Schedule generation method, robot, and program

Abstract

A schedule generation method according to the present disclosure generates an operation schedule for a robot that manufactures a product and autonomously moves, and includes: a first step for acquiring a congestion level for each position; a second step for acquiring temporal transition data of an advertisement parameter for enhancing customer purchase intent caused during manufacturing of the product by the robot; and a third step for generating an operation schedule for increasing an advertisement effectiveness index representing an advertisement effect on the customer during movement of the robot on the basis of the congestion level for each position and the temporal transition data of the advertisement parameter.

Description

Schedule generation method, robot, and program

[0001] The present disclosure relates to a schedule generation method, a robot, and a program.

[0002] Mobile sales robots that move autonomously and sell products to customers are known, and mobile sales robots that can produce products while moving or selling products are also known.

[0003] When operating such a mobile sales robot, an operation schedule is generated in advance, which indicates the product production schedule and the movement schedule. For example, Patent Documents 1 and 2 disclose techniques for producing products so that the estimated arrival time and the time when the product production is completed coincide with each other.

[0004] Incidentally, when such a mobile sales robot sells products manufactured at the destination, it is desirable for the robot to advertise the products as efficiently as possible while selling them.

[0005] Japanese Patent No. 6992550 Japanese Patent Application Laid-Open No. 2020-197874

[0006] The present disclosure aims to provide a schedule generation method, a robot, and a program for generating an operation schedule for a robot that can efficiently advertise a product.

[0007] The schedule generation method according to the present disclosure is a schedule generation method for generating an operation schedule for a robot that manufactures products and moves autonomously, and includes a first step of acquiring the congestion level for each location, a second step of acquiring time transition data of advertising parameters that increase customer purchasing motivation while the robot is manufacturing the products, and a third step of generating the operation schedule based on the congestion level for each location and the time transition data of the advertising parameters, to increase an advertising effectiveness index that represents the advertising effectiveness given to customers while the robot is moving.

[0008] FIG. 1 is a diagram illustrating an example of the configuration of a mobile sales system according to an embodiment. FIG. 2 is a diagram illustrating an example of the functional configuration of a mobile sales robot and an information processing device. FIG. 3 is a diagram illustrating an example of a service schedule generated by the information processing device. FIG. 4 is a diagram illustrating an example of the operation of the mobile sales robot. FIG. 5 is a flowchart illustrating the processing flow of the mobile sales system according to an embodiment. FIG. 6 is a flowchart illustrating the processing flow of a service schedule generated by the information processing device. FIG. 7 is a diagram illustrating an advertising effectiveness index. FIG. 8 is a diagram illustrating an example of a customer ratio. FIG. 9 is a diagram illustrating an example of a matching index. FIG. 10 is a diagram illustrating an advertising effectiveness index taking into account customer demographics and a matching index. FIG. 11 is a diagram illustrating an example of a matching index for each type of product. FIG. 12 is a flowchart illustrating an example of the processing flow of a service schedule generated by the information processing device when multiple types of products are generated. FIG. 13 is a flowchart illustrating an example of the processing flow of a service schedule generated by the information processing device when weather information and event information are used. FIG. 14 is a sequence diagram illustrating interactions between the mobile sales robot and the information processing device while the mobile sales robot is in operation. FIG. 15 is a flowchart illustrating the processing flow of a first process performed by the information processing device when a rescheduling request is received. Fig. 16 is a flowchart showing the flow of second processing of the information processing device when a rescheduling request is received. Fig. 17 is a diagram showing an example of an advertising effectiveness index and an operation schedule when multiple mobile sales robots are operated. Fig. 18 is a diagram showing a first example of a sales area when multiple mobile sales robots are operated. Fig. 19 is a diagram showing a second example of a sales area when multiple mobile sales robots are operated. Fig. 20 is a diagram showing an example of the appearance of a mobile sales robot. Fig. 21 is a diagram showing a modified example of a mobile sales system. Fig. 22 is a hardware configuration diagram of an information processing device.

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the accompanying drawings as appropriate. However, more detailed description than necessary may be omitted. Note that the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0010] FIG. 1 is a diagram showing an example of the configuration of a mobile sales system 10 according to an embodiment.

[0011] The mobile sales system 10 includes one or more mobile sales robots 20 and an information processing device 30. Each of the one or more mobile sales robots 20 is communicably connected to the information processing device 30 via a network NW or the like.

[0012] The mobile sales robot 20 is a robot that autonomously manufactures, moves, and sells merchandise. The mobile sales robot 20 is capable of loading ingredients for merchandise and manufacturing finished merchandise from the ingredients. For example, the merchandise is food. In this embodiment, the merchandise is bread. The merchandise is not limited to bread; it may also be confectionery such as cookies, soup, steak, or sushi, or it may be tea, coffee, or a smoothie made by stirring one or more liquids.

[0013] The mobile sales robot 20 receives the operation schedule generated by the information processing device 30 via the network NW. The mobile sales robot 20 produces and moves merchandise in accordance with the received operation schedule.

[0014] The information processing device 30 generates an operation schedule for each of one or more mobile sales robots 20. The information processing device 30 transmits the generated operation schedule to the corresponding mobile sales robot 20 via the network NW.

[0015] The information processing device 30 has a hardware configuration similar to that of a normal computer equipped with a processor and a storage device, and executes information processing according to a program. The information processing device 30 may be a server connected to a network NW, or may be a cloud computer in which one or more servers operate in conjunction with each other.

[0016] FIG. 2 is a diagram showing an example of the functional configuration of the mobile sales robot 20 and the information processing device 30.

[0017] The mobile sales robot 20 includes a memory unit 41, a location information acquisition unit 42, a camera 43, an image acquisition unit 44, an image analysis unit 45, a drive unit 46, a travel control unit 47, a manufacturing unit 48, a manufacturing control unit 49, a sales unit 50, a sales control unit 51, a plan change request unit 52, and a first communication unit 53.

[0018] The storage unit 41 stores the operation schedule received from the information processing device 30 and various programs and data for controlling the mobile sales robot 20.

[0019] The location information acquisition unit 42 detects detection signals from various sensors and a GPS (Global Positioning System) that detect the location of the mobile sales robot 20 , and acquires location information that indicates the location of the mobile sales robot 20 .

[0020] The camera 43 captures images of the surroundings of the mobile sales robot 20. The image acquisition unit 44 acquires images captured by the camera 43. The image acquisition unit 44 may also acquire moving images. The image analysis unit 45 analyzes the images or moving images acquired by the image acquisition unit 44 and calculates, for example, the level of customer congestion around the mobile sales robot 20, the ratio of each customer demographic representing categories such as the occupation, gender, and age of the surrounding customers, and an attention rate representing the proportion of customers paying attention to the mobile sales robot 20.

[0021] The drive unit 46 is a device for moving the mobile sales robot 20. The drive unit 46 includes, for example, a motor and wheels. The travel control unit 47 controls the drive unit 46 in accordance with the operation schedule received from the information processing device 30 to move the mobile sales robot 20. Furthermore, the travel control unit 47 determines the surrounding situation based on images or video images captured by the camera 43, and controls the amount of acceleration, braking, steering angle, etc.

[0022] The production unit 48 is loaded with product ingredients and produces finished products from the ingredients. In this embodiment, the production unit 48 is a cooking appliance that cooks the ingredients to produce food. The production control unit 49 controls the production unit 48 according to the operation schedule received from the information processing device 30, and starts each process for producing the product at a time according to the operation schedule.

[0023] The sales department 50 stores the finished products manufactured by the manufacturing department 48 in a product storage room, and provides the products stored in the product storage room to customers under the control of the sales control department 51. The sales control department 51 executes a billing process for the customer in response to a purchase request from the customer, and controls the sales department 50 to provide the product to the customer upon completion of the billing process.

[0024] The plan change request unit 52 generates a rescheduling request requesting a change in the operation schedule based on the level of congestion around the mobile sales robot 20, etc.

[0025] The first communication unit 53 is an interface that transmits and receives information to and from the information processing device 30 via the network NW or the like. The first communication unit 53 receives an operation schedule from the information processing device 30 and stores it in the storage unit 41. The first communication unit 53 also transmits to the information processing device 30 a congestion level obtained by capturing images of the surroundings of the mobile sales robot 20 with the camera 43, along with location information and time information. If a ratio or attention rate for each customer segment is calculated along with the congestion level, the first communication unit 53 also transmits the ratio and attention rate for each customer segment to the information processing device 30. If a rescheduling request is generated by the plan change request unit 52, the first communication unit 53 transmits the rescheduling request to the information processing device 30.

[0026] The information processing device 30 includes a second communication unit 61 , a map data storage unit 62 , a congestion information storage unit 63 , a congestion information update unit 64 , a manufacturing information storage unit 65 , and a control unit 66 .

[0027] The second communication unit 61 is an interface for transmitting and receiving information to and from the mobile sales robot 20 via a network NW or the like. The second communication unit 61 transmits the generated operation schedule to the corresponding mobile sales robot 20. The second communication unit 61 also receives congestion levels, location information, time information, customer demographic ratios, and attention rates from one or more mobile sales robots 20. The second communication unit 61 also receives rescheduling requests from one or more mobile sales robots 20.

[0028] The map data storage unit 62 stores map data of the range within which the mobile sales robot 20 can move. The mobile sales robot 20 can move according to a movement route generated based on the map data.

[0029] The congestion information storage unit 63 stores congestion information indicating the congestion level for each location shown in the map data. The congestion level is a value representing the number of customers per unit area. The congestion level may be a discrete value expressed at a predetermined resolution, or may be a continuous value. Furthermore, the congestion information may store the congestion level for each time period. For example, the congestion information may include the congestion level for each predetermined time period, or may include, for example, the congestion level during lunchtime and the congestion level outside of lunchtime. The congestion information may further include the ratio for each location and each customer demographic, and may further include the attention rate for each location.

[0030] When the congestion information update unit 64 receives the congestion level, location information, time information, ratio of each customer demographic, and attention rate from the mobile sales robot 20, it updates the congestion information stored in the congestion information storage unit 63. The congestion information update unit 64 may accumulate the information received from the mobile sales robot 20 for a certain period of time and update the congestion information at regular intervals.

[0031] The manufacturing information storage unit 65 stores in advance manufacturing information about the products manufactured by the mobile sales robot 20. For example, the manufacturing information includes the order of manufacturing processes for the products and the manufacturing time for each manufacturing process for the products. The manufacturing information also includes time transition data of advertising parameters that increase customer purchasing motivation while the mobile sales robot 20 is manufacturing the products.

[0032] If the product is a food product, the promotion parameter may be, for example, a fragrance parameter that represents the intensity of the fragrance generated during the manufacturing process. For example, the manufacturing information may include information representing the time change of the fragrance parameter from the start of manufacturing to the end of manufacturing as time transition data of the promotion parameter. For example, the fragrance parameter may be a discrete or continuous value that represents the intensity of the fragrance.

[0033] The promotion parameter may vary depending on the product being manufactured. For example, if the product is a smoothie, the process of stirring the liquid during production creates a dramatic effect for customers and increases their willingness to purchase. Therefore, if the product is a smoothie, the promotion parameter may be the magnitude of the dramatic effect of stirring the liquid during production. Also, for example, if the product is a steak, the sound of grilling is generated during production, creating a dramatic effect for customers and increasing their willingness to purchase. Therefore, if the product is a steak, the promotion parameter may be a value that includes the volume of the sound in addition to the strength of the aroma. In this way, the promotion parameter may be any value that represents the effect of increasing customers' willingness to purchase during the production of the product.

[0034] The control unit 66 is realized by executing a program using a processor, a memory, etc. The control unit 66 includes a schedule generation unit 67 and a schedule change determination unit 68.

[0035] The schedule generation unit 67 generates an operation schedule for the mobile sales robot 20 based on the map data stored in the map data storage unit 62, the congestion information stored in the congestion information storage unit 63, and the manufacturing information stored in the manufacturing information storage unit 65.

[0036] The schedule generation unit 67 generates an operation schedule, for example, before the mobile sales robot 20 starts business, and transmits the operation schedule to the mobile sales robot 20. Furthermore, when the schedule generation unit 67 receives a rescheduling request from the mobile sales robot 20 and determines that a schedule change is necessary, the schedule generation unit 67 generates a new operation schedule and transmits the new operation schedule to the mobile sales robot 20.

[0037] When a rescheduling request is received from the mobile sales robot 20, the schedule change determination unit 68 determines whether a schedule change is necessary. The schedule change determination unit 68 provides the determination result to the schedule generation unit 67. As a result, when it is determined that a schedule change is necessary, the schedule generation unit 67 can generate a new operation schedule.

[0038] The information processing device 30 may also acquire camera images from one or more monitoring cameras fixedly installed at any location in the service area of ​​the mobile sales robot 20. The information processing device 30 may then calculate the congestion level for each location installed in the map data based on the camera images acquired from the one or more monitoring cameras, and update the congestion information stored in the congestion information storage unit 63. Furthermore, the information processing device 30 may update the congestion information based on images captured by the camera 43 while the mobile sales robot 20 is moving. This allows the information processing device 30 to update the congestion information over time, thereby improving the accuracy of the congestion information over time.

[0039] 3 is a diagram showing an example of an operation schedule generated by the information processing device 30. The operation schedule includes the hourly movement positions of the mobile sales robot 20, and the start time and production speed of each product manufacturing process by the mobile sales robot 20. For example, the operation schedule includes the movement start time, destination position, and arrival time for each destination. Furthermore, for example, the operation schedule includes the start time of product manufacturing, such as the cooking start time.

[0040] By operating in accordance with the operation schedule, the mobile sales robot 20 can move to a designated location at a designated time along a movement route designated by the operation schedule. Furthermore, by operating in accordance with the operation schedule, the mobile sales robot 20 can start a designated manufacturing process at a designated location and time designated by the operation schedule and complete a product at a designated location and time.

[0041] FIG. 4 is a diagram showing an example of the operation of the mobile sales robot 20.

[0042] Here, the information processing device 30 generates an operation schedule that increases an advertising effectiveness index that represents the advertising effectiveness on customers while the mobile sales robot 20 is moving, based on the congestion level for each location and the time transition data of the advertising parameters. More specifically, the information processing device 30 solves an optimization problem that maximizes an objective function that represents the advertising effectiveness index, and generates an operation schedule based on the solution of the optimization problem obtained by solving the optimization problem.

[0043] For example, if the product is bread and the promotion parameter is a fragrance parameter, the information processing device 30 generates an operation schedule that maximizes the cumulative value of the product of the congestion level and the fragrance parameter during the movement period of the mobile sales robot 20, for example, during the period from when the mobile sales robot 20 starts moving until it arrives at the sales area where the product is sold.

[0044] Furthermore, in this embodiment, the information processing device 30 generates an operation schedule for the mobile sales robot 20 to move so as to maximize the advertising effectiveness index, under the condition that the product will be completed by the time the mobile sales robot 20 arrives at the sales area where the product is to be sold.

[0045] When such an operation schedule is generated, the mobile sales robot 20 operates as follows.

[0046] First, before business hours begin, the mobile sales robot 20 waits at the robot base 81. The information processing device 30 generates an operation schedule while the mobile sales robot 20 waits at the robot base 81 and transmits the operation schedule to the mobile sales robot 20. Furthermore, while the mobile sales robot 20 waits at the robot base 81, materials for the products to be manufactured are loaded onto the mobile sales robot 20.

[0047] When the movement start time arrives, the mobile sales robot 20 begins moving to the first sales area 82 indicated in the operation schedule. In this case, the operation schedule indicates the movement route that maximizes the advertising effectiveness index, as well as the product production start time and production start speed. Therefore, for example, if there are two routes between the robot base 81 and the first sales area 82: one that passes through a first congested area 83 with a large number of customers and another that passes through a first non-congested area 84 with a small number of customers, the mobile sales robot 20 moves along the route that passes through the first congested area 83. Furthermore, when passing through the first congested area 83, the mobile sales robot 20 executes a process in the product manufacturing process that has a large advertising parameter, such as a process with a large fragrance parameter. As a result, the mobile sales robot 20 can increase the purchasing motivation of customers in the first congested area 83 by using the fragrance generated during product manufacturing, and advertise the product to the customers in the first congested area 83.

[0048] Next, the mobile sales robot 20 moves from the first crowded area 83 to the first sales area 82. The mobile sales robot 20 completes the production of the products when it arrives at the first sales area 82. This allows the mobile sales robot 20 to start selling the products as soon as it arrives at the first sales area 82, ensuring sufficient sales time and allowing for efficient sales of the products. After arriving at the first sales area 82, the mobile sales robot 20 sells the products and re-produces the products as needed.

[0049] Furthermore, for example, when the congestion level decreases below a planned value while the mobile sales robot 20 is selling products in the first sales area 82, the mobile sales robot 20 transmits a rescheduling request to the information processing device 30. When the mobile sales robot 20 receives a new operation schedule from the information processing device 30 in response to transmitting the rescheduling request, the mobile sales robot 20 moves to the second sales area 85 in accordance with the new operation schedule. After moving to the second sales area 85, the mobile sales robot 20 sells products and, if necessary, manufactures products.

[0050] When business hours end, or when, for example, all products are sold out and no more materials are available to manufacture new products, the mobile sales robot 20 returns to the robot base 81. If there is still business hours remaining after returning to the robot base 81, the mobile sales robot 20 is loaded with materials for the products to be manufactured, receives a new operating schedule, and continues to move, manufacture, and sell products in accordance with the new operating schedule.

[0051] As described above, the mobile sales system 10 according to the embodiment can generate an operation schedule for the mobile sales robot 20 that can efficiently advertise products while traveling. As a result, the mobile sales system 10 according to the embodiment can efficiently sell products.

[0052] 5 is a flowchart showing the flow of processing in the mobile sales system 10 according to the embodiment. The mobile sales system 10 executes processing according to the flow shown in FIG.

[0053] First, in S11, the information processing device 30 generates an operation schedule. Then, in S12, the information processing device 30 transmits the generated operation schedule to the mobile sales robot 20, and causes the mobile sales robot 20 to operate.

[0054] FIG. 6 is a flowchart showing the flow of the process of generating an operation schedule by the information processing device 30.

[0055] In S11 of FIG. 5, the information processing device 30 executes the process according to the flow shown in FIG.

[0056] First, in S21 , the information processing device 30 acquires map data from the map data storage unit 62 .

[0057] Next, in S22, the information processing device 30 acquires congestion information indicating the congestion level for each location from the congestion information storage unit 63. If the congestion information contains too little information to generate an operation schedule, the information processing device 30 may operate the mobile sales robot 20 within the service area before providing the service, acquire the congestion level for each location from camera images, and update the congestion information. When providing a mobile sales service using the mobile sales robot 20, the information processing device 30 may operate the mobile sales robot 20 on a test run. The information processing device 30 may reduce costs by having the mobile sales robot 20 capture images of the surrounding area during the test run to update the congestion information.

[0058] The information processing device 30 then determines the sales area based on the congestion level for each location. For example, the information processing device 30 determines, as the sales area, the location with the highest congestion level among the areas where the mobile sales robot 20 can sell products while stopped, or an area with a congestion level equal to or higher than a threshold. Note that the information processing device 30 may determine the sales area without using the congestion level for each location. For example, the information processing device 30 may acquire in advance location information indicating the location of the sales area designated by the administrator, and determine the sales area based on the acquired location information.

[0059] Subsequently, in S23, the information processing device 30 acquires manufacturing information from the manufacturing information storage unit 65. The manufacturing information includes time transition data of the advertisement parameters.

[0060] Next, in S24, the information processing device 30 generates an optimization problem for maximizing an objective function representing an advertising effectiveness index. The advertising effectiveness index is a value representing the advertising effect on customers. For example, the advertising effectiveness index is a cumulative value obtained by accumulating the product of the congestion level and the fragrance parameter from the start to the end of product production. The optimization problem includes, for example, variables such as the time position of the mobile sales robot 20, the time when the mobile sales robot 20 starts producing products, and the speed at which the mobile sales robot 20 produces products. In this embodiment, the optimization problem is solved under the condition that the products will be completed by the time the mobile sales robot 20 arrives at the determined sales area.

[0061] Then, the information processing device 30 solves the generated optimization problem using an optimization problem solving program or the like.

[0062] Next, in S25, the information processing device 30 generates an operation schedule based on the solution of the optimization problem obtained by solving it, i.e., the values ​​of each variable.

[0063] By performing the above processing, the information processing device 30 can generate an operation schedule that maximizes the advertising effectiveness index, which represents the advertising effect on customers while the mobile sales robot 20 is moving, based on the congestion level at each location and the time transition data of the advertising parameters.

[0064] FIG. 7 is a diagram for explaining the advertising effectiveness index.

[0065] The congestion level changes over time as the mobile sales robot 20 moves, or even when the mobile sales robot 20 is stopped.

[0066] Furthermore, the advertising parameters change over time during the manufacturing process, from the start of product production to the completion of the product. For example, if the product is bread, the aroma parameter will be small at the start of cooking and will increase over time from the middle of cooking. The advertising parameter transition data is information that represents such changes in the advertising parameters over time.

[0067] The advertising effectiveness index is expressed by a value obtained by accumulating a composite value of the congestion level and the advertising parameter for each time period from the start of cooking to the completion of cooking. For example, if the product is a food product and the advertising parameter is an aroma parameter, the advertising effectiveness index is a value obtained by accumulating a value obtained by multiplying the congestion level and the aroma parameter for each time period from the start of cooking to the completion of cooking, as shown in FIG. 7 .

[0068] In order to maximize the advertising effectiveness index, the information processing device 30 can maximize the advertising effectiveness index by shifting the start time of product production. For example, the information processing device 30 can maximize the advertising effectiveness index by shifting the start time of product production so that a time when the congestion level is high overlaps with a time when the fragrance parameter, which is an advertising parameter, is high. Furthermore, the congestion level per hour varies depending on the movement route of the mobile sales robot 20. Therefore, the information processing device 30 can maximize the advertising effectiveness index by shifting the movement route so that the mobile sales robot 20 passes through a location where the congestion level is high during a time when the fragrance parameter, which is an advertising parameter, is high.

[0069] Therefore, the information processing device 30 generates an optimization problem based on the congestion level for each location, the map data, and the time transition data of the advertising parameters for each time period, with the advertising effectiveness index as an objective function, and including the location of the mobile sales robot 20 for each time period, the time when the mobile sales robot 20 starts producing goods, the speed at which the mobile sales robot 20 produces goods, etc. as variables of the objective function. Furthermore, the information processing device 30 finds a solution that maximizes this optimization problem. Then, the information processing device 30 generates an operation schedule based on the solution of the optimization problem thus found. As a result, the information processing device 30 can relatively easily generate an operation schedule that maximizes the advertising effectiveness index by digital calculation.

[0070] In some cases, the mobile sales robot 20 can manufacture multiple types of products. In such cases, the time transition data of the advertising parameters may be different for each type of product. This allows the mobile sales robot 20 to optimize its operation schedule for each type of product it manufactures.

[0071] In calculating the advertising effectiveness index, the operation of combining the congestion level and the scent parameter may not only involve multiplication of the congestion level and the scent parameter, but may also involve a nonlinear operation using, for example, a function. For example, the operation of combining the congestion level and the scent parameter may involve applying a predetermined function to one or both of the congestion level and the scent parameter to convert the values, or adding or subtracting other values, thereby performing a nonlinear operation on the values ​​before multiplication. The information processing device 30 may also calculate the advertising effectiveness index using a learning model. In this case, the learning model inputs the congestion level, the scent parameter, and other values ​​such as the customer attention rate, and outputs the advertising effectiveness index. The learning model is trained in advance so that the advertising effectiveness index can be appropriately output. This allows the information processing device 30 to generate an accurately optimized operation schedule using accurate time transition data of the advertising parameters.

[0072] The information processing device 30 may also calculate the advertising effectiveness index by multiplying it by a different correction coefficient depending on the time period. For example, during lunchtime and the evening, there are many customers who are about to eat and are hungry. Therefore, if the product is a food product, the advertising effectiveness index may be multiplied by a large correction coefficient during lunchtime and the evening, and by a small correction coefficient during time periods other than lunchtime and the evening. This allows the information processing device 30 to generate an operation schedule using an advertising effectiveness index that appropriately reflects customers' purchasing willingness.

[0073] The mobile sales robot 20 may also display advertising information on signage and output advertising audio through a speaker. Staff may also distribute flyers with advertising information near the mobile sales robot 20. In this case, the information processing device 30 may calculate the advertising effectiveness index for the time period during which the display, audio output, and flyer distribution are performed by multiplying the coefficient for other time periods by a larger correction coefficient. This allows the information processing device 30 to generate an operation schedule using an advertising effectiveness index that appropriately reflects customers' purchasing willingness.

[0074] Furthermore, the information processing device 30 may generate an operation schedule taking into consideration the battery consumption of the mobile sales robot 20, the number of staff members to be mobilized, and the like, in addition to the advertising effectiveness index. This allows the information processing device 30 to generate an optimized operation schedule that also takes into account the costs incurred for travel, product production, and sales.

[0075] The image analysis unit 45 of the mobile sales robot 20 may also determine, from images captured by the camera 43, the customer's line of sight, the direction of the customer's face, and whether the customer stopped near the mobile sales robot 20, and calculate an attention rate that indicates the percentage of customers paying attention to the mobile sales robot 20. In this case, the congestion information includes the attention rate in addition to the congestion level for each location. The information processing device 30 may then calculate an advertising effectiveness index by correcting the congestion level for each location using the attention rate. This allows the information processing device 30 to generate a sales schedule using an advertising effectiveness index that appropriately reflects the percentage of customers interested in the products. Furthermore, if the attention rate exceeds a threshold due to the advertising effect while the mobile sales robot 20 is moving toward a sales area, the sales area may be changed from the location determined by the operation schedule to a location near the location where the attention rate exceeds the threshold.

[0076] Furthermore, the information processing device 30 may generate an operation schedule under the constraint that a process that increases an advertising parameter, for example, a process that increases a fragrance parameter, must be performed within a predetermined distance from the sales area. For example, the information processing device 30 may generate an operation schedule such that the device patrols one or more congested areas within a predetermined distance from the sales area, and a manufacturing process that increases a fragrance parameter is performed in each congested area. Customers located closer to the sales area are considered to be more likely to purchase products than customers located farther away. Therefore, by generating an operation schedule in this manner, the information processing device 30 can generate an operation schedule that allows more advertising to be performed on customers located closer to the sales area, thereby enabling efficient product sales.

[0077] The information processing device 30 may also temporarily stop in one or more congested areas between the time it departs from the robot base 81 and the time it arrives at the sales area. The information processing device 30 may also generate an operation schedule in which the mobile sales robot 20 arrives at the sales area before the product is completed and executes a manufacturing process in the sales area that increases the scent parameter. This allows the information processing device 30 to generate an operation schedule that efficiently maximizes the advertising effectiveness index while reducing the travel distance of the mobile sales robot 20 and suppressing battery consumption.

[0078] Furthermore, if the information processing device 30 can predict the time periods when the congestion level in the sales area will be high, it may arrive at the sales area before the product is completed, and may not execute the manufacturing process with a high scent parameter during the time periods when the congestion level in the sales area is low, but may execute the manufacturing process with a high scent parameter during the time periods when the congestion level in the sales area is high. Even in this way, the information processing device 30 can generate an operation schedule that efficiently maximizes the advertising effectiveness index while reducing the travel distance of the mobile sales robot 20 and suppressing battery consumption.

[0079] Furthermore, when the information processing device 30 executes a manufacturing process with a high scent parameter near a congested area, there is a possibility that a period of time during which product production is not performed will occur in order to synchronize the execution timing of the manufacturing process with the timing of the location near the congested area. In such a case, sales time may be reduced, which may result in lower sales. For this reason, the information processing device 30 may set a deadline for completing the product or a deadline for executing a process that will increase the scent parameter in advance, and generate an operation schedule with the condition that the product is completed or the process that will increase the scent parameter is executed by the set deadline. This allows the information processing device 30 to generate an operation schedule that ensures a sufficient sales period. In this case, the information processing device 30 may generate an operation schedule that moves the robot to a congested area that is likely to have as many people as possible within the deadline, a predetermined time before the deadline for starting the manufacturing process with a high scent parameter. Then, the information processing device 30 may generate an operation schedule that moves the robot to a congested area that is likely to have as many people as possible within the deadline after starting the manufacturing process with a high scent parameter.

[0080] FIG. 8 is a diagram showing an example of customer ratios. The congestion information stored in the congestion information storage unit 63 may further include ratios for each location and each customer demographic in addition to the congestion level for each location. The customer demographic represents, for example, a customer category. For example, in the example of FIG. 8, the customer demographic is categorized by occupation. In the example of FIG. 8, when the total number of customers at a corresponding location is 1, the ratio of workers is 0.4, the ratio of housewives is 0.2, and the ratio of students is 0.1.

[0081] FIG. 9 is a diagram showing an example of a matching index. In addition to the time transition data of the advertising parameters, the manufacturing information stored in the manufacturing information storage unit 65 may further include a matching index for each customer segment related to the manufactured product. The matching index for each customer segment is a value that represents the purchase probability of the product for each customer segment. The matching index for each customer segment is set in advance by, for example, a designer. The matching index for each customer segment may also be updated based on past sales results, etc. The example in FIG. 9 shows that the matching index for workers is 1.1, the matching index for housewives is 0.8, and the matching index for students is 0.9.

[0082] FIG. 10 is a diagram for explaining the advertising effectiveness index taking into consideration the customer demographics and the matching index.

[0083] The advertising effectiveness index may be calculated based on the congestion level for each location, the ratio for each location and each customer segment as shown in Figure 8, the matching index for each customer segment as shown in Figure 9, and the time transition data of the advertising parameters.

[0084] In this case, the advertising effectiveness index is the sum of the advertising effectiveness indexes for each customer segment. The advertising effectiveness index for each customer segment is the cumulative value, from the start of production to completion, of the value obtained by multiplying the corrected congestion level, which is the congestion level corrected by the matching index and ratio, by the advertising parameter (e.g., fragrance parameter) for each time period for each customer segment.

[0085] The corrected congestion level is calculated by multiplying the congestion level for each location by the ratio of the corresponding location and the matching index, for example.

[0086] By using such advertising effectiveness index, the information processing device 30 can generate an operation schedule that efficiently advertises products to customers who are likely to purchase the products.

[0087] FIG. 11 is a diagram showing an example of a matching index for each type of product. The production information may include, for example, a matching index for each customer demographic for each type of product. The example shown in FIG. 11 shows matching indices for each customer demographic for raisin bread, French bread, and chocolate bread. In this case, the advertising effectiveness index is calculated using the matching index corresponding to the type of product to be manufactured. By using the advertising effectiveness index in this way, the information processing device 30 can generate an operation schedule for each type of product that efficiently advertises products to customers in customer demographics who are likely to purchase the products.

[0088] FIG. 12 is a flowchart showing an example of the flow of the process of generating an operation schedule by the information processing device 30 when multiple types of products are generated.

[0089] When generating multiple types of products, the information processing device 30 executes the process, for example, according to the flow shown in Fig. 12. In the flowchart shown in Fig. 12, steps that execute substantially the same processes as those shown in Fig. 6 are assigned the same step numbers, and detailed descriptions thereof will be omitted except for differences.

[0090] First, in S21 , the information processing device 30 acquires map data from the map data storage unit 62 .

[0091] Next, in S22, the information processing device 30 acquires congestion information from the congestion information storage unit 63. In this example, the congestion information includes the congestion level for each location, as well as the ratio for each location and each customer demographic. Then, the information processing device 30 determines the sales area based on the congestion information.

[0092] Next, in S23, the information processing device 30 acquires manufacturing information from the manufacturing information storage unit 65. In this example, the manufacturing information includes matching indices for each product type and each customer demographic, in addition to time transition data of the advertising parameters.

[0093] Next, in S31, the information processing device 30 acquires sales information indicating past sales by product type and determines a planned production quantity for each product type based on the acquired sales information. The information processing device 30 may determine the planned production quantity based not only on the sales information but also on the amount of materials, etc.

[0094] Next, in S24, the information processing device 30 generates an optimization problem for maximizing an objective function representing an advertising effectiveness index, with the condition that the planned production quantities of each of the multiple product types are produced. In this case, the advertising effectiveness index is calculated based on the congestion level for each location, the ratio for each location and each customer demographic, the matching index for each product type and each customer demographic, and time transition data of the advertising parameters. The information processing device 30 then solves the generated optimization problem.

[0095] Next, in S25, the information processing device 30 generates an operation schedule based on the solution of the optimization problem obtained by solving it, i.e., the values ​​of each variable.

[0096] By performing the above processing, the information processing device 30 can generate an operation schedule that maximizes the advertising effectiveness index when manufacturing multiple types of products.

[0097] FIG. 13 is a flowchart showing an example of the flow of the process of generating an operation schedule by the information processing device 30 when weather information and event information are used.

[0098] The information processing device 30 may generate an operation schedule by further using weather information and event information. Note that steps that execute substantially the same processing as that shown in Figure 6 are assigned the same step numbers, and detailed descriptions will be omitted except for differences.

[0099] After acquiring congestion information including the congestion level for each location in S22, the information processing device 30 executes the process of S41.

[0100] In S41, the information processing device 30 acquires weather information for each location and event information for each location. Note that the information processing device 30 may acquire only either the weather information or the event information.

[0101] In S42, the information processing device 30 corrects the congestion level for each location included in the congestion information based on the weather information for each location and the event information for each location. For example, the information processing device 30 reduces the congestion level for locations where the weather information indicates rain or a temperature outside the optimum temperature range, and does not change the congestion level for locations where the weather information indicates weather other than rain and a temperature within the optimum temperature range. The optimum temperature range is, for example, a predetermined temperature range relative to the average annual temperature. Furthermore, the information processing device 30 may increase the congestion level for locations where the weather information indicates sunny weather and temperature information within the optimum temperature range. Furthermore, for example, the information processing device 30 increases the congestion level for locations where an event is held based on the event information for each location, and does not change the congestion level for locations where no event is held.

[0102] When the information processing device 30 finishes the process of S42, the process proceeds to S23.

[0103] By performing the above processing, the information processing device 30 can generate an appropriate operation schedule that reflects the weather or the holding of an event.

[0104] FIG. 14 is a sequence diagram showing the exchange between the mobile sales robot 20 and the information processing device 30 while the mobile sales robot 20 is in operation.

[0105] The mobile sales robot 20 and the information processing device 30 execute the process shown in FIG. 14 while the mobile sales robot 20 is in operation.

[0106] First, in S51, the mobile sales robot 20 monitors the congestion level around the mobile sales robot 20 based on the image captured by the camera 43. Then, based on the congestion level around the mobile sales robot 20, the mobile sales robot 20 determines whether to send a rescheduling request requesting the sale of products in a new sales area.

[0107] Then, in S52 , if the mobile sales robot 20 determines to transmit a rescheduling request, it transmits the rescheduling request to the information processing device 30 .

[0108] For example, during the production or sale of merchandise, the mobile sales robot 20 determines whether the congestion level in the sales area has fallen below a preset value. The preset value is, for example, an expected congestion level in the sales area calculated when the operation schedule is generated. Alternatively, the preset value may be, for example, a value predetermined by an administrator. When the congestion level in the sales area falls below the preset value, the mobile sales robot 20 transmits a rescheduling request to the information processing device 30.

[0109] Also, for example, while moving toward a sales area, the mobile sales robot 20 determines whether or not it has detected an area with a higher congestion level than the predicted value of the congestion level in the sales area to which it is heading. If the mobile sales robot 20 detects an area with a higher congestion level than the predicted value of the congestion level in the sales area to which it is heading, it transmits a rescheduling request to the information processing device 30.

[0110] Next, in S53, the information processing device 30 receives a rescheduling request from the mobile sales robot 20. When the information processing device 30 receives the rescheduling request from the mobile sales robot 20, it determines whether or not to have the mobile sales robot 20 sell in a new sales area. When it determines that the mobile sales robot 20 should sell in the new sales area, the information processing device 30 generates a new operation schedule.

[0111] Next, in S54, if the information processing device 30 determines that the mobile sales robot 20 should make sales in a new sales area, it transmits an instruction to change the plan and a new operation schedule to the mobile sales robot 20. If the information processing device 30 determines that the mobile sales robot 20 should not make sales in a new sales area, that is, should continue sales in the current sales area, it transmits an instruction to continue the plan to the mobile sales robot 20.

[0112] Next, in S55, the mobile sales robot 20 receives an instruction to continue the plan or an instruction to change the plan from the information processing device 30. When the mobile sales robot 20 receives an instruction to continue the plan, it continues to operate without changing the current operation schedule. When the mobile sales robot 20 receives an instruction to continue the plan, it starts to operate according to the new operation schedule.

[0113] The information processing device 30 may receive the rescheduling request from a server on the network NW instead of from the mobile sales robot 20. In this case, the server detects the congestion level around the mobile sales robot 20 according to the information from the mobile sales robot 20 and determines whether to send a rescheduling request.

[0114] FIG. 15 is a flowchart showing the flow of a first process performed by the information processing device 30 when a rescheduling request is received.

[0115] When a rescheduling request is received from the mobile sales robot 20 or the server, the information processing device 30 executes processing according to the flow shown in FIG.

[0116] First, in S61, the information processing device 30 calculates a first advertising effectiveness index, which is an advertising effectiveness index when the product is manufactured and sold in a new sales area.

[0117] In addition, if a rescheduling request is received in response to the congestion level in a sales area dropping below a preset value while a product is being manufactured or sold, the information processing device 30 determines a new sales area based on congestion information indicating the congestion level for each location.

[0118] In addition, when a rescheduling request is received in response to the detection of an area with a higher congestion level than the predicted congestion level in the sales area to which the mobile sales robot 20 is heading, the information processing device 30 determines the congested area detected by the mobile sales robot 20 as the new sales area.

[0119] Next, in S62, the information processing device 30 calculates a second advertising effectiveness index, which is an advertising effectiveness index in the case where it is determined that the products will continue to be manufactured in the original sales area before the rescheduling request.

[0120] Next, in S63, the information processing device 30 compares the first advertising effectiveness index with the second advertising effectiveness index. For example, the information processing device 30 determines whether the first advertising effectiveness index is greater than the second advertising effectiveness index.

[0121] If the first advertising effectiveness index is greater than the second advertising effectiveness index (Yes in S63), the information processing device 30 proceeds to S64. If the first advertising effectiveness index is not greater than the second advertising effectiveness index (No in S63), the information processing device 30 proceeds to S66.

[0122] In S64, the information processing device 30 generates an operation schedule for moving to a new sales area to manufacture and sell products. Following S64, in S65, the information processing device 30 transmits the generated operation schedule to the mobile sales robot 20 together with an instruction to change the plan.

[0123] In S66, the information processing device 30 transmits an instruction to continue the plan to the mobile sales robot 20.

[0124] When the information processing device 30 completes the process of S64 or S65, it ends this flow.

[0125] 16 is a flowchart showing the flow of the second process of the information processing device 30 when a rescheduling request is received. When a rescheduling request is received from the mobile sales robot 20 or the server, the information processing device 30 may execute the process according to the flow shown in FIG.

[0126] First, in S71, the information processing device 30 calculates an estimated value of the congestion level in the advertising area where the mobile sales robot 20 emits fragrance to advertise products while moving from the original sales area to the new sales area.

[0127] Next, in S72, the information processing device 30 acquires an actual measurement value of the congestion level in the advertisement area.

[0128] Next, in S73, the information processing device 30 determines whether the actual measurement value is smaller than the estimated value by a predetermined threshold. If the actual measurement value is smaller than the estimated value by the threshold (Yes in S73), the information processing device 30 proceeds to S74. If the actual measurement value is not smaller than the estimated value by the threshold (No in S73), the information processing device 30 proceeds to S78.

[0129] Next, in S74, the information processing device 30 determines whether there is another area where the expected value of the congestion level is equal to or greater than the actual measurement value. If there is another area where the expected value of the congestion level is equal to or greater than the actual measurement value (Yes in S74), the information processing device 30 proceeds to S75. If there is no other area where the expected value of the congestion level is equal to or greater than the actual measurement value (No in S74), the information processing device 30 proceeds to S76.

[0130] In S75, the information processing device 30 generates a new operation schedule for producing goods in other areas where the expected congestion level is equal to or greater than the actual congestion level. Then, the information processing device 30 transmits the generated new operation schedule to the mobile sales robot 20 together with an instruction to change the plan.

[0131] In S76, the information processing device 30 determines whether the mobile sales robot 20 can temporarily stop the manufacturing process of the product. If the manufacturing process of the product can be temporarily stopped (Yes in S76), the information processing device 30 proceeds to S77. If the manufacturing process of the product cannot be temporarily stopped (No in S76), the information processing device 30 proceeds to S78.

[0132] In S77, the information processing device 30 modifies the operation schedule so as to suspend the fragrance-emitting process until the congestion level reaches a certain value or more. Then, the information processing device 30 transmits the modified operation schedule together with an instruction to change the plan to the mobile sales robot 20.

[0133] In S78, the information processing device 30 transmits to the mobile sales robot 20 an instruction to continue the operation schedule without changing it.

[0134] When the information processing device 30 completes the process of S75, S77, or S78, it ends this flow.

[0135] By executing the above-described processing, the mobile sales robot 20 and the information processing device 30 can sell products in a new sales area with higher sales efficiency.

[0136] If the mobile sales robot 20 discovers a crowded area while moving toward a sales area, it may detect whether there is anything other than the mobile sales robot 20 that is attracting customers' attention based on images of the surrounding area. If there is anything other than the mobile sales robot 20 that is attracting customers' attention, the mobile sales robot 20 may not need to send a rescheduling request because the advertising effect would be relatively reduced. Examples of things that attract customers' attention include objects with flashy decorations, other food trucks, or objects that give off strong fragrances, such as perfume shops. If there is anything other than the mobile sales robot 20 that is attracting customers' attention, the information processing device 30 may determine a new sales area where there is nothing that attracts customers' attention in order to relatively increase the advertising effect.

[0137] The mobile sales robot 20 may detect a congested area by using GPS information acquired from the mobile devices of nearby customers in addition to or instead of the captured image of the surrounding area. The mobile sales robot 20 may also detect a congested area by using the usage status of the application of this service.

[0138] Furthermore, when the mobile sales robot 20 finds a crowded area, it may stop there for a certain period of time, monitor the congestion level, and then decide whether to send a scheduling request, rather than immediately sending a rescheduling request. This allows the mobile sales robot 20 to avoid situations where customers are accidentally crowded together.

[0139] The congestion level threshold for transmitting a rescheduling request may be a predetermined value. The congestion level threshold for transmitting a rescheduling request may also be changed depending on other information. For example, the congestion level threshold for transmitting a rescheduling request may be changed to be lower when the weather is bad, or to be higher when an event is being held in the vicinity. Furthermore, if the surrounding wind speed is equal to or higher than a threshold, the mobile sales robot 20 may not transmit a rescheduling request even when it finds a congested area, because the scent generated during product production is carried away by the wind, reducing the advertising effectiveness.

[0140] Furthermore, the information processing device 30 may determine whether to send an instruction to change the plan or to continue the plan by taking into consideration the remaining battery power of the mobile sales robot 20, in addition to comparing the first advertising effectiveness index with the second advertising effectiveness index. For example, even if the information processing device 30 determines that the plan should be changed as a result of comparing the first advertising effectiveness index with the second advertising effectiveness index, it may send an instruction to continue the plan if the number of times the battery is replaced or charged per day increases.

[0141] Furthermore, when the advertising effect is small in both the current sales area and the new sales area, the information processing device 30 may generate a new operation schedule in which the mobile sales robot 20 moves linearly from the current sales area to the new sales area, rather than moving circularly in the advertising area between the current sales area and the new sales area, and starts selling the products in the new sales area as soon as production of the products is completed. In this way, the information processing device 30 can generate an operation schedule that reduces battery consumption due to traveling when the advertising effect is small, and reduces remote monitoring costs.

[0142] Furthermore, when there is a lot of foot traffic at the planned stopping location, the mobile sales robot 20 may perform, for example, a manufacturing process that releases a strong fragrance while stopped and sell the product at that location, and when there is little foot traffic, the mobile sales robot 20 may move to a place with many people and perform the manufacturing process that releases a strong fragrance, thereby increasing the advertising effect.

[0143] Furthermore, by executing the process of releasing a fragrance, there is a possibility that customers who wish to purchase a product will approach the mobile sales robot 20. In that case, if the product is out of stock, the customer will not be able to purchase the product, and the mobile sales robot 20 will lose a sales opportunity. Customers may approach the mobile sales robot 20 because they are attracted by the fragrance, but they do not necessarily want to purchase a product that has just been completed, such as freshly baked bread, and there are also customers who will purchase bread other than freshly baked bread. Therefore, the mobile sales robot 20 may execute the process of releasing a strong fragrance while holding a product ready for sale.

[0144] The mobile sales robot 20 may also move from the sales area to a promotional area different from the sales area periodically or whenever a predetermined event occurs, perform the manufacturing process for releasing a strong fragrance, and then return to the sales area to sell products. In this case, the mobile sales robot 20 may acquire the congestion level of the promotional area. Furthermore, if the congestion level of the promotional area is lower than a first threshold and the congestion level of the sales area is higher than a second threshold, the mobile sales robot 20 may perform the manufacturing process for releasing a strong fragrance in the sales area without moving to the promotional area. Furthermore, if the congestion level of the promotional area is lower than the first threshold and the congestion level of the sales area is lower than a third threshold, the mobile sales robot 20 may delay the execution time of the manufacturing process for releasing a strong fragrance and perform the manufacturing process for releasing a strong fragrance after the congestion level of the sales area reaches or exceeds the third threshold.

[0145] Furthermore, when the mobile sales robot 20 is unable to carry out a manufacturing process that generates a fragrance due to high congestion, the mobile sales robot 20 may instead generate a fragrance using a fragrance. Furthermore, while carrying out a manufacturing process that generates a fragrance, the mobile sales robot 20 may generate a different type of fragrance using a fragrance to enhance the advertising effect of the fragrance generated in the manufacturing process.

[0146] FIG. 17 is a diagram showing an example of an advertising effectiveness index and an operation schedule when a plurality of mobile sales robots 20 are operated.

[0147] The information processing device 30 may collectively generate operation schedules for each of the multiple mobile sales robots 20. In this case, for example, the information processing device 30 generates operation schedules for each of the multiple mobile sales robots 20 so as to maximize the total advertising effectiveness index of the multiple mobile sales robots 20. This allows the information processing device 30 to efficiently advertise products using the multiple mobile sales robots 20, thereby making the products more efficient.

[0148] Furthermore, for example, the information processing device 30 may generate an operation schedule that causes the vehicles to move and sell in a convoy.

[0149] It is thought that customers will approach the mobile sales robot 20 by performing a process that releases a strong fragrance. In this case, if the mobile sales robot 20 does not have products in stock, it will lose a sales opportunity. However, by having multiple mobile sales robots 20 sell products in the vicinity, it is possible to increase the likelihood that one of the mobile sales robots 20 has stock, eliminating the period when the products run out of stock.

[0150] Furthermore, for example, when a plurality of mobile sales robots 20 are caused to move in a line, the information processing device 30 generates an operation schedule so that the sum of the advertising parameters of the plurality of mobile sales robots 20 is equal to or greater than a predetermined value while the mobile sales robots 20 are moving through a location where the congestion level is equal to or greater than a predetermined value. As a result, the information processing device 30 can generate an operation schedule so that, for example, the time period when the advertising parameter is large, for example, the time period when the fragrance parameter is large, is shifted for each mobile sales robot 20, as shown in Fig. 17. As a result, the plurality of mobile sales robots 20 can extend the time period when the advertising parameter is large, for example, the time period when the fragrance parameter is large, thereby increasing opportunities for contact with a large number of customers and increasing the purchasing motivation of a large number of customers.

[0151] 18 is a diagram showing a first example of a sales area when multiple mobile sales robots 20 are operated. When the information processing device 30 collectively generates operation schedules for each of the multiple mobile sales robots 20, the information processing device 30 may set the sales area for each of the multiple mobile sales robots 20, for example, within a predetermined distance. This allows the information processing device 30 to intensively advertise to customers in a relatively small area, thereby more efficiently increasing the purchasing motivation of a relatively small number of customers.

[0152] 19 is a diagram showing a second example of a sales area when multiple mobile sales robots 20 are operated. When the information processing device 30 collectively generates operation schedules for each of the multiple mobile sales robots 20, the sales areas of the multiple mobile sales robots 20 may be set, for example, to be spaced apart by a predetermined distance or more. This allows the information processing device 30 to advertise to customers in a dispersed manner over a relatively wide area, thereby increasing the purchasing motivation of a relatively large number of customers.

[0153] When generating operation schedules for a plurality of mobile sales robots 20 collectively, the information processing device 30 may switch the calculation method of the advertising effectiveness index depending on the advertising strategy, as shown in FIGS. 18 and 19 . For example, the information processing device 30 may generate operation schedules for a plurality of mobile sales robots 20 using an advertising effectiveness index that increases when promising customers are contacted as many times as possible, as shown in FIG. 18 . In this case, however, the information processing device 30 may set an upper limit on the number of contacts with each customer. Furthermore, for example, the information processing device 30 may generate operation schedules for a plurality of mobile sales robots 20 using an advertising effectiveness index that increases when as many customers as possible are contacted, as shown in FIG. 19 .

[0154] In addition, when the information processing device 30 generates the operation schedules of each of the multiple mobile sales robots 20 in a batch, it may generate the operation schedules of each of the multiple mobile sales robots 20 so as to include a mobile sales robot 20 that maximizes the advertising effect and a mobile sales robot 20 that maximizes the sales amount.

[0155] Furthermore, when multiple mobile sales robots 20 are gathered in one place to sell products, the information processing device 30 may generate an operation schedule in which the production completion time of each mobile sales robot 20 is different. This allows the information processing device 30 to extend the period during which an advertising parameter, for example, a fragrance parameter, is large. Furthermore, by varying the production completion time of each mobile sales robot 20 in this way, the information processing device 30 can extend the period during which customers can be attracted.

[0156] For example, if the product is bread, the information processing device 30 may cause other mobile sales robots 20 to gather around the mobile sales robot 20 that is baking bread. This allows the other mobile sales robots 20 to have customers who are attracted by the aroma emitted by the mobile sales robot 20 that is baking bread look at other types of bread. As a result, the other mobile sales robots 20 can have customers purchase not only the bread that has just been baked, but also other types of bread, thereby improving overall sales.

[0157] Furthermore, the mobile sales robot 20 that has baked bread selects a location nearby where there is space for other mobile sales robots 20 to stop, and makes the bread. This allows the other mobile sales robots 20 to move around the mobile sales robot 20 that has baked bread and sell the bread.

[0158] Furthermore, the mobile sales robot 20 may change its schedule to complete production earlier than the production start time determined in advance by the operation schedule, depending on the number of other mobile sales robots 20 in the vicinity. For example, the more other mobile sales robots 20 there are in the vicinity, the earlier the mobile sales robot 20 changes its schedule to complete production. This allows, for example, a mobile sales robot 20 that is baking bread to attract customers, allowing them to see the bread being sold by the other mobile sales robots 20, increasing the chances of them purchasing, and improving overall sales.

[0159] Furthermore, the mobile sales robot 20 that has baked bread may move to the vicinity of another mobile sales robot 20 that has unsold and therefore less attractive bread in its inventory. This allows the mobile sales robot 20 that has baked bread to encourage customers to purchase the unsold and therefore less attractive bread along with the freshly baked bread, thereby improving overall sales. Furthermore, the mobile sales robot 20 that has unsold and therefore less attractive bread in its inventory may emit a fragrance using a fragrance if there is no mobile sales robot 20 currently making bread nearby.

[0160] Furthermore, each of the multiple mobile sales robots 20 may emit a different type of fragrance. In this case, the information processing device 30 generates an operation schedule for each of the multiple mobile sales robots 20 so that different types of fragrances are not emitted in the same area. This allows the information processing device 30 to prevent scents from interfering with each other in the sales area. Furthermore, each of the multiple mobile sales robots 20 may temporarily suspend a product manufacturing process if another mobile sales robot 20 emitting a different type of fragrance in the same area is performing a manufacturing process in which a scent is emitted.

[0161] Furthermore, each of the multiple mobile sales robots 20 may emit a different type of scent. The information processing device 30 generates an operation schedule in which a first mobile sales robot 20 among the multiple mobile sales robots 20 emits a scent in a first area and then moves the first mobile sales robot 20 from the first area to another area. In this case, the information processing device 30 may generate an operation schedule in which a second mobile sales robot 20 among the multiple mobile sales robots 20 moves to the first area within an interval time during which the scent remains in the first area after the first mobile sales robot 20 moves from the first area to another area. Even if the mobile sales robot 20 does not emit a scent, a sufficient advertising effect can be achieved during the period during which the scent remains in the first area. Therefore, the information processing device 30 can efficiently sell products by moving the mobile sales robot 20 to the first area within the interval time during which the scent remains in the first area. The information processing device 30 may generate an operation schedule by increasing or decreasing the interval period depending on the type of product that emits the fragrance, the wind speed in the first area, and the like.

[0162] FIG. 20 is a diagram showing an example of the appearance of the mobile sales robot 20.

[0163] The mobile sales robot 20 may be provided with a display device 91 for displaying text or image information to customers. This allows the mobile sales robot 20 to advertise to customers using a method other than advertising parameters.

[0164] The mobile sales robot 20 may also display the remaining time until the production of the product is completed on the display device 91. After the production of the product is completed, the mobile sales robot 20 may also display the planned sales location where the product will be sold next.

[0165] Furthermore, the mobile sales robot 20 may have a portion, such as the side surface 92, made of a transparent material such as glass, so that the product manufacturing process can be seen by customers. In this way, for example, if the product is a smoothie, the mobile sales robot 20 can allow customers to see the process of stirring the liquid during manufacturing, creating a visual advertising effect and increasing customer willingness to purchase.

[0166] In addition, when there are an excessive number of customers, the mobile sales robot 20 can only provide a visual advertising effect to a portion of the total number of customers. Therefore, when generating an operation schedule using advertising parameters that represent visual advertising effects, the information processing device 30 may use an advertising effect index whose value decreases when there are an excessive number of customers.

[0167] Furthermore, if it is predicted that a sufficient advertising effect will be obtained, the mobile sales robot 20 that is cooking may display on the display devices 91 of other mobile sales robots 20 manufacturing processes that will generate a visual advertising effect, such as the process of stirring liquid during manufacturing. In this way, the mobile sales robot 20 that is cooking can provide a visual advertising effect to customers who cannot see the mobile sales robot 20, thereby increasing the customers' willingness to purchase.

[0168] In addition, in many cases, products such as smoothies are manufactured and sold in the same place. In such cases, the information processing device 30 may predict sales separately from the advertising effectiveness index and determine the sales area taking into consideration the advertising effectiveness index and the sales prediction.

[0169] FIG. 21 is a diagram showing a modified example of the mobile sales system 10. In FIG.

[0170] The mobile sales system 10 may further include one or more user terminal devices 94. Each of the one or more user terminal devices 94 is communicably connected to the information processing device 30 via a network NW or the like.

[0171] Each of the one or more user terminal devices 94 has a hardware configuration similar to that of a typical computer, including a processor and a storage device, and executes information processing according to a program. Each of the one or more user terminal devices 94 is carried by a user. For example, each of the one or more user terminal devices 94 is a smartphone, a tablet device, a notebook computer, or the like. When each of the one or more user terminal devices 94 launches an application program, it can receive information from the information processing device 30.

[0172] The information processing device 30, for example, acquires location information of the user terminal device 94 and displays information about the mobile sales robot 20 on the user terminal device 94. For example, the information processing device 30 may display on the user terminal device 94 information indicating what kind of product the mobile sales robot 20 closest to the user terminal device 94 is manufacturing and information indicating when the product will be completed. The information processing device 30 may also display information indicating where a specified product can be purchased. The information processing device 30 may also display on the user terminal device 94 information indicating whether other mobile sales robots 20 are manufacturing the same product or a similar product to the product being manufactured by the mobile sales robot 20 closest to the user terminal device 94 and where the other mobile sales robots 20 are located.

[0173] The information processing device 30 may also display on the user terminal device 94 information showing a list of products manufactured and sold in the area on that day by one or more mobile sales robots 20, and information allowing the user to search for a specific product from the list. The information processing device 30 may also provide a notification to the user via the user terminal device 94 when the manufacturing of a product designated in advance by the user is completed. The information processing device 30 may also provide a notification to the user via the user terminal device 94 when a mobile sales robot 20 manufacturing and selling a product designated in advance by the user arrives near the user or in an area designated by the user.

[0174] The user terminal device 94 may also accept, via an application program, user operation to register one or more products manufactured by the mobile sales robot 20 as favorites. In this case, for example, the information processing device 30 accepts, from each of one or more user terminal devices 94, information about the favorite products registered by the user and location information indicating the user's location. For each of one or more mobile sales robots 20, the information processing device 30 may set an area where many users have registered the manufactured product as a favorite as a congested area, or calculate the congested area based on the number of users who have registered the manufactured product as a favorite. Then, the information processing device 30 generates an operation schedule for each of one or more mobile sales robots 20 based on the congested area thus set or calculated.

[0175] FIG. 22 is a diagram showing the hardware configuration of the information processing device 30.

[0176] The information processing device 30 has a hardware configuration that utilizes a typical computer, with a CPU (Central Processing Unit) 102, a ROM (Read Only Memory) 104, a RAM (Random Access Memory) 106, an I / F 108, etc. interconnected by a bus 88.

[0177] The CPU 102 is a computing device that controls the information processing device 30. The ROM 104 stores programs and the like that realize information processing by the CPU 102. The RAM 106 stores data necessary for various processes by the CPU 102. The I / F 108 is an interface that is connected to a storage unit, an input unit, an output unit, a sensor, a communication unit, and the like, and is used to send and receive data.

[0178] In the information processing device 30, the CPU 102 reads out a program from the ROM 104 onto the RAM 106 and executes it, thereby realizing each function of the information processing device 30 on the computer.

[0179] The programs for executing the processes executed by the information processing device 30 may be stored in a hard disk drive (HDD). Also, the programs for executing the processes executed by the information processing device 30 may be provided by being pre-installed in the ROM 104.

[0180] Furthermore, the program for executing the processes executed by the information processing device 30 may be stored in an installable or executable file format on a computer-readable storage medium such as a CD-ROM, CD-R, memory card, DVD (Digital Versatile Disk), or flexible disk (FD) and provided as a computer program product. Furthermore, the program for executing the information processing executed by the information processing device 30 may be stored on a computer connected to a network such as the Internet and provided by downloading via the network. Furthermore, the program for executing the information processing executed by the information processing device 30 may be provided or distributed via a network such as the Internet.

[0181] Although the embodiments have been described above, they are presented as examples and are not intended to limit the scope of the invention. This novel embodiment can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. This embodiment and its modifications are included within the scope and spirit of the invention, and are also included in the inventions and their equivalents as defined in the claims.

[0182] REFERENCE SIGNS LIST 10 Mobile sales system 20 Mobile sales robot 30 Information processing device 41 Memory unit 42 Position information acquisition unit 43 Camera 44 Image acquisition unit 45 Image analysis unit 46 Drive unit 47 Travel control unit 48 Manufacturing unit 49 Manufacturing control unit 50 Sales unit 51 Sales control unit 52 Plan change request unit 53 First communication unit 61 Second communication unit 62 Map data storage unit 63 Congestion information storage unit 64 Congestion information update unit 65 Manufacturing information storage unit 66 Control unit 67 Schedule generation unit 68 Schedule change determination unit

Claims

1. A schedule generation method for generating an operation schedule for a robot that manufactures products and moves autonomously, comprising: a first step of acquiring a congestion level for each location; a second step of acquiring time transition data of advertising parameters that increase customer purchasing motivation while the robot is manufacturing the products; and a third step of generating the operation schedule based on the congestion level for each location and the time transition data of the advertising parameters, to increase an advertising effectiveness index that represents the advertising effectiveness given to customers while the robot is moving.

2. The schedule generation method according to claim 1, wherein in the third step, the operation schedule is generated based on a solution to an optimization problem that maximizes an objective function that represents the advertising effectiveness index.

3. The schedule generation method according to claim 1, wherein the product is a food product, the robot is capable of manufacturing a finished product from ingredients of the food product, and the advertising parameter is a fragrance parameter that represents the strength of a fragrance generated in the process of manufacturing the food product.

4. The schedule generation method according to claim 1, wherein in the third step, an operation schedule is generated in which the robot moves so as to maximize the advertising effectiveness index under the condition that the product will be completed by the time the robot arrives at the sales area where the product is sold.

5. A schedule generation method as described in claim 1, wherein in the first step, a ratio for each location and for each customer segment representing the customer category is obtained; in the second step, a matching index representing the possibility of purchasing the product for each customer segment is obtained; the advertising effectiveness index is calculated based on the corrected congestion level for each customer segment and each location and the time transition data of the advertising parameters; and the corrected congestion level for each location is calculated by correcting the congestion level for each location by the ratio for each location and the matching index.

6. The schedule generation method according to claim 5, wherein the robot is capable of manufacturing a plurality of types of the product, and in the second step, the matching index is obtained for each type of product and each customer segment, and the advertising effectiveness index is calculated using the matching index corresponding to the type of product to be manufactured.

7. A schedule generation method as set forth in claim 1, further comprising: a fourth step of receiving a rescheduling request from the robot or server requesting the sale of the product in a new sales area; and a fifth step of, when the rescheduling request has been received, determining whether or not to sell the product in the new sales area by comparing the advertising effectiveness index in the case where the product is moved to the new sales area and manufactured and sold there with the advertising effectiveness index in the case where the product is continued to be manufactured and sold in the sales area prior to the rescheduling request, wherein, when it is determined that the product will be sold in the new sales area, in the third step, the operation schedule for the case where the product will be sold in the new sales area is generated.

8. The schedule generation method according to claim 7, wherein the robot transmits the rescheduling request when the congestion level in the sales area falls below a preset value while the product is being manufactured or sold.

9. The schedule generation method according to claim 7, wherein the robot sends the rescheduling request if, during movement, the robot discovers the new sales area with a higher congestion level than the sales area prior to the rescheduling request.

10. A schedule generation method as described in claim 7, wherein in the fifth step, it is further determined whether or not to make a sale in the new sales area based on the remaining battery charge if the sale were made in the sales area before the rescheduling request and the remaining battery charge if the sale were made in the new sales area.

11. The schedule generation method according to claim 1, wherein in the third step, the congestion level for each location is corrected based on weather information for each location or information about events being held for each location.

12. A schedule generation method according to claim 1, wherein in the third step, the operation schedules of the plurality of robots are generated so as to increase the total value of the advertising effectiveness index of the plurality of robots.

13. A schedule generation method as described in claim 12, wherein the operation schedule is generated such that a plurality of the robots are moved in a formation and the total value of the advertising parameters of the plurality of the robots is equal to or greater than a predetermined value during a period when the robots are moving through a location where the congestion level is equal to or greater than a predetermined value.

14. A robot that manufactures and moves products autonomously, which receives an operation schedule generated by an information processing device, manufactures and moves the products in accordance with the received operation schedule, and the operation schedule is generated by the information processing device based on the congestion level at each location and time transition data of an advertisement parameter that increases customer purchasing motivation during the manufacture of the products, so as to increase an advertising effectiveness index that represents the advertising effectiveness given to the customer while moving.

15. A program for causing an information processing device to generate an operation schedule for a robot that manufactures products and moves autonomously, the program causing the information processing device to execute: a first step of acquiring the congestion level for each location; a second step of acquiring time transition data of advertising parameters that increase customer purchasing motivation while the robot is manufacturing the products; and a third step of generating the operation schedule that increases an advertising effectiveness index that represents the advertising effectiveness given to customers while the robot is moving, based on the congestion level for each location and the time transition data of the advertising parameters.

Images