Control method, autonomous moving body, and program

Abstract

A control method according to the present disclosure is for controlling, by means of a computer with the support of an operator, an autonomous moving body which is capable of moving autonomously and performing a prescribed task, wherein actual measurement of the load of the operator is performed on the basis of first information indicating the status of the autonomous moving body, which is operating according to an operation schedule of the autonomous moving body, an actual measured load is calculated, and the autonomous moving body is controlled so as to increase the load of the operator if the actual measured load is equal to or less than a first threshold value.

Description

Control method, autonomous moving body, and program

[0001] The present disclosure relates to a control method, an autonomous moving body, and a program.

[0002] Technologies have been developed to allow autonomous mobile objects, such as robots, to perform various tasks with the support of an operator. For example, in the technology disclosed in Patent Literature 1, when the operator's margin of intervention is below a threshold, i.e., when the operator has no time to intervene, the autonomous mobile object's travel route is changed. In this way, various countermeasures have been devised to reduce the burden on the operator.

[0003] However, currently, no measures are taken to deal with situations where the operator's load is lower than expected. As a result, a decrease in the operator's load may lead to a decrease in the quality of the service provided by the autonomous mobile unit, for example, due to the operator becoming careless and making a mistake. Furthermore, if the operator's load remains low for a long period of time, there is a possibility that opportunities to further improve service quality, such as by requesting the operator to take additional action regarding the service, may be missed.

[0004] Patent No. 7183891

[0005] The present disclosure aims to provide a control method, an autonomous moving body, and a program that can improve service quality by appropriately increasing the load on an operator.

[0006] The control method disclosed herein is a control method in which a computer controls an autonomous moving body that can move autonomously and perform specified tasks with the support of an operator, and the control method measures the load on the operator based on first information that indicates the status of the autonomous moving body while it is operating in accordance with an operation schedule of the autonomous moving body, and calculates the measured load.If the measured load is equal to or less than a first threshold, the autonomous moving body is controlled to increase the load on the operator.

[0007] According to the control method, autonomous moving body, and program disclosed herein, service quality can be improved by appropriately increasing the load on operators.

[0008] FIG. 1 is a block diagram illustrating a schematic configuration of a robot system according to an embodiment. FIG. 2 is a block diagram illustrating an example of a detailed configuration of a robot system according to an embodiment. FIG. 3 is an example of basic data referenced when a server device according to an embodiment calculates a predicted load. FIG. 4 is a diagram illustrating an example of a calculation result of a predicted load that may occur on an operator for multiple robots by the server device according to an embodiment. FIG. 5 is an example of basic data referenced when a server device according to an embodiment calculates an actual load or service quality. FIG. 6 is a diagram illustrating several examples of a calculation result of an actual load, a result of adjusting the actual load, and a calculation result of service quality by the server device according to an embodiment. FIG. 7 is a diagram illustrating several examples of a calculation result of an actual load, a result of adjusting the actual load, and a calculation result of service quality by the server device according to an embodiment. FIG. 8 is a diagram illustrating several examples of a calculation result of an actual load, a result of adjusting the actual load, and a calculation result of service quality by the server device according to an embodiment. FIG. 9 is a diagram illustrating several examples of a calculation result of an actual load, a result of adjusting the actual load, and a calculation result of service quality by the server device according to an embodiment. FIG. 10 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 11 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 12 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 13 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 14 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 15 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 16 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment.FIG. 17 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 18 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 19 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 20 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 21 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 22 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 23 is a diagram illustrating several examples of the calculation results of the actual load, the adjustment results of the actual load, and the calculation results of the service quality by the server device according to the embodiment. FIG. 24 is a flow diagram showing an example of a procedure for robot control processing performed by the server device according to the embodiment. FIG. 25 is a schematic diagram showing an example of various display screens displayed on an output unit by the server device according to Modification 1 of the embodiment. FIG. 26 is an example of basic data referenced when a predicted load is calculated by the server device according to Modification 2 of the embodiment. FIG. 27 is an example of basic data referenced when a predicted load is calculated by the server device according to Modification 2 of the embodiment. FIG. 28 is an example of basic data referenced when a predicted load is calculated by the server device according to Modification 2 of the embodiment. FIG. 29 is a diagram showing an example of a method for adjusting a predicted load that may occur on an operator for a plurality of robots by the server device according to Modification 2 of the embodiment. FIG. 30 is a diagram showing an example of a method for adjusting a predicted load that may occur on an operator for a plurality of robots by the server device according to Modification 2 of the embodiment. FIG. 31 is a diagram showing an example of a method for adjusting a predicted load that may occur on an operator for a plurality of robots by the server device according to Modification 2 of the embodiment. FIG. 32 is a block diagram showing an example of a detailed configuration of a robot system according to Modification 3 of the embodiment.FIG. 33 is a flowchart illustrating an example of a procedure for a robot control process performed by a server device according to the third modification of the embodiment.

[0009] Hereinafter, embodiments of a control method, an autonomous moving body, and a program according to the present disclosure will be described with reference to the drawings.

[0010] 1 is a block diagram showing a schematic configuration of a robot system 1 according to an embodiment. As shown in FIG. 1, the robot system 1 includes a plurality of robots 10, a server device 20, and a plurality of input / output devices 30.

[0011] Each robot 10 is connected to a server device 20 via a network NT such as the Internet, and is configured to be able to move autonomously under the control of the server device 20 and perform various tasks such as delivery, security, mobile sales, or cleaning.

[0012] The server device 20 is connected to a plurality of input / output devices 30 which can be operated by a plurality of operators 33. The operators 33 monitor the status of each robot 10 from the server device 20 via the input / output devices 30 and provide support to these robots 10.

[0013] The server device 20 is connected to at least the same number of input / output devices 30 as the number of operators 33, with at least one input / output device 30 assigned to each individual operator 33. In the robot system 1, one operator 33 supports at least one robot 10, and typically supports multiple robots 10. Therefore, the server device 20 is connected to and remotely controlled by at least the number of robots 10 equal to or greater than the number of operators 33.

[0014] (Example of Robot Configuration) Fig. 2 is a block diagram showing an example of a detailed configuration of the robot system 1 according to the embodiment. Fig. 2 shows one each of the multiple robots 10 and multiple input / output devices 30 included in the robot system 1. Hereinafter, the detailed configuration of the robot 10 according to the embodiment will be described with reference to Fig. 2.

[0015] 2 , the robot 10 includes a communication unit 11, a service information acquisition unit 12, a robot information acquisition unit 13, a sensor group 14, a control information acquisition unit 15, a control unit 16, and a drive unit 17. The robot 10 is an example of an autonomous mobile object that can move autonomously and perform a predetermined task with the support of an operator 33.

[0016] The sensor group 14 includes a position sensor, a speed sensor, an acceleration sensor, a distance sensor, an imaging unit, and other sensors, and detects the situation around the robot 10.

[0017] The position sensor is a Global Navigation Satellite System (GNSS) receiver or the like that can receive position information from a GNSS, and identifies the current position of the robot 10 .

[0018] The speed sensor detects the running speed of the robot 10 based on, for example, the drive amount per unit time of the drive unit 17. The acceleration sensor detects the acceleration occurring in the main body of the robot 10. The acceleration sensor may also function as a speed sensor by detecting the speed of the robot 10.

[0019] The distance sensor transmits, for example, ultrasonic waves or infrared rays and detects the reflected waves that are reflected by surrounding objects, thereby detecting the presence or absence, number, and distance of objects from the robot 10 to the objects around the robot 10.

[0020] The imaging unit is a camera or the like equipped with an imaging element such as a CMOS (Complementary Metal Oxide Semiconductor) sensor, a CCD (Charge Coupled Device) sensor, etc. The imaging unit detects the presence, number, and type of objects around the robot 10.

[0021] The robot 10 may be equipped with multiple distance measuring sensors and multiple imaging units.

[0022] The control information acquisition unit 15 acquires control information output from the server device 20. The control information may include information such as control for causing the robot 10 to run or stop, and control for causing the robot 10 to execute a predetermined task. When causing the robot 10 to run, the control information may also include information such as the running speed, acceleration, running direction, and running distance.

[0023] The control unit 16 controls the drive unit 17 based on the control information acquired by the control information acquisition unit 15 from the server device 20 .

[0024] The driving unit 17 includes, for example, a mechanism that allows the robot 10 to travel a predetermined distance in a predetermined direction at a predetermined speed, and a mechanism that can perform an operation to execute a task.

[0025] The mechanism for moving the robot 10 may be, for example, crawlers or wheels, etc. Other mechanisms for moving the robot 10 include a motor for rotating the crawlers or wheels, etc., and a brake for braking the crawlers or wheels, etc.

[0026] The mechanism for executing the task may be, for example, a storage mechanism for taking in and out deliveries when the task is delivery, a warning light and alarm and a control mechanism for these when the task is security, a storage mechanism for taking in and out merchandise and a cash register function for handling money and the like when the task is mobile sales, a sweeping mechanism for wiping away trash and dirt, a trash collection mechanism, etc. In addition, the robot 10 may be equipped with a display device, a speaking mechanism, etc. as a mechanism for executing a task.

[0027] The robot information acquisition unit 13 acquires the detection results of the sensor group 14, the control signals of the driving mechanism of the robot 10 in the driving unit 17, etc. as robot information indicating the state of the robot 10. Therefore, the robot information includes, for example, the current position of the robot 10, its state (whether it is running or stopped), its running speed and direction if it is running, and the situation around the robot 10.

[0028] The service information acquisition unit 12 acquires the detection results of the sensor group 14, the control signals of the task execution mechanism in the drive unit 17, and the like as service information indicating the status of the service being provided by the robot 10. The service information includes, for example, information such as the type of service, the progress and degree of completion of the service, and the like.

[0029] The type of service refers to the tasks of the robot 10, such as delivery, security, mobile sales, cleaning, etc., as described above.

[0030] For example, if the task is delivery, the progress of the service includes information such as the current location of the robot 10, the current status of the robot 10 (e.g., whether it is delivering, has not yet arrived at the delivery destination, or has already arrived), the distance from the current location of the robot 10 to the delivery destination, or the current distance traveled relative to the total distance traveled. Also, for example, if the task is security or cleaning, the progress of the service includes information such as the current location of the robot 10 within the security range or cleaning range, the range in which security or cleaning has been completed, or the range in which security or cleaning is not yet completed. Also, for example, if the task is mobile sales, the progress of the service includes information such as the current location of the robot 10 within the range in which the mobile sales is performed, the number of locations already visited among the destination locations in the mobile sales, or the number of locations planned to be visited.

[0031] For example, if the task is delivery, the degree of completion of the service includes information such as the estimated time when the delivery can actually be completed compared to a predetermined scheduled delivery time. Also, for example, if the task is security, mobile sales, or cleaning, the degree of completion of the service includes information such as the estimated range in which the security, mobile sales, or cleaning can actually be performed compared to the planned range of the security, mobile sales, or cleaning.

[0032] The communication unit 11 transmits the robot information acquired by the robot information acquisition unit 13 and the service information acquired by the service information acquisition unit 12 to the server device 20 via the network NT.

[0033] The robot 10 may be equipped with a computer including a central processing unit (CPU), a read-only memory (ROM), a random access memory (RAM), etc. (not shown). The CPU loads a control program stored in the ROM into the RAM and executes it, thereby realizing the functions of at least the service information acquisition unit 12, the robot information acquisition unit 13, and the control unit 16 among the above-mentioned components of the robot 10.

[0034] (Configuration Example of Server Device) Next, a detailed configuration of the server device 20 according to the embodiment will be described with reference to Fig. 2. As shown in Fig. 2, the server device 20 includes an operation schedule information database 21, an operator information database 22, an operator load prediction unit 23, an information acquisition unit 24, an operator load measurement unit 25, a determination unit 26, a control information generation unit 27, and a control information output unit 28.

[0035] The operation schedule information database 21 stores operation schedule information regarding the operation schedule of each robot 10. The operation schedule information includes, for example, the planned travel route, planned travel distance, planned travel speed, and the degree of risk at each point along the planned travel route of each robot 10. Furthermore, if the task of the robot 10 is security or cleaning, etc., the operation schedule information includes the planned area of ​​security or cleaning. Furthermore, if the task of the robot 10 is mobile sales, etc., the operation schedule information includes the area in which the mobile sales will be conducted, as well as target sales numbers and target sales revenue for each product. Note that the target sales numbers and target sales revenue for each product are determined based on past performance. Furthermore, the operation schedule information includes other information, such as the type of service and service conditions.

[0036] The planned driving route includes information on multiple points along the planned driving route that the robot 10 will pass through or stop at. The degree of risk at each point is calculated based on, for example, statistical information indicating the number of traffic participants at each point and history information on remote control requests at each point.

[0037] Traffic participants are, for example, cars, motorcycles, bicycles, pedestrians, etc., and can be calculated from the past history at each point. The greater the number of traffic participants at each point, the more likely it is that the autonomous movement of the robot 10 will be interrupted due to the robot 10 being obstructed or falling over, resulting in a delay in the task.

[0038] A remote control request is a request for remote assistance from the operator 33 when the robot 10 encounters a problem that it cannot solve by itself. The number of remote control requests can be calculated from the past history of remote control requests that occurred while the robot 10 was passing through or stopping at each point. The more remote control requests there are at each point, the more likely it is that the robot 10 will be temporarily stopped or that it will take a certain amount of time for the operator 33 to respond, causing delays in the robot 10's tasks.

[0039] Therefore, in light of past history, the more traffic participants there are at a point, and the more remote control requests there are at a point, the higher the calculated risk level is. In this way, it can be said that the risk that may occur in the task of the robot 10 is the delay that may occur in the task of the robot 10.

[0040] Note that when calculating the risk level, the risk level may be calculated taking into account information such as the difficulty of the remote control request and the time required to respond to it. In other words, the risk level may be calculated to be higher the higher the difficulty of the remote control request and the longer the time required to respond to it.

[0041] The planned travel distance is a value calculated from, for example, the planned travel route. The planned travel speed may be determined based on, for example, the task of each robot 10, the length of the planned travel distance, etc. When determining the planned travel speed based on the task of each robot 10, for example, if the task is delivery, the planned travel speed may be calculated from the planned delivery time. If the task is security, mobile sales, or cleaning, the planned travel speed may be calculated from the planned security area, planned mobile sales area, or planned cleaning area, etc. In addition, the planned travel distance may be determined based on, for example, the number of traffic participants at each point included in the planned travel route. In this case, for example, if the number of traffic participants at each point is small, the speed of the robot 10 can be increased while ensuring safety.

[0042] Furthermore, as described above, the types of services included in the operation schedule information are tasks for the robot 10, such as delivery, security, mobile sales, cleaning, etc. Furthermore, the service conditions included in the operation schedule information include, for example, if the task is delivery, information such as the name of the item to be delivered, the delivery destination, and the scheduled delivery time. Furthermore, for example, if the task is security, the service conditions include information such as the scheduled security area and how to respond to suspicious persons and suspicious objects. Furthermore, for example, if the task is mobile sales, the service conditions include information such as the type of product, sales destination, and price. Furthermore, for example, if the task is cleaning, the service conditions include information such as the scheduled cleaning area, and the location and method of garbage disposal. Operation schedule information regarding the operation schedules of multiple robots 10 is an example of third information.

[0043] The operator information database 22 stores operator information about each operator 33. The operator information includes information about each operator 33, such as the degree of workload that the operator 33 can handle. The degree of workload that each operator 33 can handle is calculated based on the attributes of the operator 33, such as the length of service of the operator 33, the number of support work experiences, proficiency, and past performance. The operator information indicating the degree of workload that the operator 33 can handle is an example of second information.

[0044] The operator load prediction unit 23 calculates a predicted load by predicting the load that may occur on the operator 33 based on the operation schedule information stored in the operation schedule information database 21. As will be described in detail later, the predicted load is calculated, for example, by assigning a score to each of the above-mentioned items included in the operation schedule information.

[0045] Furthermore, the operator load prediction unit 23 checks, based on the operator information stored in the operator information database 22, that the predicted load does not exceed the load that each individual operator 33 can handle.

[0046] Furthermore, based on the calculated predicted load, the operator load prediction unit 23 determines a lower limit threshold and an upper limit threshold to be used as indicators when determining whether the actual measured load of the operator 33 described below is greater than or less than the predicted load, as well as a judgment value for the duration of the actual measured load exceeding the lower limit threshold or the upper limit threshold. The lower limit threshold is set at least lower than the predicted load, and the upper limit threshold is set at least higher than the predicted load. In this case, the operator load prediction unit 23 may determine the judgment values ​​for the lower limit threshold, upper limit threshold, and duration by taking into account the load that each operator 33 can handle.

[0047] The lower limit threshold used when determining whether the actual load of the operator 33 is greater than or equal to the predicted load is an example of a first threshold, and the upper limit threshold is an example of a second threshold. Also, the judgment value used when determining the duration of a period in which the actual load is equal to or less than the lower limit threshold is an example of a first period. Also, the judgment value used when determining the duration of a period in which the actual load to be determined exceeds the upper limit threshold is an example of a second period.

[0048] The information acquisition unit 24 acquires robot information and service information transmitted from the communication unit 11 of the robot 10. The robot information and service information acquired from the plurality of robots 10 is an example of first information.

[0049] The operator load measurement unit 25 calculates the measured load by measuring the load imposed on each operator 33 by supporting multiple robots 10, based on the robot information acquired by the information acquisition unit 24 from the robots 10. As will be described in detail later, the measured load is calculated, for example, by assigning a score to each of the above-mentioned items included in the robot information. At this time, the operator load measurement unit 25 may calculate the measured load of each operator 33 by taking into account the response status of each operator 33, etc.

[0050] The response status of each operator 33 can be determined, for example, based on control information (described later) output from the operator 33. Alternatively, the response status of each operator 33 may be determined, for example, based on a video image of the operator 33. Information on the response status of the operator 33 obtained in this manner may be included in the first information, similar to the robot information and service information described above.

[0051] Here, the actual load calculated based on the robot information acquired from the robot 10 may not match the predicted load calculated based on the operation schedule information. For example, if the number of traffic participants or remote control requests at a specified location is lower than predicted, the actual load may be lower than the predicted load. Also, if the number of traffic participants at a specified location is higher than expected, or if an unexpected remote control request occurs due to a sudden accident, the actual load may exceed the predicted load.

[0052] The determination unit 26 determines whether to increase, maintain, or decrease the load of each operator 33 based on the predicted load calculated by the operator load prediction unit 23 and the actual load calculated by the operator load measurement unit 25.

[0053] More specifically, if the actual measured load is equal to or less than the lower limit threshold set lower than the predicted load and the duration of such a state reaches the determination value (first period), the determination unit 26 determines to increase the load of the operator 33. Also, if the actual measured load exceeds the upper limit threshold set higher than the predicted load and the duration of such a state reaches the determination value (second period), the determination unit 26 determines to reduce the load of the operator 33. Also, if the actual measured load is above the lower limit threshold and is equal to or less than the upper limit threshold, the determination unit 26 determines to maintain the load of the operator 33 as is.

[0054] Furthermore, the determination unit 26 calculates the service quality of each robot 10 based on the service information acquired from the robot 10 by the information acquisition unit 24 .

[0055] If the task of the robot 10 is, for example, delivery, the service quality is calculated based on a comparison between the scheduled delivery time and the scheduled arrival time within which the delivery can be completed. If the task of the robot 10 is, for example, security, the service quality is calculated based on a comparison between the scheduled security area and the scheduled completion area within which the security can be completed. If the task of the robot 10 is, for example, mobile sales, the service quality is calculated based on the target sales volume or target sales amount for each product and the actual sales volume or sales amount. If the task of the robot 10 is, for example, cleaning, the service quality is calculated based on a comparison between the scheduled cleaning area and the scheduled completion area within which the cleaning can be completed.

[0056] The above-mentioned scheduled delivery time, scheduled security area, target sales quantity and target sales amount for each product, and scheduled cleaning area can be obtained, for example, from the operation schedule information of each robot 10 stored in the operation schedule information database 21. The above-mentioned scheduled arrival time and scheduled completion area for security or cleaning can be obtained, for example, from the progress and degree of achievement of the service contained in the service information acquired by the information acquisition unit 24 from the robot 10. The actual number of products sold or sales amount in the mobile sales are acquired each time a product is handed over to a customer, and are totaled when the mobile sales task by the robot 10 is completed.

[0057] In principle, the control information generation unit 27 generates control information for controlling each robot 10 based on the operation schedule information stored in the operation schedule information database 21. In addition, the control information generation unit 27 appropriately changes the control content of the robot 10 based on the determination result of the above-mentioned determination unit 26 so as to adjust the load actually imposed on the operator 33.

[0058] More specifically, if the determination result is that the actual measured load is within a range above the lower threshold and below the upper threshold, the control information generation unit 27 generates control information for the robot 10 so that the load imposed on the operator 33 is maintained as is.

[0059] Furthermore, if the determination result indicates that the actual measured load is below the lower threshold, the control information generation unit 27 changes the control information of at least one of the multiple robots 10 supported by the operator 33 so as to increase the load on the operator 33.

[0060] In this case, the robot 10 for which the control information is to be changed may be, for example, the robot 10 that caused the actual measured load of the operator 33 to fall below the predicted load. Alternatively, a predetermined robot 10 may be selected as the robot 10 for which the control information is to be changed, for example, based on the service quality calculated by the determination unit 26.

[0061] In the selection based on service quality, for example, a robot 10 whose calculated service quality is equal to or lower than a predetermined threshold can be selected. The threshold of service quality is an example of a third threshold, and is determined based on, for example, a target service quality or the average service quality at that time of multiple robots 10. Furthermore, if there are special members who pay an additional fee, a robot 10 that provides services to those special members may be selected.

[0062] Alternatively, the robot 10 for which the control information is to be changed may be a robot 10 that is in a situation where it is unlikely to be affected by the change in control information, for example, depending on the progress of the service included in the service information.

[0063] Examples of control that increases the workload of the operator 33 include control to increase the traveling speed of the target robot 10, control to change the traveling route to a route that increases the workload of the operator 33, control to increase the number of points on the traveling route such as adding delivery destinations, control to expand the security area or cleaning area, control to change the traveling route to include points where more traffic participants are present to increase the encounter rate with potential customers in the mobile sales, and control that requires additional action by the operator. The encounter rate with potential customers in the mobile sales can be calculated from the number of traffic participants per unit time that appear within a predetermined distance from the robot 10, based on information acquired from the sensor group 14 of the robot 10, which includes, for example, an imaging unit.

[0064] A travel route that places a greater burden on the operator 33 is, for example, a route that is a shortcut but passes through points where many traffic participants are expected or points where many remote control requests are expected.

[0065] Control requiring additional action by the operator 33 includes, for example, control of the target robot 10 to speak while cleaning in order to alert people in the vicinity, control of the robot 10 during mobile sales to speak in order to increase the purchasing motivation of potential customers in the vicinity, control of the operator 33 himself to perform the security task of checking whether any suspicious situations have occurred around the robot 10 while it is cleaning via the robot 10's sensor group 14 including an imaging unit, etc., control to increase the speed at which tasks are executed, such as advancing the delivery time or expanding the security area per unit time, the mobile sales area, or the cleaning area, and control to have the robot 10 execute other tasks in addition to the tasks originally planned, such as having the robot 10 that was cleaning also perform security.

[0066] In order to support the robot 10 under the control described above, the operator 33 will need to take additional measures, such as determining when it is necessary to alert people in the vicinity or when there are potential customers nearby and having the robot 10 speak, or operating the robot 10 to sequentially transmit information acquired by the sensor group 14 including an imaging unit etc. so that the operator 33 can check the situation around the robot 10 while it is cleaning, or strengthening monitoring as the speed at which the robot 10 executes its tasks increases, as the task is interrupted or delayed due to the robot 10 falling over, etc., i.e., the degree of risk also increases.

[0067] Examples of control to reduce the burden on the operator 33 include control to reduce the traveling speed of the robot 10 that is the target of the control change, control to change the traveling route to a route that reduces the burden on the operator 33, and control to narrow the security range, the mobile sales area, or the cleaning area. By reducing the traveling speed of the robot 10, the degree of concentration of the operator 33 monitoring the autonomously moving robot 10 can be reduced. Furthermore, narrowing the security range or the cleaning range can narrow the area that needs to be monitored, such as the situation around the robot 10 while it is operating, and can also reduce the number of objects that need to be monitored, thereby reducing the burden on the operator 33. Furthermore, narrowing the mobile sales area can complete the mobile sales in a shorter time, thereby reducing the burden on the operator 33.

[0068] The control information output unit 28 outputs the control information for the robot 10 generated by the control information generation unit 27 to the robot 10 and the input / output device 30. As a result, the robot 10 performs operations in accordance with the control information. In addition, the operator 33 can know the control status of the robot 10 by referring to the input / output device 30.

[0069] As will be described later, the operator 33 may input further control information from the input / output device 30 based on the information on the control status of the robot, and perform remote control, etc. The control information output unit 28 also outputs the control information input by the operator 33 to the robot 10.

[0070] In addition, in the server device 20, the acquisition of robot information and service information, calculation of the actual load of the operator 33 based on this information, comparison of the actual load with the predicted load, generation of control information based on the operation schedule information or the comparison and judgment result, and control of the robot 10 based on the control information are repeatedly performed every unit time.

[0071] In this case, the measured load of the operator 33 calculated by the operator load measuring unit 25 based on the robot information after the load on the operator 33 has been adjusted and the response status of the operator 33 is also referred to as the adjusted load. The robot information after the load on the operator 33 has been adjusted is an example of fourth information. The response status of the operator 33 after the load on the operator 33 has been adjusted may be included in the fourth information.

[0072] If the state in which the adjusted load exceeds the upper threshold continues for a period of time exceeding the above-mentioned judgment value of the duration, in order to reduce the load on the operator 33, the above-mentioned control such as reducing the traveling speed, changing the route, reducing the security area, mobile sales area, or cleaning area is performed for at least one robot 10, and the control that increases the load on the operator 33 may also be terminated.

[0073] When terminating the control that increases the load on the operator 33, it is basically possible to terminate the control for the robot 10 that has performed the control that increases the load on the operator 33. Furthermore, when there are multiple such robots 10, and when selecting a robot 10 from among these robots 10 for which the control that increases the load on the operator 33 is to be terminated, it is possible to select a robot 10 that is in a situation where it is unlikely to be affected by a change in the control information, for example, depending on the progress of the service included in the service information, etc.

[0074] The server device 20 configured as above includes a computer including a CPU, ROM, RAM, etc. (not shown). The CPU loads a control program stored in the ROM into the RAM and executes it, thereby realizing the functions of at least the operator load prediction unit 23, the operator load measurement unit 25, the determination unit 26, and the control information generation unit 27 among the above components of the server device 20.

[0075] The control program executed by the server device 20 can be provided by being recorded in an installable or executable file format on a recording medium readable by a computer device, such as a CD (Compact Disc)-ROM (Read Only Memory), a flexible disk (FD), a CD-R (Recordable), or a DVD (Digital Versatile Disk).

[0076] The control program may be stored on a computer such as a server connected to a network such as the Internet and provided by being downloaded via the network. The control program may also be provided or distributed via a network such as the Internet.

[0077] (Configuration Example of Input / Output Device) Next, a detailed configuration of the input / output device 30 according to the embodiment will be described with reference to Fig. 2. As shown in Fig. 2, the input / output device 30 includes an output unit 31 and an input unit 32.

[0078] The output unit 31 is, for example, a display device such as a liquid crystal panel, a printing device such as a printer, etc. The operator 33 can obtain various information related to the server device 20 and the plurality of robots 10 from the information output from the output unit 31. The information related to the plurality of robots 10 includes, for example, control information for the robots 10 output from the server device 20, as described above.

[0079] The input unit 32 is, for example, a keyboard, a mouse, or other input device. The input unit 32 may also be a touch panel or the like integrated with a display device or the like. For example, when a remote control request is received, the operator 33 can input control information for the robot 10 from the input unit 32. As described above, the control information input from the input unit 32 is output to the robot 10, for example, via the control information output unit 28 of the server device 20. Furthermore, the control information input from the input unit 32 may be referred to by the operator load measurement unit 25 of the server device 20 as information indicating the response status of the operator, and the measured load of the operator 33 may be calculated.

[0080] (Example of Load Prediction) Next, an example of calculation of the predicted load of the operator 33 will be described with reference to FIGS. 3 and 4. FIG.

[0081] 3 shows an example of basic data referenced when the server device 20 according to the embodiment calculates a predicted load. As shown in Fig. 3, the load levels at multiple points included in the planned travel route, the load levels based on the operation schedule information of each robot 10, and the load levels based on the operator information of each operator 33 are quantified in advance, and the server device 20 calculates the predicted load of the operator 33 based on, for example, these numerical values.

[0082] FIG. 3A shows an example of basic data on the load levels at a plurality of points included in the planned travel route.

[0083] As shown in FIG. 3A, the planned travel route set for each robot 10 may include a starting point, at least one of points A through F that the robot 10 passes through or stops at, and at least one of destination points 1 through 4. Furthermore, the number of traffic participants and the number of remote control requests are extracted from the past history of each point to assess the degree of risk at each point. The number of traffic participants and the number of remote control requests are ranked, such as low, average, or high, depending on their magnitude. These ranks are quantified as 1, 2, 3, etc. for low, average, and high, respectively, making it possible to numerically represent the degree of load at each point.

[0084] Here, the number of traffic participants may be determined based on a predetermined threshold corresponding to the average number of traffic participants calculated from the past history for each location. Similarly, the number of remote control requests may be determined based on a predetermined threshold corresponding to the average number of remote control requests calculated from the past history for each location.

[0085] In the example of Figure 3(a), for example, the number of traffic participants and the number of remote control requests at the departure point are both ranked "average," and the load level at the departure point is calculated to be 4.0. Also, for example, the number of traffic participants and the number of remote control requests at point C are ranked "low" and "average," respectively, and the load level at point C is calculated to be 3.0. Also, for example, the number of traffic participants and the number of remote control requests at arrival point 1 are both ranked "high," and the load level at arrival point 1 is calculated to be 6.0.

[0086] FIG. 3B shows an example of basic data of the load level based on the operation schedule information of each robot 10.

[0087] As shown in FIG. 3B, the operation schedule information for each robot 10 includes, for example, the planned travel speed and planned travel distance of each robot 10. The planned travel speed and planned travel distance are also ranked according to the planned speed and the planned travel distance. For example, the planned travel speed is ranked as low, medium, etc., and these ranks are quantified as 1, 2, etc. for low and medium speed, respectively. The planned travel distance is also ranked as short or long, and these ranks are quantified as 1, 2, etc. for short and long, respectively. This allows the degree of load based on the operation schedule information for each robot 10 to be expressed numerically.

[0088] Here, the planned traveling speed may be determined based on a predetermined threshold value corresponding to, for example, the maximum speed or average traveling speed of the robot 10. The planned traveling distance may be determined based on, for example, a predetermined threshold value corresponding to, for example, the average traveling distance of the robot 10. Alternatively, the planned traveling distance may be determined based on, for example, the number of points included in the planned traveling route.

[0089] In the example of Figure 3(b), for example, the ranks of the planned running speed and planned running distance specified for robot 10 No. 1 are "low speed" and "long," respectively, and the load level required to support robot 10 is calculated to be 3.0. Also, for example, the ranks of the planned running speed and planned running distance specified for robot 10 No. 2 are "medium speed" and "short," respectively, and the load level required to support robot 10 is calculated to be 3.0.

[0090] Note that the operation schedule information of each robot 10 may include other items such as the planned security area, the planned area for mobile sales, the planned area for cleaning, etc., when the task of each robot 10 is security, mobile sales, cleaning, etc. Therefore, the load level based on the operation schedule information of each robot 10 may be calculated including such other items.

[0091] FIG. 3C shows an example of basic data of the load level based on the operator information of each operator 33.

[0092] 3C, the operator information for each operator 33 includes, for example, the proficiency level of each operator 33, the number of times the operator has performed the operator's job, etc. The proficiency level of each operator 33 is ranked, such as medium or high, depending on the level of proficiency. The proficiency ranks are quantified as 10, 20, etc. for medium and high, respectively, and by adding these numbers to, for example, the number of times the operator has performed the job, the degree of workload that each operator 33 can handle can be expressed numerically.

[0093] In the example of Figure 3(c), for example, the proficiency rank of operator A 33 is "high" and the number of experiences is 10. Therefore, the load level that operator A 33 can handle is calculated to be 30. Also, for example, the proficiency rank of operator B 33 is "medium" and the number of experiences is 8. Therefore, the load level that operator A 33 can handle is calculated to be 18.

[0094] Based on the basic data defined as above, the server device 20 calculates a predicted load as shown in FIG. 4, for example.

[0095] 4 is a diagram illustrating an example of a calculation result of a predicted workload that may occur on an operator 33 for a plurality of robots 10 by the server device 20 according to the embodiment. In the example of FIG. 4, four robots 10 (1 to 4) are assigned to one operator 33 (A).

[0096] 4A shows the predicted load that is expected to be placed on the operator 33 when supporting multiple robots 10. As shown in FIG. 4A, the predicted load that will be placed on the operator 33 is calculated based on the sum of the load levels for multiple robots 10, numbered 1 to 4, for each predetermined time t0 to t5, for example.

[0097] For example, at time t0, all robots 10, numbered 1 to 4, are located at the starting point. The load level at the starting point is, for example, 4.0, as shown in Figure 3(a) above. Furthermore, the load levels based on the operation schedule information of robots 10, numbered 1 to 4, are 3.0, 3.0, 4.0, 2, and 0, respectively, as shown in Figure 3(b) above.

[0098] Furthermore, for each robot 10, the load level at the starting point and the load level based on the operation schedule information for the robot 10 are added together, and these values ​​are multiplied by 1 / 2 to compare the load level and magnitude that each operator 33 can handle. As a result, the load levels for robots 10 1 to 4 are calculated as 3.5, 3.5, 4.0, 3.0, etc., respectively. Therefore, the predicted load that operator A 33 may experience when supporting multiple robots 10 at time t0 is calculated to be 14.

[0099] Furthermore, for example, at time t1, robots 10 1 to 4 are located at points A, B, E, and D, where the load levels are 4.0, 6.0, 3.0, and 5.0, respectively. If these load levels are added to the load levels based on the operation schedule information for each robot 10 and multiplied by 1 / 2, the load levels for robots 10 1 to 4 are calculated as 3.5, 4.5, 3.5, 3.5, etc., respectively. Therefore, the predicted load that may be imposed on operator A 33 in supporting multiple robots 10 at time t1 is calculated to be 15.

[0100] Similarly, for times t2 to t5, the predicted load that may occur to operator A's operator 33 can be calculated. In this case, in the example of FIG. 4(a), robot 10 No. 3 arrives at arrival point 2 at time t3, and robot 10 No. 4 arrives at arrival point 4 at time t4, and both robots are excluded from the support targets of operator A's operator 33.

[0101] 4B is a graph showing the relationship between the predicted load imposed on operator A's operator 33 and the load level that operator A can handle when supporting multiple robots 10. As shown in FIG. 4B, at all times t0 to t5, the predicted load is lower than the load level that operator A's operator 33 can handle.

[0102] In this way, when determining the operation schedule for multiple robots 10, the number of robots 10 to be supported, as well as the planned driving route, planned driving distance, planned security area, planned area for mobile sales or planned cleaning area, and planned driving speed of each robot 10 are determined so that the predicted load does not exceed the load level that each operator 33 can handle.

[0103] In addition, based on the degree of load that each individual operator 33 can handle, the server device 20 determines a lower threshold and an upper threshold to be used as indicators when judging the load of the operator 33, as well as a judgment value that serves as an indicator of the duration of time that the load remains below the lower threshold or above the upper threshold.

[0104] The lower limit threshold can be, for example, a value obtained by subtracting a value according to the proficiency level of the operator 33 from the load level that the operator 33 can handle. In this way, by setting the lower limit threshold according to the availability level and proficiency level of each individual operator 33, it is possible to set an appropriate load for each individual operator 33. Furthermore, the lower limit threshold is set higher for an operator 33 with a high availability level and proficiency level, which makes it easier to determine that the operator 33 has a sufficient load capacity, and control is performed to increase the load of the operator 33, making it easier to improve service quality.

[0105] The upper limit threshold can be set to, for example, a value equal to the load level that the operator 33 can handle. In this way, the upper limit threshold is also set according to the availability of each individual operator 33, thereby making it possible to keep the load state at an appropriate value for each individual operator 33. Furthermore, the upper limit threshold is set higher for operators 33 who have a high availability and proficiency, making it possible to prevent the load of the operator 33 from decreasing inadvertently, thereby maintaining service quality.

[0106] The determination value for the duration equal to or less than the lower threshold value can be, for example, one frame at time t0, t1, t2, etc. The determination value for the duration exceeding the upper threshold value can also be, for example, one frame at time t0, t1, t2, etc. The determination values ​​for the duration equal to or less than the lower threshold value or exceeding the upper threshold value may also be different for each operator 33 depending on the availability and proficiency of each individual operator 33.

[0107] That is, for an operator 33 with a high degree of availability and proficiency, the judgment value for the duration below the lower threshold can be set to a shorter value. This also makes it easier to determine that the operator 33 has a sufficient load, and control can be performed to increase the load on the operator 33, making it easier to improve service quality. This can also be expected to lengthen the period during which service quality can be improved.

[0108] On the other hand, for an operator 33 with a high level of availability and proficiency, the judgment value for the duration below the upper threshold can be set longer. This also prevents the operator 33 from having excess load, making it easier to improve service quality. This also makes it possible to expect a longer period during which service quality can be improved.

[0109] The operation schedule of each robot 10 is determined on the condition that the predicted load does not remain below the lower limit threshold for a period exceeding the above-mentioned determination value for the duration. More preferably, the operation schedule of each robot 10 is determined on the condition that the predicted load does not remain below the lower limit threshold throughout all of the times from t0 to t5.

[0110] Furthermore, the operation schedule of each robot 10 is determined so that 100% service quality is obtained for each robot 10 throughout all times from time t0 to t5.

[0111] (Examples of Actual Measurement and Adjustment of Load) Next, examples of calculation and adjustment of the actual measured load by the operator 33 will be described with reference to FIGS.

[0112] 5A to 5E show examples of basic data referenced when the server device 20 according to the embodiment calculates the measured load or service quality. As shown in FIGS. 5A to 5E, the load level of the operator 33 according to the robot information of the robot 10, the load level of the operator 33 according to the actual number of traffic participants, and the load level of the operator 33 according to the actual response status of the operator 33 are quantified in advance, and the server device 20 calculates the measured load of the operator 33 based on, for example, these numerical values. Furthermore, as shown in FIG. 5F, the load level when the operator 33 is made to perform additional response to increase the load of the operator 33 is also quantified in advance, and the server device 20 calculates the service quality after adjusting the load of the operator 33 based on, for example, these numerical values.

[0113] FIG. 5A shows an example of basic data of the load level based on the running speed included in the robot information of each robot 10.

[0114] 5A, the running speed of each robot 10 is ranked according to its speed. For example, the running speed is ranked as stopped, slow, medium, fast, etc., and these ranks are quantified as 0, 1, 2, 3, etc. for stopped, slow, medium, and fast, respectively.

[0115] Here, the actual running speed of the robot 10 may be determined based on a predetermined threshold value, for example, according to the maximum speed or average running speed that the robot 10 can achieve, similar to the planned running speed described above.

[0116] FIG. 5B shows an example of basic data of the load level based on the travel distance included in the robot information of each robot 10.

[0117] 5B, the travel distance of each robot 10 is ranked according to the length of the travel distance. For example, the travel distance is ranked as "arrival," "short," "long," etc., and these ranks are quantified as 0, 1, 2, etc. for "arrival," "short," and "long," respectively.

[0118] Here, similar to the aforementioned length of the planned traveling distance, the length of the traveling distance of the robot 10 may be determined based on a predetermined threshold value corresponding to, for example, the average traveling distance of the robot 10. Alternatively, the length of the traveling distance may be determined based on, for example, the number of points included in the traveling route.

[0119] FIG. 5C shows an example of basic data of the load level based on the guard range, mobile sales range, or cleaning range per unit time included in the robot information of each robot 10.

[0120] 5(c), the guard area or cleaning area per unit time by each robot 10 is ranked according to the size of these areas. For example, the guard area, mobile sales area, or cleaning area per unit time is ranked as small, large, etc., and these ranks are quantified as 0.9, 1.1, etc. for small and large, respectively.

[0121] The security area, mobile vending area, or cleaning area per unit time can be adjusted by adjusting the operating efficiency of the robot 10, such as by increasing the travel speed of the robot 10, increasing the speed of operations associated with security or cleaning, or changing the travel route to one with a larger number of traffic participants in the mobile vending business. The size of the security area, mobile vending area, or cleaning area per unit time by the robot 10 may be determined based on a predetermined threshold value according to, for example, the average security area, mobile vending area, or cleaning area per unit time by the robot 10.

[0122] FIG. 5D shows an example of basic data of the load level based on the number of traffic participants at the current position of each robot 10.

[0123] 5(d), the number of traffic participants at the current location of each robot 10 is ranked according to the number of traffic participants. For example, the number of traffic participants is ranked as low, average, high, etc., and these ranks are quantified as 1, 2, 3, etc. for low, average, and high, respectively.

[0124] Here, the number of traffic participants at the current position of the robot 10 can be calculated from the detection results obtained by the sensor group 14, such as the situation around the robot 10 included in the robot information. In addition, the actual number of traffic participants may be determined based on a predetermined threshold according to the average number of traffic participants obtained from the past history at each point, similar to the number of traffic participants based on the above-mentioned prediction.

[0125] FIG. 5E shows an example of basic data of the load level based on the actual response situation of the operator 33 .

[0126] 5(e), the actual response status of the operator 33 includes, for example, inability to respond, monitoring, watching, stop control or running restart control, remote control, etc. These actual response statuses are quantified as 0, 1, 2, 3, MAX, etc. for inability to respond, monitoring, watching, stop control or running restart control, and remote control, depending on the difficulty of the response or the time required for the response.

[0127] "Unable to respond" refers to a situation in which the operator 33 is unable to respond to a specific robot 10, for example, because the measured load exceeds the load level that the operator 33 can handle. "Monitoring" refers to the operator's normal support state, meaning that no particular concerns or obstacles are occurring with the robot 10 being supported. "Watching" refers to a state in which more careful supervision is required than monitoring, for example, because the robot 10 is at increased risk due to a task delay caused by the robot 10 tipping over. "Stop control" refers to control when an unexpected event occurs with the robot 10 or when the measured load exceeds the load that the operator 33 can handle. "Restart control" refers to control when the stopped robot 10 resumes traveling after such a situation is resolved.

[0128] FIG. 5F shows an example of basic data of the load level based on the content of the additional action taken by the operator 33 .

[0129] 5(f), depending on whether or not there is an additional response by the operator 33, for example, no additional response and an additional response accompanying an utterance by the robot 10 are quantified as 1, 2, etc. Note that the additional response by the operator 33 may also include additional responses accompanying other items, such as increasing the task execution speed of the robot 10 and executing multiple tasks by the robot 10, as described above. Therefore, the load level based on the content of the additional response by the operator 33 may also be set for these other items.

[0130] Here, the actual response status of the operator 33 can be determined from the control information for the robot 10 input by the operator 33 to the input / output device 30, as described above. Alternatively, as described above, the actual response status of the operator 33 may be determined from a video or the like of the operator 33. Similarly, the degree of burden based on the content of the additional response by the operator 33 may be calculated from the video or the like of the operator 33.

[0131] Based on the basic data defined as above, the server device 20 calculates and adjusts the measured load and calculates the service quality, for example, as shown in FIGS.

[0132] 6 to 23 are diagrams illustrating examples of the results of calculating the actual load, adjusting the actual load, and calculating the service quality by the server device 20 according to the embodiment. Of these, Figs. 6 to 11, 12 to 17, and 18 to 23 each illustrate a different example.

[0133] 6 to 23(a) show the calculation results of the actual measured load and the calculation results of the service quality, and Fig. 6 to 23(b) show the relationship between the predicted load, the actual measured load, and the load level that can be handled by the operator 33. In Fig. 6 to 23(b), the predicted load is indicated by a dashed line.

[0134] 6 to 11, four robots 10, numbered 1 to 4, that perform delivery tasks are assigned to one operator 33 of A. When the task of a robot 10 is delivery, the following formula (1) is used to calculate the service quality.

[0135] In the above formula (1), the scheduled delivery time is the time specified by the operation schedule information of the robot 10, and the scheduled arrival time is the arrival time at the delivery destination predicted from the robot information of the robot 10 at that time.

[0136] Furthermore, since the load degree that A's operator 33 can handle is 30, which is close to the maximum value, the lower limit threshold for load determination for A's operator 33 is set to 20, which is obtained by subtracting 10 from the load degree that A's operator 33 can handle, 30. The upper limit threshold for load determination is set to 30, which is equal to the load degree that A's operator 33 can handle.

[0137] FIG. 6 shows the robot information of robots 10 1 to 4, the response status of operator A 33, the measured load, the service quality, etc. at time t0.

[0138] 6A, at time t0, for example, looking at the situation of robot 10 1, robot 10 1 is traveling at a low speed in an environment with few traffic participants, and its travel distance is short. Furthermore, the scheduled delivery time for robot 10 1 is 12:30, and the estimated arrival time predicted from the current robot information is also 12:30, meaning there is no delay or the like relative to the scheduled delivery time specified in the operation schedule information for robot 10 1.

[0139] Furthermore, for example, at time t0, when the response status of operator A 33 regarding robot 10 is examined, operator A 33 is currently monitoring robot 10.

[0140] The server device 20 adds up the above-mentioned status of the robot 10 and the above-mentioned response status of the operator 33 of the robot A, and calculates a value of 4 as the load level at time t0. Furthermore, the server device 20 calculates a value of 100% as the service quality of the robot 10 using the scheduled delivery time and the scheduled delivery time using the above-mentioned formula (1).

[0141] Similarly, the server device 20 calculates the load levels of robots 2 to 4 at time t0 as 8, 5, and 7, respectively, based on the robot information of robots 2 to 4 at time t0 and the response status of operator A's 33 for each robot 10. Furthermore, the server device 20 calculates the service quality of robots 2 to 4 as 100% using the above-mentioned formula (1) from the scheduled delivery times and expected delivery times of each of robots 2 to 4.

[0142] Furthermore, the server device 20 adds up the load degrees 4, 8, 5, and 7 calculated for the robots 10 Nos. 1 to 4, respectively, to calculate a value of 24 as the measured load of the operator 33 No. A at time t0.

[0143] 6B, the predicted load at time t0 calculated in advance by the server device 20 and the actual load calculated from the actual measurement value at time t0 are approximately the same. Therefore, the server device 20 determines to maintain the current load of the operator 33 of A. In other words, in this case, no control change is made to the robots 10 1 to 4, and the control based on the initially set operation schedule information is maintained for these robots 10.

[0144] FIG. 7 shows the robot information of robots 10 1 to 4, the response status of operator A 33, the measured load, the service quality, etc. at time t1.

[0145] As shown in Figure 7(a), at time t1, all of the robots 10, for example, 1 to 4, are stopped. In addition, for robot 10 2, the response status of operator A 33 is remotely controlling it, which indicates that some kind of problem has occurred in robot 10 2 and operator A 33 is currently responding, which means that the other robots 10 1, 3, and 4 are in an unresponsive state.

[0146] In fact, the actual load at time t1 calculated by the server device 20 in the same manner as in Figure 6(a) above, based on the robot information of robots 10 1 to 4 and the response status of operator A 33 for each robot 10, also reaches its maximum value. As a result, operator A 33 temporarily suspends the other robots 10 1, 3, and 4. Furthermore, this causes delays in the estimated arrival times predicted from the robot information of robots 10 1 to 4 at time t1, and the service quality for each robot 10 drops to 95%.

[0147] 7B, at time t1, the measured load of operator A's 33 is approximately equal to the load that operator A's 33 can handle. This also indicates that the measured load of operator A's 33 is at its maximum. Even in this case, since the measured load does not exceed the load that operator A's 33 can handle, no change in control is made to robots 10 1 to 4, and control based on the initially set operation schedule information is maintained for these robots 10.

[0148] FIG. 8 shows the robot information of robots 10 1 to 4, the response status of operator A 33, the measured load, the service quality, etc. at time t2.

[0149] As shown in FIG. 8(a), at time t2, robots 10 1 to 4 have resumed running, and it can be seen that the obstacle at time t1 has been resolved.

[0150] The server device 20 calculates a value of 23 as the actual load of the operator 33 of A at time t2 based on the robot information of the robots 10 1 to 4 at time t2 and the response status of the operator 33 of A for each robot 10. The server device 20 also calculates a value of 95% as the service quality of each of the robots 10 1 to 4.

[0151] 8B, the predicted load at time t2 calculated in advance by the server device 20 and the actual load calculated from the actual measurement value at time t2 are approximately the same. Therefore, the server device 20 determines to maintain the current load of the operator A 33 even at time t2.

[0152] FIG. 9 shows the robot information of robots 10 1 to 4, the response status of operator A 33, the measured load, the service quality, etc. at time t3.

[0153] 9A, at time t3, for example, the number of traffic participants at the current positions of robots 10 2 and 4 has decreased compared to the past history, and robots 10 2 and 4 have been able to travel more smoothly than expected. Accordingly, the response status of operator A 33 for robots 10 2 and 4 has also become monitoring, which means a normal support state.

[0154] Therefore, the actual load calculated by the server device 20 at time t3 based on the robot information of robots 10 1 to 4 and the response status of operator A 33 for each robot 10 is 20, which is below the lower limit threshold. In Figure 9(a), it is assumed that this situation continues throughout the period indicated by time t3.

[0155] Furthermore, the server device 20 calculated the service quality of robots 10 1 to 4 as 95% for all of them, which indicates that there is room for further improvement in the service quality of these robots 10.

[0156] As shown in FIG. 9B, the actual load calculated from the actual measurement value at time t3 is significantly lower than the predicted load at time t3 calculated in advance by the server device 20.

[0157] In response to the above situation, the server device 20 makes a decision to implement control to increase the load on the operator 33 of A on at least one of the robots 10 (1 to 4).

[0158] FIG. 10 shows the robot information of robots 10 1 to 4, the response status of operator A 33, the measured load, the service quality, etc. at time t4.

[0159] 10A, at time t4, based on the determination result of the server device 20 at time t3, the travel speeds of robots 10 1 to 4 are all increased by one level to increase the load on operator 33 of A. As a result, at time t4, the measured load exceeds the lower threshold and increases to 24. In addition, the delay in the predicted scheduled arrival time is eliminated, and the service quality of robots 10 1 to 4 is also improved to 100%.

[0160] 10B, the actual measured load calculated from the actual measured value at time t4 exceeds the predicted load at time t4 calculated in advance by the server device 20, but does not exceed the load level that can be handled by the operator 33 of A. Therefore, the server device 20 determines to maintain the current load of the operator 33 of A at time t4.

[0161] As described above, in the server device 20 of the embodiment, it is possible to increase the load on the operator 33 to an appropriate value by changing the control of the robot 10 that is the cause of the underload on the operator 33, as in the robots 10 of the examples 2 and 4 in Fig. 9. Furthermore, in the server device 20 of the embodiment, it is also possible to increase the load on the operator 33 by changing the control of a robot 10 that is different from the robot 10 that is the cause of the underload on the operator 33, as in the robots 10 of the examples 1 and 3 in Fig. 10.

[0162] FIG. 11 shows the robot information of robots 10 1 to 4, the response status of operator A 33, the measured load, the service quality, etc. at time t5.

[0163] 11(a), robot 10 1 is in the process of handing over the delivery package, and operator A 33 is watching robot 10 1 more carefully than usual. Based on the robot information of robots 10 1 to 4 at time t5 and the response status of operator A 33 for each robot 10, server device 20 calculates a value of 22 as the actual load of operator A 33 at time t5. Server device 20 also calculates a value of 100% as the service quality of robots 10 1 to 4.

[0164] 11B, the actual load calculated from the actual measured value at time t5 is slightly lower than the predicted load at time t5 calculated in advance by the server device 20, but is not below the lower limit threshold. Therefore, the server device 20 determines to maintain the current load of the operator A 33 even at time t5.

[0165] 12 to 17, four robots 10, numbered 1 to 4, that perform security tasks are assigned to one of the operators 33 of B. When the task of the robot 10 is security, the following formula (2) is used to calculate the service quality.

[0166] In the above formula (2), the planned security range is the security range defined by the planned operation information of the robot 10, and the planned completion range is the final security range predicted from the robot information of the robot 10 at that time.

[0167] Furthermore, since the load level that operator B's operator 33 can handle is quite low at 6, the lower limit threshold for load determination for operator B's operator 33 is set to 4, which is obtained by subtracting 2 from the load level that operator B's operator 33 can handle, 6. The upper limit threshold for load determination is set to 6, which is the same as the load level that operator B's operator 33 can handle.

[0168] FIG. 12 shows the robot information of robots 10 1 to 4 at time t0, the response status of operator 33 of B, the measured load, the service quality, etc.

[0169] As shown in Figure 12(a), at time t0, for example, looking at the situation of robot 10, robot 10 is traveling at a medium speed in an environment with a normal number of traffic participants, and the security range per unit time is small. Also, the planned security range for robot 10 is 20,000 m ２ The estimated completion range based on the current robot information is also 20,000m. ２ Thus, the planned security range defined by the operation schedule information of the robot 10 can be maintained.

[0170] Furthermore, for example, at time t0, when the response status of operator B 33 regarding robot 10 is examined, operator B 33 is currently gazing at robot 10.

[0171] The server device 20 multiplies the above-mentioned status regarding robot 10 No. 1 by the above-mentioned response status of operator 33 No. B, and calculates a numerical value of 1.8 as the load level at time t0. Furthermore, the server device 20 calculates a numerical value of 100% as the service quality by robot 10 No. 1 using the above-mentioned formula (2) from the planned security range and the planned completion range.

[0172] Similarly, the server device 20 calculates the load levels of robots 2 to 4 at time t0 as 0.9, 1, and 0.9, respectively, based on the robot information of robots 2 to 4 at time t0 and the response status of operator B 33 for each robot 10. Furthermore, the server device 20 calculates the service quality of robots 2 to 4 as 100% using the above-mentioned formula (2) from the planned security range and planned completion range of each of robots 2 to 4.

[0173] Furthermore, the server device 20 adds up the load degrees 1.8, 0.9, 1, and 0.9 calculated for the robots 10 1 to 4, respectively, to calculate a value of 4.6 as the measured load of the operator 33 of B at time t0.

[0174] 12(b), the predicted load at time t0 calculated in advance by the server device 20 and the actual load calculated from the actual measurement value at time t0 are approximately the same. Therefore, the server device 20 determines to maintain the current load of the operator 33 of B. In other words, in this case, no control change is made to the robots 10 1 to 4, and the control based on the initially set operation schedule information is maintained for these robots 10.

[0175] FIG. 13 shows the robot information of robots 10 1 to 4, the response status of operator 33 of B, the measured load, the service quality, etc. at time t1.

[0176] 13A, at time t1, all of the robots 10, for example, 1 to 4, are stopped. In addition, for robot 10 2, the response status of operator B 33 is remotely controlled, which indicates that some kind of problem has occurred in robot 10 2 and operator B 33 is currently responding, which means that the other robots 10 1, 3, and 4 are unable to respond.

[0177] In fact, the actual load at time t1 calculated by the server device 20 in the same manner as in Figure 12(a) above, based on the robot information of robots 10 1 to 4 and the response status of operator B 33 for each robot 10, also reaches its maximum value. As a result, operator B 33 temporarily suspends the other robots 10 1, 3, and 4. Furthermore, as a result, the planned completion range of security work predicted from the robot information of robots 10 1 to 4 at time t1 is smaller than the planned security range specified in the operation schedule information, and the service quality for each robot 10 has dropped to 90%.

[0178] 13(b), at time t1, the measured load of operator B's 33 is approximately equal to the load that operator B can handle. This also shows that the measured load of operator B's 33 is at its maximum value. Even in this case, since the measured load does not exceed the load that operator B's 33 can handle, no change in control is made to robots 10 1 to 4, and control based on the initially set operation schedule information is maintained for these robots 10.

[0179] FIG. 14 shows the robot information of robots 10 1 to 4, the response status of operator 33 of B, the measured load, the service quality, etc. at time t2.

[0180] As shown in FIG. 14(a), at time t2, robots 10 1 to 4 have resumed running, and it can be seen that the obstacle at time t1 has been resolved.

[0181] The server device 20 calculates a value of 4.7 as the actual load of the operator 33 of B at time t2 based on the robot information of the robots 10 1 to 4 at time t2 and the response status of the operator 33 of B for each robot 10. The server device 20 also calculates a value of 90% as the service quality of each of the robots 10 1 to 4.

[0182] 14B, the predicted load at time t2 calculated in advance by the server device 20 and the actual load calculated from the actual measurement value at time t2 are approximately the same. Therefore, the server device 20 determines to maintain the current load of the operator 33 of B even at time t2.

[0183] FIG. 15 shows the robot information of robots 10 1 to 4, the response status of operator 33 of B, the measured load, the service quality, etc. at time t3.

[0184] As shown in Figure 15(a), at time t3, for example, the number of traffic participants at the current location of robot 10 1 has decreased compared to past history, and robot 10 1 was able to travel more smoothly than expected.

[0185] Also, for example, it is assumed that the expected remote control request is not made at the current position of the robot 10 of 3. Accordingly, the response status of the operator 33 of B is also monitoring, which means a normal support status.

[0186] Therefore, the actual load calculated by the server device 20 at time t3 based on the robot information of robots 10 1 to 4 and the response status of operator B 33 for each robot 10 is 3.6, which is below the lower limit threshold. In Figure 15(a), it is assumed that this situation continues throughout the period indicated by time t3.

[0187] Furthermore, the server device 20 calculated the service quality of robots 10 1 to 4 as 90% for all of them, which indicates that there is room for further improvement in the service quality of these robots 10.

[0188] As shown in FIG. 15B, the actual load calculated from the actual measurement value at time t3 is significantly lower than the predicted load at time t3 calculated in advance by the server device 20.

[0189] In response to the above situation, the server device 20 makes a decision to implement control to increase the load on the operator 33 of B on at least one of the robots 10 (1 to 4).

[0190] FIG. 16 shows the robot information of robots 10 1 to 4, the response status of operator 33 of B, the measured load, the service quality, etc. at time t4.

[0191] As shown in Figure 16 (a), at time t4, based on the judgment result of the server device 20 at time t3, in order to increase the load on the operator 33 of B, the running speeds of robots 10 1 and 3 are both increased by one step, and the security range per unit time for robot 10 is expanded.

[0192] However, at time t4, the number of traffic participants at the current positions of robots 10 2 and 4 has increased by one step. Therefore, the response of operator 33 of B to robots 10 2 and 4 has changed from monitoring to watching.

[0193] Due to the above-mentioned change in control for robots 10 No. 1 and No. 3, at time t4, the service quality of robots 10 No. 1 and No. 3 has improved to 200% and 100%, respectively. On the other hand, due to the change in control for robots 10 No. 1 and No. 3 and the change in the situation of robots 10 No. 2 and No. 4, the measured load has increased to 6.2, exceeding the upper threshold.

[0194] As shown in Figure 16 (b), the actual load calculated from the actual measured value at time t4 exceeds the predicted load at time t4 calculated in advance by the server device 20, and also exceeds the load that operator B's operator 33 can handle.

[0195] Therefore, at time t4, the server device 20 determines to implement control to reduce the load on the operator 33 of B on at least one of the robots 10 of 1 to 4.

[0196] FIG. 17 shows the robot information of robots 10 1 to 4, the response status of operator 33 of B, the measured load, the service quality, etc. at time t5.

[0197] As shown in Figure 17(a), at time t5, control is performed to reduce the load on operator 33 of B based on the determination result of server device 20 at time t4. At this time, rather than restoring the control of robots 10 of 1 and 3, which was controlled to increase the load on operator 33 of B in Figure 16 described above, a change in control is made to robots 10 of 2 and 4. Specifically, at time t5, the speeds of robots 10 of 2 and 4 are each reduced by two stages.

[0198] As a result, at time t5, the service quality of robots 10 2 and 4 further declines from 90% to 77% and 83%, respectively. Meanwhile, at time t5, the actual load of operator 33 B has been reduced to 5.6, which is below the upper threshold. Therefore, even at time t5, the server device 20 determines to maintain the current load of operator 33 A.

[0199] As described above, the server device 20 of the embodiment is able to perform control to return the excessive load on the operator 33 to an appropriate value by allowing a decrease in service quality. In addition, in this case, the server device 20 of the embodiment can change the control of other robots 10, rather than the control of the robot 10 that caused the overload on the operator 33, as in the example of robots 10 1 and 3 in FIG. 17 .

[0200] 18 to 23, four robots 10, numbered 1 to 4, that perform a cleaning task are assigned to one operator 33 of C. When the task of the robot 10 is cleaning, the following formula (3) is used to calculate the service quality.

[0201] In the above formula (3), the planned cleaning range is the cleaning range specified by the robot 10's operation schedule information, and the planned completion range is the final cleaning range predicted from the robot information of the robot 10 at that time.

[0202] Furthermore, since the load level that the operator 33 of C can handle is quite low at 6, the lower limit threshold for load determination for the operator 33 of C is set to 4, which is obtained by subtracting 2 from the load level that the operator 33 of C can handle, 6. The upper limit threshold for load determination is set to 6, which is the same as the load level that the operator 33 of C can handle.

[0203] FIG. 18 shows the robot information of robots 10 1 to 4, the response status of operator C 33, the measured load, the service quality, etc. at time t0.

[0204] As shown in FIG. 18(a), at time t0, robots 10 1 to 4 are all traveling toward the cleaning site.

[0205] Also, for example, looking at the situation regarding the robot 10, the robot 10 is traveling at a low speed in an environment with a moderate number of traffic participants, and the cleaning range per unit time is small. Also, the planned cleaning range for the robot 10 is 20,000 m ２ In addition, based on the current robot information, it is expected that the robot will arrive at the cleaning site at the scheduled time, and therefore the predicted completion range is also 20,000m. ２ and the expected completion range defined by the operation schedule information of the robot 10 can be maintained.

[0206] Furthermore, for example, at time t0, when the response status of operator C 33 regarding robot 10 is examined, operator C 33 is currently gazing at robot 10.

[0207] The server device 20 multiplies the above-mentioned status of the robot 10 by the above-mentioned response status of the operator 33 of C, and calculates a value of 1.6 as the load level at time t0. Furthermore, the server device 20 calculates a value of 100% as the service quality of the robot 10 using the above-mentioned formula (3) from the planned cleaning range and the planned completion range.

[0208] Similarly, the server device 20 calculates the load levels of robots 2 to 4 at time t0 as 1.0, 0.7, and 1.0, respectively, based on the robot information of robots 2 to 4 at time t0 and the response status of operator C 33 for each robot 10. Furthermore, the server device 20 calculates the service quality of robots 2 to 4 as 100% using the above-mentioned formula (3) from the planned cleaning range and planned completion range of each of robots 2 to 4.

[0209] Furthermore, the server device 20 adds up the load degrees 1.6, 1.0, 0.7, and 1.0 calculated for the robots 10 1 to 4, respectively, to calculate a value of 4.3 as the measured load of the operator 33 C at time t0.

[0210] 18(b), the predicted load at time t0 calculated in advance by the server device 20 and the actual load calculated from the actual measurement value at time t0 are approximately the same. Therefore, the server device 20 determines to maintain the current load of the operator 33 of C. In other words, in this case, no control change is made to the robots 10 1 to 4, and the control based on the initially set operation schedule information is maintained for these robots 10.

[0211] FIG. 19 shows the robot information of robots 10 1 to 4, the response status of operator C 33, the measured load, the service quality, etc. at time t1.

[0212] As shown in FIG. 19(a), it is assumed that at time t1, none of the robots 10, 1 to 4, have arrived at the cleaning site yet.

[0213] Also, at time t1, all of the robots 10, for example, 1 to 4, are stopped. In addition, for robot 10 2, the response status of operator C 33 is remotely controlled, which indicates that some kind of problem has occurred in robot 10 2 and operator C 33 is currently responding, which means that the other robots 10 1, 3, and 4 are in an unresponsive state.

[0214] In fact, the actual load at time t1 calculated by the server device 20 in the same manner as in FIG. 19(a) above, based on the robot information for robots 10 1 to 4 and the response status of operator C 33 for each robot 10, also reached its maximum value. Therefore, operator C 33 temporarily stopped the other robots 10 1, 3, and 4. Furthermore, as a result, the robot information for robots 10 1 to 4 at time t1 predicted a delay in their arrival at the cleaning site, and the predicted planned cleaning completion range was shorter than the planned cleaning range specified in the operation schedule information. Therefore, the service quality for each robot 10 dropped to 95%.

[0215] 19(b), at time t1, the measured load of operator C's 33 is approximately equal to the load that operator C can handle. This also shows that the measured load of operator C's 33 is at its maximum value. Even in this case, since the measured load does not exceed the load that operator C's 33 can handle, no change in control is made to robots 10 1 to 4, and control based on the initially set operation schedule information is maintained for these robots 10.

[0216] FIG. 20 shows the robot information of robots 10 1 to 4, the response status of operator C 33, the measured load, the service quality, etc. at time t2.

[0217] As shown in FIG. 20(a), at time t2, robots 10 1 to 4 have resumed running, and it can be seen that the obstacle at time t1 has been resolved.

[0218] The server device 20 calculates a value of 5.3 as the actual load of the operator 33 of C at time t2 based on the robot information of the robots 10 1 to 4 at time t2 and the response status of the operator 33 of C for each robot 10. The server device 20 also calculates a value of 95% as the service quality of each of the robots 10 1 to 4.

[0219] 20B, the predicted load at time t2 calculated in advance by the server device 20 and the actual load calculated from the actual measurement value at time t2 are approximately the same. Therefore, the server device 20 determines to maintain the current load of the operator 33 of C even at time t2.

[0220] FIG. 21 shows the robot information of robots 10 1 to 4, the response status of operator C 33, the measured load, the service quality, etc. at time t3.

[0221] As shown in FIG. 21(a), it is assumed that at time t3, all of the robots 10, 1 to 4, are still traveling toward the cleaning site.

[0222] Also, at time t3, for example, the number of traffic participants at the current positions of robots 10 1 to 3 is less than in the past history, and robots 10 1 to 3 are able to travel more smoothly than expected.

[0223] Also, for example, it is assumed that the expected remote control request is not made at the current position of the robot 10 of 3. Accordingly, the response status of the operator 33 of C is also monitoring, which means a normal support status.

[0224] Therefore, the actual load calculated by the server device 20 at time t3 based on the robot information of robots 10 1 to 4 and the response status of operator C 33 for each robot 10 is 3.4, which is below the lower limit threshold. In Figure 21(a), it is assumed that this situation continues throughout the period indicated by time t3.

[0225] Furthermore, as for the service quality of robots 10 1 to 4, as mentioned above, delays in arrival at the cleaning site are expected, so the server device 20 calculates a value of 95% for each, which indicates that there is room for further improvement in the service quality of these robots 10.

[0226] As shown in FIG. 21B, the actual load calculated from the actual measurement value at time t3 is significantly lower than the predicted load at time t3 calculated in advance by the server device 20.

[0227] In response to the above situation, the server device 20 determines to implement control to increase the load on the operator 33 of C on at least one of the robots 10 of 1 to 4.

[0228] FIG. 22 shows the robot information of robots 10 1 to 4, the response status of operator C 33, the measured load, the service quality, etc. at time t4.

[0229] 22(a), at time t4, based on the determination result of the server device 20 at time t3, in order to increase the load on the operator 33 of C, the running speeds of the robots 10 1 to 4 are all increased by one step, and the robot 10 1 is made to perform an additional speaking task, and the robot 10 3 is made to perform an additional guard task. As described above, making the robots 10 perform additional tasks also increases the need for additional responses by the operator 33.

[0230] As a result, at time t4, the measured load exceeds the lower threshold and increases to 5.4. In addition, the delay in arrival at the cleaning site and the reduction in the predicted completion range are resolved, and the service quality of robots 10 2 and 4 also improves to 100%. Furthermore, the service quality of robots 10 1 and 2, which have been made to perform additional measures, increases to 100% + α.

[0231] 22(b), the actual measured load calculated from the actual measured value at time t4 exceeds the predicted load at time t4 calculated in advance by the server device 20, but does not exceed the load level that can be handled by the operator 33 of C. Therefore, the server device 20 determines to maintain the current load of the operator 33 of C at time t4.

[0232] As described above, in the server device 20 of the embodiment, it is possible to have any of the robots 10 that have caused an underload on the operator 33 perform an additional task, such as the robots 10 1 to 3 in the example of Fig. 21. Furthermore, in the server device 20 of the embodiment, it is also possible to have a robot 10 other than the robot 10 that has caused an underload on the operator 33 perform an additional task.

[0233] FIG. 23 shows the robot information of robots 10 1 to 4, the response status of operator 33 of C, the measured load, the service quality, etc. at time t5.

[0234] As shown in Figure 23 (a), at time t5, robot 10 No. 3 arrives at the cleaning site, so the server device 20 causes robot 10 No. 3 to end guarding the additional task and start cleaning.

[0235] Furthermore, the server device 20 calculates a value of 4.4 as the actual load of the operator 33 of C at time t5 based on the robot information of the robots 10 1 to 4 at time t5 and the response status of the operator 33 of C for each robot 10. The server device 20 also calculates a value of 100% as the service quality of each of the robots 10 1 to 4.

[0236] 23B, the actual load calculated from the actual measured value at time t5 is slightly lower than the predicted load at time t5 calculated in advance by the server device 20, but is not below the lower limit threshold. Therefore, the server device 20 determines to maintain the current load of the operator 33 of C even at time t5.

[0237] (Example of Processing by Server Device) Next, an example of control processing of the robot 10 by the server device 20 according to the embodiment will be described with reference to Fig. 24. Fig. 24 is a flow diagram illustrating an example of the procedure of control processing of the robot 10 performed by the server device 20 according to the embodiment.

[0238] 24 , the operator load prediction unit 23 of the server device 20 calculates a predicted load by predicting a load that may occur on the operator 33 based on the operation schedule information in the operation schedule information database 21 and the operator information in the operator information database 22 (step S101). At this time, the operator load prediction unit 23 also calculates a lower limit threshold, an upper limit threshold, and a judgment value for the duration of a predetermined state, which are used to judge the load on the operator 33.

[0239] Furthermore, the server device 20 starts the operation of the plurality of robots 10 in accordance with the operation schedule information (step S102). More specifically, in accordance with the operation schedule information, the control information generator 27 generates control information for controlling each robot 10, and the control information output unit 28 outputs the control information to each robot 10. As a result, each robot 10 starts a task in accordance with the operation schedule information.

[0240] The information acquisition unit 24 of the server device 20 acquires robot information from each robot 10 that has started operation (step S103). At this time, the information acquisition unit 24 also acquires service information for the operating robot 10. The operator load measurement unit 25 calculates the actual measured load actually imposed on the operator 33 based on the robot information acquired from the operating robot 10 and the response status of the operator 33 obtained from input information from the input / output device 30, etc. (step S104).

[0241] The determination unit 26 of the server device 20 compares the measured load with the predicted load and determines whether the measured load is equal to or less than the predicted load (step S105). If the measured load is equal to or less than the predicted load (step S105: Yes), the determination unit 26 determines whether the measured load is equal to or less than a lower threshold (step S106). If the measured load is equal to or less than the lower threshold (step S106: Yes), the server device 20 performs control to increase the load on the operator 33 (step S107).

[0242] More specifically, when the measured load is equal to or less than the lower limit threshold (step S106: Yea), the control information generator 27 of the server device 20 generates control information that increases the load on the operator 33, and the control information output unit 28 outputs the control information to the target robot 10. As a result, the target robot 10 operates under a control different from the control currently set. As a result, the load on the operator 33 increases.

[0243] The server device 20 also recalculates the actual load of the operator 33 after the load-increasing control has been performed (step S108). The actual load is calculated in the same manner as in the processes of steps S103 and S104 described above. At this time, the determination unit 26 may also calculate the service quality of each robot 10.

[0244] On the other hand, when the measured load is greater than the predicted load (step S105: No), the determining unit 26 determines whether the measured load is greater than the upper threshold (step S110). When the measured load is greater than the upper threshold (step S110: Yes), the server device 20 performs control to reduce the load on the operator 33 (step S111).

[0245] More specifically, if the measured load exceeds the upper threshold (step S110: Yes), the control information generation unit 27 of the server device 20 generates control information that reduces the load on the operator 33, and the control information output unit 28 outputs the control information to the target robot 10. As a result, the target robot 10 operates under a control different from the control currently set. Alternatively, as a result, the load on the operator 33 is reduced.

[0246] If the measured load is above the lower threshold (step S106: No) or equal to or less than the upper threshold (step S110: No), the server device 20 does not perform any of the processes in steps S107 to S108 and S111.

[0247] In the above process, the server device 20 appropriately monitors whether the task of each robot 10 has been completed (step S109). If at least one of the robots 10 is continuing the task (step S109: No), the server device 20 repeats the process from step S103. If the tasks of all the robots 10 have been completed (step S109: Yes), the process ends.

[0248] This completes the control process for the robot 10 performed by the server device 20 of the embodiment.

[0249] (Summary) There is a technology that remotely controls an autonomously moving robot from a server device with the support of an operator. The operator supports the robot in response to remote control requests from the robot via the server device, etc. To date, technology has been developed that keeps the operator's load within an appropriate level when the operator's load is likely to exceed the load level that can be handled.

[0250] However, even if the operator's load is excessively reduced when the robot is operating more smoothly than expected, the above technology does not provide control to appropriately increase the operator's load.

[0251] According to the control method in the server device 20 of the embodiment, when the situation in which the measured load is equal to or lower than the lower threshold continues for a predetermined period of time, at least one of the robots 10 is controlled to increase the load on the operator 33. In this way, by appropriately increasing the load on the operator 33, the quality of service provided by the robot 10 can be improved.

[0252] According to the control method in the server device 20 of the embodiment, at least one of the lower limit threshold of the actual load and the judgment value for the duration for which the actual load is equal to or less than the lower limit threshold is determined based on operator information indicating the load level that the operator 33 can handle. This allows the lower limit threshold of the actual load and the judgment value for the duration to be set appropriately for each operator 33. Furthermore, for an operator 33 with a high level of skill, the lower limit threshold is set higher, making it easier to control the load on the operator 33 and to lengthen the duration of such control. This allows for further improvement in service quality.

[0253] According to the control method in the server device 20 of the embodiment, the control to increase the load on the operator 33 includes at least one of the following: control to increase the traveling speed of at least one robot 10; control to change the traveling route of at least one robot 10 to a route that, for example, shortens the traveling distance but increases the monitoring load on the operator 33; control to expand the task execution range of at least one robot 10; and control that requires additional action by the operator 33 for at least one robot 10. This makes it possible to further improve the quality of service.

[0254] According to the control method in the server device 20 of the embodiment, at least one of the multiple robots 10 is controlled to further increase, maintain, or decrease the load on the operator 33 based on the determination result of the adjusted load after control that increases the load on the operator 33 is implemented. In this way, even after adjusting the load on the operator 33, by continuously monitoring and feeding back the actual measured load such as the adjusted load, the load on the operator 33 can be maintained at an appropriate level, thereby further improving the quality of service provided by the robot 10.

[0255] According to the control method in the server device 20 of the embodiment, control to increase the load on the operator 33 is performed on the robot 10 that has caused the measured load to remain below the lower threshold for a predetermined period of time. This directly resolves the cause of the decrease in the measured load on the operator 33, and appropriately increases the load on the operator 33.

[0256] According to the control method in the server device 20 of the embodiment, control to increase the load on the operator 33 is performed on the robot 10 whose service quality is below a predetermined threshold. By performing such control, the service quality of the robot 10 can be further improved.

[0257] According to the control method in the server device 20 of the embodiment, if the task of the robot 10 is delivery, the service quality is calculated by comparing the scheduled delivery time specified in the operation schedule information of the robot 10 with the scheduled arrival time predicted based on the robot information of the robot 10; if the task of the robot 10 is security, the service quality is calculated by comparing the scheduled security area specified in the operation schedule information of the robot 10 with the scheduled completion area predicted based on the robot information of the robot 10; if the task of the robot 10 is mobile sales, the service quality is calculated by comparing the target product sales volume or target sales amount specified in the operation schedule information of the robot 10 with the actual product sales volume or sales amount predicted based on the robot information of the robot 10; and if the task of the robot 10 is cleaning, the service quality is calculated by comparing the scheduled cleaning area specified in the operation schedule information of the robot 10 with the scheduled completion area predicted based on the robot information of the robot 10.

[0258] This makes it possible to properly calculate and understand the service quality of each robot 10, and then properly control each robot 10. Therefore, the service quality provided by the robot 10 can be further improved.

[0259] In the above-described embodiment, the control for increasing the load on the operator 33 is performed by changing the control of at least one of the robots 10 under the control of the operator 33. However, the method for increasing the load on the operator 33 is not limited to this.

[0260] For example, in order to increase the workload of the operator 33, the number of robots 10 under the control of the operator 33 may be temporarily increased. If an excessive decrease in the workload of the operator 33 is caused, for example, by a failure of one of the robots 10 under the control of the operator 33, the number of robots 10 may be permanently increased to increase the workload of the operator 33. Alternatively, an operator 33 with a lighter workload may assist another operator 33 with a heavier workload.

[0261] As described above, when adding a robot 10 under the jurisdiction of an operator 33, a robot 10 under the control of another operator 33 may be added. In this case, the other operator 33 can select an operator 33 with a higher actual measured load from among the multiple operators 33. Furthermore, the robot 10 to be added can be a robot 10 with a declining service quality from among the robots 10 under the control of the other operator 33.

[0262] In the above embodiment, the measured load is calculated for each individual operator 33. However, the overall measured load of the multiple operators 33 may be determined based on the average value of the measured loads of all the multiple operators 33, and the measured loads of the multiple operators 33 may be adjusted mutually. Similarly, the service quality of all the robots 10 under the control of each individual operator 33 may be compared, and mutual adjustments may be made to improve the service quality of the robots 10 with low service quality.

[0263] In the above embodiment, when the measured load of the operator 33 is equal to or lower than the lower limit threshold for a predetermined period of time, control is performed to increase the load of the operator 33. However, whether or not to perform control to increase the load of the operator 33 may be determined based on a determination condition other than the above.

[0264] In this case, as an example, as an additional determination condition, the server device 20 may refer to the past load history of the operator 33. If, based on the load history of the operator 33, the measured load of the operator 33 has continuously exceeded the upper threshold for a predetermined period, the server device 20 can determine not to perform control to increase the load of the operator 33, even if the measured load of the operator 33 subsequently falls below the lower threshold for a predetermined period.

[0265] As another example, whether or not to perform control to increase the load on the operator 33 may be determined based on a prediction of the period during which the actual load on the operator 33 will be equal to or less than the lower threshold. The period during which the actual load on the operator 33 will be equal to or less than the lower threshold can be predicted, for example, from the current situation in which the robot 10 is placed.

[0266] In other words, for example, if the number of traffic participants at the point where the robot 10 is currently moving is fewer than the number predicted from the operation schedule of the robot 10, and if this situation is predicted to continue in the future, it can be predicted that the actual measured load of the operator 33 will remain below the lower threshold for a period of time while passing through that area.

[0267] The current situation of the robot 10 can be determined from, for example, the information used to calculate the actual measured load of the operator 33, that is, the robot information and service information acquired from multiple robots 10.

[0268] When predicting a period during which the actual load of the operator 33 will be equal to or less than the lower limit threshold, if the predicted period is equal to or longer than the above-mentioned predetermined period, the server device 20 can perform control to increase the load of the operator 33. In this case, the server device 20 may also perform control to increase the load of the operator 33 only during the above-mentioned predicted period.

[0269] Furthermore, in the above-described embodiment, each item such as operation schedule information and operator information that are referenced when calculating the predicted load, and each item such as robot information and operator response status that are referenced when calculating the actual load, are quantified by being converted into binary, ternary, etc. However, these reference items may also be quantified linearly.

[0270] In the above embodiment, the task of the operator 33 is solely to remotely support the robot 10. However, the operator 33 may have other tasks besides directly supporting the robot 10, such as recording the operation history of the robot 10 and the execution history of various operations.

[0271] In this case, the decision as to whether to increase the load on the operator 33 can be made by taking into consideration not only the support task of the robot 10 by remote control but also the load status of other tasks assigned to the operator 33. In other words, when the load on the operator 33 for both the support task of the robot 10 by remote control and the other tasks is low, the server device 20 can control the operator 33 to increase the load of the support task of the robot 10 by remote control.

[0272] In the above-described embodiment, the actual workload of the operator 33 is calculated based on the robot information, service information, and the like acquired from the robot 10 under the control of the operator 33. However, the method for calculating the actual workload of the operator 33 is not limited to this.

[0273] As an example, the actual load of the operator 33 may be calculated based on the physical and mental load conditions of the operator 33 in addition to the above. The physical and mental load of the operator 33 can be calculated from biological information such as the pulse, heart rate, breathing, sweat, and body temperature of the operator 33 by having the operator 33 wear a vital sensor capable of measuring such biological information.

[0274] (Modification 1) Next, a server device according to Modification 1 of the embodiment will be described with reference to Fig. 25. The server device according to Modification 1 differs from the embodiment described above in that it presents information related to changes in control of the robot 10 to the operator 33.

[0275] FIG. 25 is a schematic diagram showing an example of various display screens that the server device according to the first modification of the embodiment causes the input / output device 30 to display.

[0276] As shown in Figures 25(a) to 5(c), the server device of variant example 1 may display information regarding changes in control on the output section 31 (see Figure 2) of the input / output device 30 when performing control to increase the load on the operator 33 based on the comparison result between the actual load and the predicted load.

[0277] In the example of FIG. 25( a ), the server device of the first modification displays how to change the control of the robot 10 in order to increase the load on the operator 33 and improve the quality of service.

[0278] In the example of Figure 25 (b), the server device of variant example 1 displays in more detail how the control of the robot 10 will be changed in order to increase the load on the operator 33 and improve service quality, by quantifying the content of the changes, for example.

[0279] In the example of Figure 25 (c), the server device of variant example 1 displays how the control of the robot 10 will be changed, along with the reason for changing the control, in order to increase the load on the operator 33 and improve service quality.

[0280] 25(d), when changing the control of the robot 10, the server device of Modification 1 may display, on the output unit 31 of the input / output device 30, information regarding the change in control, as well as a message requesting permission from the operator 33 to change the control of the robot 10. When the operator 33 gives permission to change the control of the robot 10, the server device of Modification 1 changes the control of the robot 10 so as to increase the load on the operator 33.

[0281] In the above embodiment, when the actual load of the operator 33 is within a range above the lower limit threshold set lower than the predicted load and below the upper limit threshold set higher than the predicted load, the load of the operator 33 is maintained as is. However, for example, in the configuration of Fig. 25(d), even when the actual load is above the lower limit threshold and below the upper limit threshold, the server device of Modification 1 may be able to adjust the load of the operator 33 within a range above the lower limit threshold and below the upper limit threshold.

[0282] Specifically, the server device of Modification 1 may propose to the operator 33 to reduce the load on the condition that the load remains above the lower threshold. Also, the server device of Modification 1 may propose to the operator 33 to increase the load on the condition that the load does not exceed the upper threshold. If the operator 33 accepts these proposals, the server device of Modification 1 increases or decreases the load on the operator 33 according to the content of the proposal.

[0283] (Variation 2) In the above-described embodiment, the predicted workload of the operator 33 is calculated using the values ​​in Figures 3(a) to 3(c) based on a previously established operation schedule for the robot 10. However, the method for calculating the predicted workload of the operator 33 is not limited to the method in the above-described embodiment.

[0284] In the following Modification 2, an example of calculating the predicted load of the operator 33 using a method different from that of the above-described embodiment will be described with reference to Figures 26 to 31. Note that in the following description, the same components as those in the above-described embodiment will be denoted by the same reference numerals, and the description thereof may be omitted.

[0285] 26 to 28 show examples of basic data that are referred to when the server device according to the second modification calculates a predicted load.

[0286] 26 to 28, also in the server device of Modification 2, the load degrees at multiple locations, the load degrees based on the operation schedule information of each robot 10, and the load degrees based on the operator information of each operator 33 are quantified in advance. However, in the server device of Modification 2, the way in which this information is separated and quantified differs from the embodiment described above.

[0287] Fig. 26(a) shows an example of basic data of load levels at multiple points included in the planned travel route of each robot 10. In the example of Fig. 26(a), the load levels at each point are set for each time period of the day.

[0288] At a given location, the number of traffic participants may vary depending on the time of day, such as a relatively low number of traffic participants in the morning, an increase in the number of shoppers during the day, and an increase in the number of traffic participants in the evening due to children returning home from school. Furthermore, the number of remote control requests may also vary in accordance with the fluctuation in the number of traffic participants. Thus, in Modification 2, multiple load levels are set, for example, for each time period or each day of the week, taking into account the actual conditions at each location.

[0289] 26(b) is an example of basic data of load levels between a plurality of points. That is, in FIG. 26(b), the load levels that may occur as each robot 10 moves from one predetermined point to another predetermined point, such as from point A to point B, from point A to point C, or from point C to point E, are set. In this way, in Modification 2, not only the load level for each point but also the load level associated with movement between points is set.

[0290] Fig. 27 shows an example of basic data of the load degree based on the operation schedule information of each robot 10. In response to the addition of the item of the load degree associated with movement between multiple points in Fig. 26(b) to the load degrees at multiple points, in Modification 2, as shown in Fig. 27, the load degree based on the operation schedule information of each robot 10 is quantified with a focus on the load degree that may arise depending on the running speed of each robot 10. Furthermore, in Modification 2, the running speed of each robot 10 includes low speed, medium speed, high speed, and also a stopped state.

[0291] Fig. 28 shows an example of basic data of the load level based on the operator information of each operator 33. As shown in Fig. 28, the load level of each operator 33 is set by the proficiency level of each operator 33, and the upper and lower limits of the allowable load of each operator 33 determined based on the proficiency level.

[0292] The above-described operator information is updated for each individual operator 33, for example, each time the individual operator 33 performs an operator task.

[0293] 29 to 31 are diagrams showing an example of a method for adjusting the predicted workload that may occur on the operator 33 for a plurality of robots 10 by the server device according to the second modification of the embodiment.

[0294] The server device of Modification 2 acquires information such as the number of robots 10 for a given operator 33, the tasks of these robots 10, and the time periods during which the tasks are performed. In the example of Figures 29 to 31, four robots 10 (1 to 4) are assigned to operator 33 1 of operators 1 to 3 shown in Figure 28 above, and all four robots are given the task of guarding, with the guard area covering the entire area of ​​points A to G and the time period being the daytime hours from 12:00 to 15:00.

[0295] Based on the above information, the server device of Modification 2 sets, for each robot 10, a travel route and travel speed that enables comprehensive security of points A to G without overlapping the security areas of the individual robots 10. Furthermore, the server device calculates, based on the values ​​in Figures 26 to 28 described above, the predicted load on the operator 33 at each time when security is performed according to the above settings. The calculation results are shown in Figure 29.

[0296] In the example of Fig. 29, four robots 10, numbered 1 to 4, are set to start from points A, B, G, and G, respectively, and travel along individual travel routes that include points A to G. At time t0, these robots 10 are stopped at their respective starting points. At time t1, these robots 10 are set to move at a low speed to the next point.

[0297] Thereafter, similarly, at time t2, each of the four robots 10 stops at the point next to the starting point, at time t3, it moves to the next point at a medium speed, and when it arrives at that point and stops at time t4, it moves to the next point at a high speed at time t5, and arrives at the final point and stops at time t6.

[0298] Furthermore, the server device of Modification 2 calculates the predicted load of the operator 33 at each of times t0 to t6 for each of the robots 10 (1 to 4), and then calculates the total predicted load. The predicted load for each robot 10 can be calculated using the formula: load level at the point corresponding to the current position of the robot 10 or between points x load level according to the traveling speed of the target robot 10.

[0299] 29, the upper and lower limits of the allowable load for one operator 33 are 26 and 17, respectively, while the total predicted load is below the lower limit of the allowable load at time t1. At time t3, the total predicted load exceeds the upper limit of the allowable load.

[0300] In this case, the server device of Modification 2 first attempts to change the running speed of each robot 10 at times t1 and t3 in order to keep the predicted load values ​​at times t1 and t3 within the range of the upper and lower limits of the allowable load for one operator 33. The results of changing the running speed of each robot 10 are shown in Figure 30.

[0301] 30, the traveling speed at time t1 is changed from low to medium for robots 10 1 to 4. As a result, the predicted load of the operator 33 at time t1 exceeds the lower limit of the allowable load, and is within the upper limit of the allowable load.

[0302] On the other hand, at time t3, the travel speed of robots 10 1 to 4 is changed from medium to low, and as a result, the predicted load of operator 33 at time t3 falls below the lower limit of the allowable load.

[0303] In this case, the server device of the second modification attempts further adjustment by, for example, changing the travel path of each robot 10. The result of changing the travel path is shown in FIG.

[0304] In the example of Fig. 31, the travel routes of robots 10 Nos. 1 to 4 are changed after time t3. That is, in the example of Fig. 30, all of robots 10 Nos. 1 to 4 were generally taking travel routes with a moderate load at time t3, whereas, as shown in Fig. 31, some robots 10 are changed to take travel routes with a relatively low load, so that the predicted load at time t3 falls within the range between the upper and lower limits of the allowable load. Furthermore, the predicted load after time t3 after the travel route change is also maintained within the range between the upper and lower limits of the allowable load.

[0305] As described above, the server device of variant example 2 adjusts the running speed and running path of each robot 10 until the predicted load of the operator 33 falls within the range between the upper and lower limits of the allowable load of the operator 33 at all times.

[0306] (Modification 3) Next, a server device 120 according to Modification 3 of the embodiment will be described with reference to Fig. 32 and Fig. 33. The server device 120 according to Modification 3 differs from the embodiment described above in that it adjusts the load on an operator based on the current load on the operator.

[0307] FIG. 32 is a block diagram showing an example of a detailed configuration of a robot system 2 according to a third modification of the embodiment.

[0308] As shown in FIG. 32, the robot system 2 of the third modification includes a server device 120 instead of the server device 20 of the above-described embodiment.

[0309] The server device 120 of the third modification does not have components corresponding to the operation schedule information database 21, the operator information database 22, and the operator load prediction unit 23 in the server device 20 of the above-described embodiment. Moreover, the server device 120 of the third modification includes a determination unit 126 instead of the determination unit 26 of the server device 20 of the above-described embodiment.

[0310] In the server device 20 of the above-described embodiment, the determining unit 26 adjusts the load of the operator 33 based on the predicted load calculated by the operator load predicting unit 23. In contrast, the determining unit 126 included in the server device 120 of Modification 3 adjusts the load of the operator based on the result of comparing the actual load calculated by the operator load measuring unit 25 with the preset upper and lower thresholds.

[0311] That is, the determination unit 126 of Modification 3 determines to increase the operator's load when the actual load calculated by the operator load measurement unit 25 is equal to or less than a predetermined lower threshold. On the other hand, the determination unit 126 of Modification 3 determines to decrease the operator's load when the actual load calculated by the operator load measurement unit 25 exceeds a predetermined upper threshold.

[0312] In addition, if the actual load calculated by the operator load measurement unit 25 is higher than a predetermined lower threshold and equal to or lower than a predetermined upper threshold, the judgment unit 126 of variant example 3 judges not to adjust the operator's load and to maintain the operator's work content as is.

[0313] The above-mentioned lower and upper thresholds can be set based on the load of the operator during normal work. In this case, these lower and upper thresholds may be set for each operator or for each operator's attributes, such as length of service, number of support work experiences, proficiency level, and past performance, taking into account the load that each individual operator can handle. The server device 120 of the third modification may have the basic data shown in FIG. 28 of the second modification and be able to determine the above-mentioned lower and upper thresholds based on that data.

[0314] Furthermore, as in the above-described embodiment, methods for adjusting the load on the operator include, for example, changing the running speed, running path, and task execution range of the robot 10 under the operator's supervision, or requesting the operator to take additional action or canceling the request.

[0315] FIG. 33 is a flowchart showing an example of a procedure of a control process for the robot 10 performed by the server device 120 according to the third modification of the embodiment.

[0316] 33 , the server device 120 of Modification 3 starts operation of multiple robots 10 in accordance with the operation schedule information (step S202). The information acquisition unit 24 of the server device 120 acquires robot information from each robot 10 that has started operation (step S203). The operator load measurement unit 25 calculates the actual load imposed on the operator based on the robot information acquired from the operating robot 10 and the operator's response status obtained from input information from the input / output device 30, etc. (step S204).

[0317] The determination unit 126 of the server device 120 determines whether the measured load is equal to or less than a preset lower threshold (step S206). If the measured load is equal to or less than the lower threshold (step S206: Yes), the server device 120 performs control to increase the load of the operator (step S207). Furthermore, the server device 20 recalculates the measured load of the operator after performing the load-increasing control (step S208), similar to the processes of steps S103 and S114 described above, for example.

[0318] On the other hand, if the measured load exceeds the lower threshold (step S206: No), the determining unit 126 determines whether the measured load exceeds the upper threshold (step S210). If the measured load exceeds the upper threshold (step S210: Yes), the server device 120 performs control to reduce the load on the operator (step S211).

[0319] If the measured load exceeds the lower threshold (step S206: No) and is equal to or less than the upper threshold (step S210: No), the server device 120 does not perform any of the processes in steps S207 to S208 and S211.

[0320] The server device 120 also monitors whether the tasks of the individual robots 10 have been completed (step S209). If at least one of the robots 10 is still performing a task (step S209: No), the server device 120 repeats the process from step S203. If the tasks of all the robots 10 have been completed (step S209: Yes), the process ends.

[0321] This completes the control process for the robot 10 performed by the server device 120 of the third modified example.

[0322] According to the control method in the server device 120 of Modification 3, when the measured load is equal to or less than the lower threshold, the robot 10 is controlled to increase the load on the operator 33. This method also makes it possible to appropriately increase the load on the operator 33, thereby improving the quality of service provided by the robot 10. Furthermore, since the predicted load on the operator is not calculated, the server device 120 of Modification 3 can be configured more simply.

[0323] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention described in the claims and their equivalents.

[0324] REFERENCE SIGNS LIST 1, 2 Robot system 10 Robot 20, 120 Server device 21 Operation schedule information database 22 Operator information database 23 Operator load prediction unit 24 Information acquisition unit 25 Operator load measurement unit 26, 126 Determination unit 27 Control information generation unit 28 Control information output unit 30 Input / output device 33 Operator

Claims

1. A control method for an autonomous mobile body capable of autonomously moving and executing a predetermined task, which is controlled by a computer under the support of an operator, the method including: measuring the load on the operator based on first information indicating the situation of the autonomous mobile body during operation according to the operation plan of the autonomous mobile body, and calculating the measured load; and when the measured load is less than or equal to a first threshold, controlling the autonomous mobile body to increase the load on the operator.

2. The control for increasing the load on the operator is performed when, in addition to the measured load being less than or equal to the first threshold, the situation where the measured load is less than or equal to the first threshold continues for a first period, or when it is predicted that the situation where the measured load is less than or equal to the first threshold will continue for at least the first period. The control method according to claim 1.

3. When it is predicted that the situation where the measured load is less than or equal to the first threshold will continue for more than the first period, during the period when it is predicted that the situation where the measured load is less than or equal to the first threshold will continue, the control for increasing the load on the operator is performed. The control method according to claim 2.

4. Further calculating a predicted load by predicting the load on the operator based on second information regarding the operation plan of the autonomous mobile body; setting the first threshold lower than the predicted load; and the second information includes a risk degree predicting the likelihood of the task being delayed due to the interruption of the autonomous movement of the autonomous mobile body. The control method according to claim 1.

5. The first information includes an actual risk degree indicating the likelihood of the task being delayed due to the actual interruption of the autonomous movement of the autonomous mobile body. The control method according to claim 4.

6. At least one of the first threshold and the first period is determined based on second information indicating the degree of load that the operator can handle. The control method according to claim 2.

7. The control for increasing the load on the operator includes at least one of: controlling to increase the traveling speed of the autonomous mobile body; controlling to change the traveling route of the autonomous mobile body; controlling to expand the execution range of the task of the autonomous mobile body; and controlling the autonomous mobile body to require additional response by the operator. The control method according to claim 1.

8. The control requiring the additional support includes at least one of control for increasing the execution speed of the task by the autonomous mobile body and control for causing the autonomous mobile body to execute another task in parallel with the task, according to the control method of claim 7.

9. The task is at least one of delivery, security, mobile vending, and cleaning. To increase the execution speed of the task, when the task is delivery, control for advancing the delivery time is performed; when the task is security, control for expanding the security range per unit time is performed; when the task is mobile vending, control for increasing the encounter rate with traffic participants per unit time is performed; and when the task is cleaning, control for expanding the cleaning range per unit time is performed, according to the control method of claim 8.

10. Instead of or in addition to controlling the autonomous mobile body to increase the operator's load, the operator is made to additionally support another autonomous mobile body, according to the control method of claim 1.

11. The other autonomous mobile body is at least one of a plurality of autonomous mobile bodies supported by another operator with a high measured load, according to the control method of claim 10.

12. Referring to the operator's load history, when the operator's measured load is higher than a second threshold set higher than the first threshold, even when the measured load is below the first threshold, the control of the autonomous mobile body for increasing the operator's load is not performed, according to the control method of claim 1.

13. Based on third information indicating the situation of the autonomous mobile body in operation according to the control for increasing the operator's load, the operator's load is measured to calculate an adjusted load, it is determined whether the adjusted load exceeds the first threshold, and based on the determination result for the adjusted load, the control of the autonomous mobile body is performed to further increase, maintain, or decrease the operator's load, according to the control method of claim 1.

14. The operator supports a plurality of autonomous mobile bodies including the autonomous mobile body, and the control for increasing the operator's load is performed on the autonomous mobile body among the plurality of autonomous mobile bodies that has caused the measured load to be below the first threshold, according to the control method of claim 1.

15. Calculate the service quality of the plurality of autonomous mobile bodies based on the first information, and perform control to increase the load on the operator for an autonomous mobile body whose service quality is equal to or lower than a third threshold value. The control method according to claim 1.

16. The task is at least one of delivery, security, mobile vending, and cleaning. When the task is delivery, the service quality is calculated from the scheduled arrival time predicted based on the first information. When the task is security, the service quality is calculated from the predicted completion range predicted based on the first information. When the task is mobile vending, the service quality is calculated from the predicted number of products sold or sales amount predicted based on the first information. When the task is cleaning, the service quality is calculated from the predicted completion range predicted based on the first information. The control method according to claim 15.

17. When performing control of the autonomous mobile body to increase the load on the operator, present the content of the control change to the operator. The control method according to claim 1.

18. When performing control of the autonomous mobile body to increase the load on the operator, request permission from the operator. The control method according to claim 1.

19. An autonomous mobile body that can autonomously move and execute a predetermined task under the support of an operator, and operates to increase the load on the operator when the measured load obtained by measuring the load on the operator based on the first information indicating the status of the operating autonomous mobile body according to the operation schedule of the autonomous mobile body is equal to or lower than a first threshold value.

20. A program for causing a computer to control an autonomous mobile body that can autonomously move and execute a predetermined task under the support of an operator, calculates the measured load by measuring the load on the operator based on the first information indicating the status of the operating autonomous mobile body according to the operation schedule of the autonomous mobile body, and when the measured load is equal to or lower than a first threshold value, causes the computer to perform control of the autonomous mobile body to increase the load on the operator.

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