an information storage unit 210, a communication processing unit 211, and a congestion status prediction unit 212.

The information storage unit 210 stores information such as congestion history information 251 and congestion prediction information 252.
Among them, the congestion history information 251 is the time of the service providing area 2 detected by the congestion state prediction unit 212 based on data (for example, video data or image data; hereinafter referred to as sensor data) acquired from the congestion state sensor 30. Information on the history of congestion status (degree of congestion) for each is included. The congestion prediction information 252 includes information indicating the congestion status (congestion degree) for each time of the service providing area 2 predicted by the congestion status prediction unit 212 based on the congestion history information 251.

  The communication processing unit 211 transmits various information (control command, congestion prediction information, etc.) to the robot 10 and receives various information (position information, service status, monitoring information, etc.) from the robot 10.

  The congestion state prediction unit 212 generates the congestion prediction information 252 based on the sensor data received from the congestion state sensor 30 by the communication processing unit 211. As shown in the figure, the congestion status prediction unit 212 includes a congestion history information generation unit 2121, a statistical processing unit 2122, and a prediction information generation unit 2123.

  Among these, the congestion history information generation unit 2121 generates the congestion history information 251 based on the sensor data received from the congestion status sensor 30. The congestion history information generation unit 2121 determines the congestion status (congestion degree) every predetermined time in the service providing area 2 and registers it in the congestion history information 251. Note that the congestion history information generation unit 2121 performs, for example, video analysis (video recognition), image analysis (image recognition), person recognition, moving object detection, and the like on the sensor data, and the congestion status of the service providing area 2 every predetermined time. (Congestion degree) is determined. In addition, the congestion history information generation unit 2121 determines the degree of congestion based on image data sent from a camera functioning as the congestion state sensor 30, as described in, for example, Patent Document 2 (Japanese Patent Laid-Open No. 2008-55578). The congestion status (degree of congestion) of the service providing area 2 is determined every predetermined time.

An example of the congestion history information 251 is shown in FIG. As shown in the figure, the congestion history information 251 is composed of a plurality of records including items of a date 2511, a day of the week 2512, a time 2513, and a congestion state 2514. Each record corresponds to the date and time specified by the date 2511, the day of the week 2512, and the time 2513. In this example, the time interval between adjacent (continuous) records (difference between adjacent record time 2513) is 1 hour. However, the time interval is not necessarily limited. For example, the time interval is shorter than 1 hour. A longer time interval may be used.

  In the congestion status 2514, information indicating the congestion status of the service providing area 2 determined by the congestion status prediction unit 212 based on the sensor data acquired by the congestion status sensor 30 at the date and time of the record is set. In this example, the congestion status 2514 includes “congestion” indicating that the service providing area 2 is congested, “normal” indicating that the service providing area 2 is normally congested, and the service providing area 2 One of “quiet” indicating that it is vacant (including unmanned cases) is set.

  Returning to FIG. 5, the statistical processing unit 2122 aggregates the contents of the congestion history information 251 every predetermined time (statistical processing) as preparation for statistically predicting the congestion situation, and the aggregated result is the congestion prediction information. 252 is registered. In this example, the statistical processing unit 2122 counts the contents of the congestion history information 251 for each day of the week and for each hour, but the counting method is not necessarily limited.

  An example of the congestion prediction information 252 is shown in FIG. As shown in the figure, the congestion prediction information 252 includes a plurality of records each having items of a day of the week 2521, a time 2522, statistical information 2523, and a congestion state (prediction) 2526. As shown in the figure, the statistical information 2523 includes three items of congestion, normal, and quiet. For each of these items, a value (result of statistical processing) obtained by counting the number of appearances in the congestion status 2514 of the congestion history information 251 of each item is set.

  Referring back to FIG. 5, the prediction information generation unit 2123 of the congestion state prediction unit 212 predicts the congestion state for each predetermined time in the service providing area 2 based on the statistical information 2523 of the congestion prediction information 252 and predicts the predicted result as a congestion prediction. Information 252 is set in the congestion status (prediction) 2526. In the example of FIG. 7, “congestion” indicating that the service providing area 2 is congested in the congestion status (prediction) 2526, “normal” indicating that the service providing area 2 is normally congested, and Any one of “quiet” indicating that the service providing area 2 is vacant (including an unmanned case) is set.

[Operation mode]
Next, the operation mode described above will be described. The robot 10 can set an operation mode that is a mode that defines the operation mode of the robot 10 in the service providing area 2. In this example, it is assumed that three operation modes (“standby mode”, “remote mode”, and “search mode”) described below can be set in the robot 10. In this example, three operation modes can be set as described above, but two operation modes or four or more operation modes may be set in the robot 10.

FIG. 8 is a diagram for explaining the “search mode” among the operation modes. The “search mode” is set in the robot 10 when, for example, the service providing area 2 is not congested (hereinafter referred to as a quiet time). In addition, it includes a time when there is no person 3 in the service providing area 2 when there is no time (unmanned). As shown in the figure, when the “search mode” is set, the robot 10 moves within the service providing area 2 (for example, autonomously moves at random), and the person 3 moves within a predetermined distance from the robot 10 during the movement. When approaching, the person 3 starts an interpersonal service. As described above, in the “search mode”, the robot 10 moves in the service providing area 2 and searches for a person to whom the interpersonal service is provided, so that the robot 10 can be actively used.

FIG. 9 is a diagram for explaining the “remote mode” among the operation modes. The “remote mode” is set in the robot 10 when, for example, the service providing area 2 is more congested than when it is quiet, but is not congested compared to the congested time described below (hereinafter referred to as normal). As shown in the figure, when the “remote mode” is set, the robot 10 is in a standby area 90 which is an area narrower than the service providing area 2 in the service providing area 2 except when providing the interpersonal service. Only when providing the interpersonal service, the mobile station moves to the vicinity of the person 3 and performs the interpersonal service. For example, when the service providing area 2 is a passage, the standby area 90 is set to a place that is unlikely to obstruct the passage of the person 3 such as near the end of the passage. When waiting in the waiting area 90, the human motion recognition unit 117 of the robot 10 monitors the person 3 existing in the service providing area 2. When it is detected that the person 3 existing in the service providing area 2 has performed a predetermined action (for example, a gesture overlooking the surroundings or an action of looking at a map), the robot 10 moves close to the person 3. Go and provide interpersonal services. Note that after the interpersonal service is completed, the robot 10 returns to the standby area 90 and resumes monitoring the person 3 existing in the service providing area 2. As described above, in the “remote mode”, the robot 10 is waiting in the standby area 90 except when providing the interpersonal service, so that it is possible to prevent the traffic from being obstructed. Further, when the interpersonal service is required, the robot 10 can be used effectively because the interpersonal service is provided by moving to the vicinity of the person 3.

  FIG. 10 is a diagram for explaining the “standby mode” among the operation modes. In the “standby mode”, for example, when the service providing area 2 is more congested than usual and there is a high possibility that the presence of the robot 10 will hinder traffic (hereinafter referred to as a congested time), the robot 10 is in a “standby mode”. Is set. As shown in the figure, when the “standby mode” is set, the robot 10 stays in the standby area 90 which is a narrower area in the service providing area 2 than the service providing area 2 (in the case of emergency etc. In the case of a special situation, it may be possible to move out of the waiting area 90). When the robot 10 detects that the person 3 has approached within a predetermined range from itself, the robot 10 provides an interpersonal service to the person 3. As described above, in the “standby mode”, the robot 10 stays in the standby area 90, so that it can be surely prevented from obstructing passage. Further, when the person 3 approaches, an interpersonal service is provided so that the robot 10 can be used effectively.

[Operation mode setting process]
FIG. 11 is a diagram for explaining an overview of processing related to setting of the operation mode performed in the robot control system 1. In the following, the outline of the processing related to the operation mode setting will be described with reference to FIG.

  As shown in the figure, the communication processing unit 211 of the platform 20 receives the sensor data sent from the congestion state sensor 30 and inputs it to the congestion state prediction unit 212 of the platform 20 (S1111 and S1112).

  The congestion history information generation unit 2121 of the congestion status prediction unit 212 generates the congestion history information 251 based on the input sensor data (S1113).

  Subsequently, the statistical processing unit 2122 of the congestion status prediction unit 212 totals (statistical processing) the contents of the congestion history information 251 every predetermined time, and registers the totaled result in the congestion prediction information 252. (S1114).

  Subsequently, based on the statistical information 2523, the prediction information generation unit 2123 of the congestion state prediction unit 212 predicts the hourly congestion state of the service providing area 2, and the predicted result indicates the congestion state (prediction) of the congestion prediction information 252. Set to 2526.

  The platform 20 repeatedly performs the above processing, whereby the contents of the congestion history information 251 and the congestion prediction information 252 are updated as needed.

The robot 10 accesses the platform 20 and updates the latest congestion prediction information 252 at any time.
Is acquired and stored as congestion prediction information 152 (S1116), and its own operation mode is set based on the content of congestion prediction information 152 (S1117).

[Congestion prediction information generation processing]
FIG. 12 is a flowchart for explaining details of the processing of S1114 and S1115 of FIG. 11 (hereinafter referred to as congestion prediction information generation processing S1200). Hereinafter, the congestion prediction information generation process S1200 will be described with reference to FIG.

  As shown in the figure, first, the statistical processing unit 2122 of the congestion status prediction unit 212 generates statistical information 2523 based on the congestion history information 251 and registers it in the congestion prediction information 252 (S1211).

  Subsequently, based on the statistical information 2523, the prediction information generation unit 2123 of the congestion status prediction unit 212 determines the degree of congestion of each record of the congestion prediction information 252 (hereinafter referred to as congestion degree).

  As shown in the figure, first, the prediction information generation unit 2123 selects one record of the congestion prediction information 252 (S1212).

The prediction information generation unit 2123 has an index of congestion status (degree of congestion) obtained from the statistical information 2523 of the selected record (hereinafter referred to as a congestion index. The value of the congestion index increases as the congestion increases). If the preset first threshold value is exceeded (S1213: YES), the congestion level of the record is determined as “congested” (S1214). Thereafter, the process proceeds to S1220. Note that the congestion index is obtained, for example, by performing calculation based on the following equation for the statistical information 2523 for each record. In the following equation, “congestion value”, “normal value”, and “low value” correspond to the “crowded” value, “normal” value, and “low” value in the statistical information 2523, respectively. .
Congestion index = Congestion value / (Congestion value + Normal value + Leisure value) ・ ・ ・ Equation 1

  The prediction information generation unit 2123 also determines that the congestion index of the record being selected is equal to or less than a preset first threshold value and exceeds a preset second threshold value (S1213: NO, S1215: YES). ), The congestion degree of the record is determined to be “normal” (S1216). Thereafter, the process proceeds to S1220.

  Further, when the congestion index of the selected record is equal to or less than the second threshold value set in advance (S1215: NO), the prediction information generation unit 2123 determines that the congestion level of the record is “free” (S1217). Thereafter, the process proceeds to S1220.

  In S1220, the prediction information generation unit 2123 sets the determination result as described above in the congestion status (prediction) 2526 of the corresponding record of the congestion prediction information 252.

  Subsequently, the prediction information generation unit 2123 determines whether or not all the records of the congestion prediction information 252 have been selected in S1212 (S1221). If all the records have not been selected (S1221: NO), the process returns to S1212. If all the records have been selected (S1221: YES), the congestion prediction information generation process S1200 ends.

The congestion index, the first threshold value, and the second threshold value can be set in various ways. For example, in S1213 of FIG. 12, for example, when the congestion value of the statistical information 2523 is equal to or greater than a predetermined number of times (for example, once) (S1213: YES), the congestion degree is determined as “congested” (S1214). Also good. In S1215 of FIG. 12, for example, if the normal value of the statistical information 2523 is equal to or greater than a predetermined number of times (for example, once), it is determined as “normal” (S1216), and otherwise is determined as “low” (S1217) You may do it.

[Operation mode setting (current)]
FIG. 13 is a flowchart for explaining the processing of S1116 and S1117 of FIG. 11 (hereinafter referred to as operation mode setting processing (current) S1300). The operation mode setting process (current) S1300 will be described below with reference to FIG.

  As shown in the figure, the robot 10 determines in real time whether or not the timing for setting the operation mode has arrived (S1311: NO). The timing for setting the operation mode comes, for example, when a preset time arrives or at predetermined time intervals. When the timing for setting the operation mode arrives (S1311: YES), the process proceeds to S1312.

  In S1312, the robot 10 accesses the platform 20, and corresponds to the current date and time in the current congestion status of the service providing area 2, that is, the congestion prediction information 252, from the congestion prediction information 252 stored in the platform 20 (or The congestion status (prediction) 2526 associated with the day of the week 2521 and the time 2522 is acquired (received).

  Subsequently, the robot 10 determines whether or not the content of the acquired (received) congestion status (prediction) 2526 is “congested” (S1313). When the content of the acquired congestion status (prediction) 2526 is “congested” (S1313: YES), the robot 10 sets the operation mode to “standby mode” (S1314). Thereafter, the process returns to S1311. On the other hand, if the content of the acquired congestion status (prediction) 2526 is not “congested” (S1313: NO), the process proceeds to S1315.

  In S1315, the robot 10 determines whether or not the content of the acquired (received) congestion status (prediction) 2526 is “normal”. When the content of the acquired congestion status (prediction) 2526 is “normal” (S1315: YES), the robot 10 sets the operation mode to “remote mode” (S1316). Thereafter, the process returns to S1311. On the other hand, when the content of the acquired congestion status (prediction) 2526 is not “normal” (S1315: NO), the process proceeds to S1317.

  In S1317, the robot 10 sets the operation mode to “search mode”. Thereafter, the process returns to S1311.

  As described above, the robot 10 appropriately sets the operation mode according to the current congestion state of the service providing area 2 acquired from the congestion prediction information 252, while reliably preventing the passage of traffic. The robot 10 can be actively used effectively.

[Operation mode setting (future)]
In the operation mode setting process (current) S1300 in FIG. 13, the robot 10 sets the operation mode according to the current congestion state of the service providing area 2 acquired from the congestion prediction information 252. The operation mode may be set according to the congestion status of the service providing area 2 that is acquired from the congestion prediction information 252 and is in the future (predetermined time ahead) from the present.

FIG. 14 shows the case where the robot 10 sets the operation mode according to the congestion status of the service providing area 2 in the future (predetermined time ahead) from the current time acquired from the congestion prediction information 252. It is a flowchart explaining the process of S1116 and S1117 (hereinafter, referred to as operation mode setting process (future) S1400). As shown in the figure, the flow of the operation mode setting process (future) S1400 acquires (receives) the congestion status of the future service providing area 2 from the congestion prediction information 252 in S1412, and determines this in S1413 and S1415. Except for this point, the operation mode setting process (current) S1300 shown in FIG. It should be noted that in the acquisition (reception) of the future service provision area 2 in S1412, the robot 10 receives the congestion state (corresponding to the day of the week 2521 and the time 2522 corresponding to the time point of the future for a predetermined time from the current date and time ( Prediction) 2526 is acquired (received). More specifically, for example, the robot 10 acquires the congestion status (prediction) 2526 of the record next to the record corresponding to the current date and time of the congestion prediction information 252 (the record corresponding to the current day of the week 2521 and the time 2522) ( Receive).

  As described above, the robot 10 appropriately sets the operation mode in advance according to the future congestion situation of the service providing area 2 acquired from the congestion prediction information 252, so that it is possible to obstruct traffic. The robot 10 can be used effectively and effectively while preventing it.

[Operation mode setting (current and future)]
FIG. 15 is a flowchart for explaining another example of the processing of S1116 and S1117 of FIG. 11 (hereinafter referred to as operation mode setting processing (current and future) S1500). In operation mode setting processing (current and future) S1500, the robot 10 sets an operation mode according to the current and future congestion status acquired from the congestion prediction information 252. The operation mode setting process (current and future) S1500 will be described below with reference to FIG.

  As shown in the figure, the robot 10 determines in real time whether or not the timing for setting the operation mode has arrived (S1511: NO). The timing for setting the operation mode comes, for example, when a preset time arrives or at predetermined time intervals. When the timing for setting the operation mode comes (S1511: YES), the process proceeds to S1512.

  In S1512, the robot 10 communicates with the platform 20, and the current day of the week corresponding to the current date and time in the current congestion status of the service providing area 2 from the congestion prediction information 252 stored in the platform 20, that is, the congestion prediction information 252, is displayed. The congestion status (prediction) 2526 associated with 2521 and time 2522 is acquired (received).

  Subsequently, the robot 10 determines whether or not the content of the acquired (received) congestion status (prediction) 2526 is “congested” (S1513). When the content of the acquired congestion status (prediction) 2526 is “congested” (S1513: YES), the robot 10 sets the operation mode to “standby mode” (S1514). Thereafter, the process returns to S1511. On the other hand, if the acquired (received) congestion status (prediction) 2526 is not “congested” (S1513: NO), the process proceeds to S1515.

  In S1515, the robot 10 accesses the platform 20, and in the future congestion situation of the service providing area 2 from the congestion prediction information 252 stored in the platform 20, that is, in the congestion prediction information 252, a future time of a predetermined time from the current date and time. The congestion status (prediction) 2526 associated with the day of the week 2521 and the time 2522 corresponding to the time is acquired (received). For example, the robot 10 acquires (receives) the congestion status (prediction) 2526 of the record next to the record corresponding to the current date and time of the congestion prediction information 252 (the record corresponding to the current day of the week 2521 and the time 2522).

Subsequently, the robot 10 acquires the future congestion status (prediction) 25 acquired (received) in S1515.
It is determined whether or not the content of 26 is “congested” (S1516). If the acquired (received) congestion status (prediction) 2526 is “congested” (S1516: YES), the robot 10 sets the operation mode to “standby mode” (S1514). Thereafter, the process returns to S1511. On the other hand, if the acquired (received) congestion status (prediction) 2526 is not “congested” (S1516: NO), the process proceeds to S1517.

  In S1517, the robot 10 determines whether or not the content of the future congestion status (prediction) 2526 acquired (received) in S1515 is “normal”. If the acquired (received) congestion status (prediction) 2526 is “normal” (S1517: YES), the robot 10 sets the operation mode to “remote mode” (S1518). Thereafter, the process returns to S1511. On the other hand, if the acquired (received) congestion status (prediction) 2526 is not “normal” (S1517: NO), the process proceeds to S1519.

  In S1519, the robot 10 sets the operation mode to “search mode”. Thereafter, the process returns to S1511.

  As described above, the robot 10 considers the future congestion situation in addition to the current congestion situation, and if the future congestion situation is “congestion” even if the current congestion situation is not “congestion”, the operation mode Is set to “standby mode”, so that it is possible to prevent the robot 10 from obstructing passage in advance. In addition, the robot 10 can provide interpersonal services to the extent that it does not hinder traffic during normal times, and the robot 10 can actively provide interpersonal services in off-peak hours.

  By the way, it goes without saying that the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the scope of the invention. For example, the above embodiment has been described in detail for easy understanding of the present invention, and is not necessarily limited to the one having all the configurations described. In addition, it is possible to add, delete, and replace other configurations for a part of the configuration of the above embodiment.

Each of the above-described configurations, function units, processing units, processing means, and the like may be realized in hardware by designing some or all of them, for example, with an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by the processor interpreting and executing a program that realizes each function. Information such as programs, tables, and files for realizing each function can be stored in a recording device such as a memory, a hard disk, or an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

  Further, in each of the above drawings, control lines and information lines indicate what is considered necessary for explanation, and not all control lines and information lines on the mounting are necessarily shown. For example, it may be considered that almost all configurations are actually connected to each other.

  Moreover, the arrangement | positioning form of the various function parts of the robot control system 1 demonstrated above, various process parts, and various databases is only an example. The arrangement form of the various function units, the various processing units, and the various databases can be changed to an optimum arrangement form from the viewpoint of the performance of hardware and software provided in the robot control system 1, processing efficiency, communication efficiency, and the like.

  The database configuration (schema) described above can be flexibly changed from the viewpoints of efficient use of resources, improvement of processing efficiency, improvement of access efficiency, improvement of search efficiency, and the like.

DESCRIPTION OF SYMBOLS 1 Robot control system, 2 Service provision area, 10 Robot, 110 Information storage part, 111 Communication processing part, 114 Service provision part, 115 Congestion prediction information receiving part, 116 Operation mode setting part, 117 Person motion recognition part, 151 Service information , 152 congestion prediction information, 153 operation mode information, 20 platforms, 210 information storage unit, 211 communication processing unit, 212 congestion status prediction unit, 2121 congestion history information generation unit, 2122 statistical processing unit, 2123 prediction information generation unit, 30 congestion Situation sensor, S1200 congestion prediction information generation process, S1300 operation mode setting process (current), S1400 operation mode setting process (future), S1500 operation mode setting process (current and future)

Claims (17)

An information storage unit that stores congestion history information that is information indicating a degree of congestion every past predetermined time in a service providing area in which a robot capable of autonomous movement provides an interpersonal service;
A congestion status prediction unit that generates congestion prediction information that is information obtained by predicting the degree of congestion of the service providing area every predetermined time based on the congestion history information;
Any one of a plurality of operation modes having different influences on the degree of congestion of the service providing area selected according to the degree of congestion of the current or future service providing area acquired from the congestion prediction information An operation mode setting unit for setting the robot to
A robot control system comprising: The robot control system according to claim 1,
The operation mode setting unit
When the congestion level of the current or future service provision area acquired from the congestion prediction information exceeds a first threshold, the robot is set to the first operation mode,
When the degree of congestion in the current or future service provision area acquired from the congestion prediction information is equal to or less than the first threshold, the influence on the degree of congestion in the service provision area is greater than that in the first operation mode. Setting the robot to the second operation mode;
Robot control system. The robot control system according to claim 1,
The operation mode setting unit
When the congestion level of the current or future service provision area acquired from the congestion prediction information exceeds a first threshold, the robot is set to the first operation mode,
When the degree of congestion in the current or future service provision area acquired from the congestion prediction information exceeds the first threshold and exceeds the second threshold (<first threshold), the service is more effective than the first operation mode. The robot is set to the second operation mode having a large influence on the congestion degree of the provision area,
When the current or future congestion level of the service provision area acquired from the congestion prediction information is equal to or less than the second threshold value, the influence on the congestion level of the service provision area is greater than that of the second operation mode. Setting the robot to the third operation mode;
Robot control system. The robot control system according to claim 1,
The operation mode setting unit
When the congestion level of the current service providing area acquired from the congestion prediction information exceeds a first threshold, the robot is set to the first operation mode,
The current congestion level acquired from the congestion prediction information does not exceed the first threshold, but when the future congestion level acquired from the congestion prediction information exceeds the first threshold, the first degree Set the robot in operation mode,
When neither the current congestion level of the service providing area acquired from the congestion prediction information nor the future congestion level acquired from the congestion prediction information exceeds the first threshold, the first operation Setting the robot to the second operation mode having a larger influence on the degree of congestion of the service providing area than the mode;
Robot control system. The robot control system according to claim 1,
The operation mode setting unit
When the congestion level of the current service providing area acquired from the congestion prediction information exceeds a first threshold, the robot is set to the first operation mode,
The current congestion level acquired from the congestion prediction information does not exceed the first threshold, but when the future congestion level acquired from the congestion prediction information exceeds the first threshold, the first degree Set the robot in operation mode,
When the degree of congestion in the future service provision area acquired from the congestion prediction information is not more than the first threshold and exceeds a second threshold (<first threshold), the service provision area is more than in the first operation mode. The robot is set to the second operation mode having a large influence on the degree of congestion of
When the degree of congestion in the future service provision area acquired from the congestion prediction information is less than or equal to the second threshold, the influence on the degree of congestion in the service provision area is greater than that in the second operation mode. Setting the robot to the operation mode of
Robot control system. The robot control system according to any one of claims 2 to 5,
In the first operation mode, the robot provides the interpersonal service in a predetermined area narrower than the service providing area provided in the service providing area.
Robot control system. The robot control system according to any one of claims 2 to 5,
In the first operation mode, the robot provides the interpersonal service in a predetermined area narrower than the service providing area provided in the service providing area;
In the second operation mode, the robot determines whether or not the interpersonal service is necessary based on an action of a person existing in the service providing area within a predetermined area provided in the service providing area. When it is determined that a service is necessary, move to the vicinity of the person and provide the interpersonal service.
Robot control system. The robot control system according to claim 3 or 5,
In the first operation mode, the robot provides the interpersonal service in a predetermined area narrower than the service providing area provided in the service providing area;
In the second operation mode, the robot determines whether or not the interpersonal service is necessary based on an action of a person existing in the service providing area within a predetermined area provided in the service providing area. When it is determined that a service is necessary, move to the vicinity of the person to provide the interpersonal service,
In the third operation mode, the robot moves in the service providing area and provides the interpersonal service when a person approaches within a predetermined range from the robot during the movement.
Robot control system. The robot control system according to any one of claims 1 to 5,
The congestion status prediction unit generates the congestion prediction information based on information obtained by performing statistical processing on the congestion history information.
Robot control system. The robot control system according to any one of claims 1 to 5,
A congestion history information generating unit that generates the congestion history information based on sensor data that is data acquired by a congestion status sensor that is a sensor that acquires a congestion status in the service providing area;
Robot control system. The robot control system according to claim 10,
The congestion status sensor is a camera;
The sensor data is video data or image data,
The congestion history information generation unit generates the congestion history information by performing video recognition or image recognition on the sensor data.
Robot control system. The robot control system according to claim 1,
A robot capable of autonomous movement providing interpersonal services in the service providing area;
A communication processing unit that communicates with the robot, an information storage unit that stores congestion history information that is information indicating a degree of congestion at each past predetermined time in the service providing area, and a predetermined time interval based on the congestion history information A platform having a congestion status prediction unit that generates congestion prediction information, which is information predicting the degree of congestion;
With
The robot receives the congestion prediction information from the platform, and is selected according to the congestion degree of the current or future service provision area acquired from the received congestion prediction information. Having an operation mode setting unit for setting itself to any one of a plurality of operation modes having different influences on
Robot control system. The platform in the robot control system according to claim 12,
A communication processing unit for communicating with the robot;
An information storage unit that stores congestion history information that is information indicating a degree of congestion every predetermined time period in the service providing area;
And based on the congestion history information, a congestion status prediction unit that generates congestion prediction information that is information predicting the degree of congestion every predetermined time,
With a platform. The robot in the robot control system according to claim 12,
An operation control unit for controlling its own operation;
A movement control unit for controlling its own movement;
A service providing unit for controlling the interpersonal service;
The congestion prediction information is received from the platform, and is selected according to the congestion degree of the service providing area at present or in the future acquired from the received congestion prediction information. An operation mode setting unit that sets itself to one of a plurality of different operation modes;
A robot comprising: Information processing device
A step of storing congestion history information that is information indicating a degree of congestion every past predetermined time in a service providing area in which a robot capable of autonomous movement provides an interpersonal service;
Generating congestion prediction information which is information obtained by predicting the degree of congestion every predetermined time in the service providing area based on the congestion history information;
Any one of a plurality of operation modes having different influences on the degree of congestion of the service providing area selected according to the degree of congestion of the current or future service providing area acquired from the congestion prediction information Setting the robot to
To control the robot. The robot control method according to claim 15, comprising:
The information processing apparatus is
Setting the robot to the first operation mode when the congestion level of the current or future service providing area acquired from the congestion prediction information exceeds a first threshold;
When the degree of congestion in the current or future service provision area acquired from the congestion prediction information is equal to or less than the first threshold, the influence on the degree of congestion in the service provision area is greater than that in the first operation mode. Setting the robot to the second operating mode;
To control the robot. The robot control method according to claim 15, comprising:
The information processing apparatus is
Setting the robot to the first operation mode when the congestion level of the current or future service providing area acquired from the congestion prediction information exceeds a first threshold;
When the degree of congestion in the current or future service provision area acquired from the congestion prediction information exceeds the first threshold and exceeds the second threshold (<first threshold), the service is more effective than the first operation mode. Setting the robot to the second operation mode having a large influence on the congestion degree of the provision area;
When the current or future congestion level of the service provision area acquired from the congestion prediction information is equal to or less than the second threshold value, the influence on the congestion level of the service provision area is greater than that of the second operation mode. Setting the robot to a third operating mode;
To control the robot.

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