Mobile body controller and method for controlling mobile body

Abstract

To efficiently arrange a plurality of drones for delivering items, in a plurality of stations.SOLUTION: The mobile body controller according to an embodiment includes specification units and an arrangement control unit. The specification units are each arranged in one of a plurality of stations, and each specification unit specifies an arrangement destination station of a plurality of drones for delivering items in a distribution area of the arranged station on the basis of the positions of the drones and the remaining amount of a battery. An arrangement control unit arranges a drone in the arrangement destination station specified by the specification unit. The distribution area is set according to a drone flying prohibited area.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The disclosed embodiments relate to a mobile object control device and a mobile object control method. [Background technology]

[0002] Conventionally, a system for controlling multiple drones is known (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-131332 A Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology has the problem that it may not be possible to efficiently deploy multiple drones delivering goods at multiple stations.

[0005] The present invention has been made in consideration of the above, and aims to efficiently deploy multiple drones that deliver goods at multiple stations. [Means for solving the problem]

[0006] A mobile object control device according to one aspect of an embodiment includes an identification unit and a placement control unit. The identification unit identifies a placement station for a plurality of drones, each of which is placed at one of a plurality of stations and delivers goods within a delivery area of ​​the station, based on the position and remaining battery level of the drones. The placement control unit places the drone at the placement station identified by the identification unit. The delivery area is set according to an area where the drones cannot fly. Effect of the Invention

[0007] According to one aspect of the embodiment, multiple drones delivering items can be efficiently deployed to multiple stations. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an outline of a mobile object control system according to an embodiment. [Diagram 2] FIG. 2 is a functional block diagram showing an outline of the mobile object control device according to the embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of a flight range according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a delivery area according to the embodiment. [Diagram 5] FIG. 5 is a diagram illustrating an example of demand information according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of remaining battery level information according to the embodiment. [Figure 7] FIG. 7 is a flowchart illustrating the arrangement process of the mobile body control device according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of the second battery remaining amount information according to the embodiment. [Figure 9] FIG. 9 is a diagram showing another example of demand information according to the embodiment. [Figure 10] FIG. 10 is a flowchart illustrating the placement process of a drone that needs to be charged according to the embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of a hardware configuration of a computer that functions as a mobile object control device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] The present invention will be described below through embodiments, but the following embodiments do not limit the scope of the invention according to the claims. In addition, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0010] A mobile object control system according to an embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an overview of the mobile object control system according to an embodiment.

[0011] As shown in Fig. 1, the mobile object control system includes a mobile object control device 10, a drone 20a, a drone 20b, and a drone 20c. In the following description, the drones included in the mobile object control system may be referred to as drone 20 without distinction. In addition, the number of drones included in the mobile object control system is not limited to the number shown in the figure. The number of drones may be two or less, or four or more.

[0012] The mobile control device 10 is connected to the drone 20 via a network N. The network N is, for example, a mobile communication network such as LTE (Long Term Evolution) or 5G. The network N may include multiple networks. For example, the network N may include a public communication line such as the Internet in addition to the above-mentioned mobile communication network.

[0013] The drone 20 is an example of a moving object. The drone 20 is a multicopter equipped with multiple (for example, four) rotor propellers, and performs unmanned autonomous flight. The drone 20 is also powered by a battery.

[0014] The drone 20 has a mechanism (such as a box, a basket, or a robot arm) for holding an item. The drone 20 also transports (delivers) the held item to a specified location.

[0015] The drone 20 includes a communication module for performing wireless communication via the network N. The drone 20 also includes various sensors such as an acceleration sensor, a gyro sensor, and an optical sensor (camera). The drone 20 also includes a computer (e.g., a microcomputer) that executes a positioning function for measuring its own position, an attitude control function for controlling its attitude, and the like.

[0016] The mobile object control device 10 controls the movement of the drone 20. The mobile object control device 10 specifies a destination position for the drone 20.

[0017] In this embodiment, the mobile object control system is used to provide an item delivery service using a drone 20. For example, the delivery service is a food delivery service that delivers food to a user.

[0018] The mobile control device 10 controls the placement of the drones 20, thereby helping to provide efficient delivery services.

[0019] Here, a delivery service has a designated service area, and the drone 20 delivers items to users within the service area.

[0020] In addition, a station is provided within or near the provision area. The station is a facility where drones can land and take off. The station may be a flat surface on which multiple drones 20 can be placed.

[0021] The drone 20 waits at the station. Then, when a delivery instruction is received, the drone 20 takes off from the station while holding the item and moves to the location of the delivery destination. The drone 20 then returns from the delivery destination to the station and waits until an instruction is received.

[0022] The station may be integral with a facility for preparing the articles to be distributed, or may be separate from the facility for preparing the articles to be distributed.

[0023] For example, if the delivery service is a food delivery service, the station may be a container vehicle parked in a parking lot and equipped on the roof of the container vehicle with a kitchen for preparing the food to be delivered.

[0024] On the other hand, the station may be provided at a location separate from the kitchen for preparing the food to be delivered. For example, if the food is prepared in a hotel restaurant, the station may be provided on the rooftop or in a parking lot of the hotel.

[0025] A charging station for charging the battery of the drone 20 is provided at the same location as the station where the drone 20 waits or at a different location. For example, the battery of the drone 20 is charged by the drone 20 entering a dock provided in the charging station. In addition, the battery of the drone 20 may be replaced with a charged battery at the charging station.

[0026] In addition, the delivery area of ​​goods for drones launched from each station is set by the mobile control device 10 according to a predetermined flight range.

[0027] This flight range is determined based on the number of residents who are the recipients of the delivery service, the flight range of the drone 20, the tolerance for deterioration of the quality of the goods over time (e.g., deterioration of food), etc. The flight range may be changed depending on the goods to be delivered, the remaining battery power of the drone 20, etc.

[0028] The mobile control device 10 determines the delivery area from a preset flight range according to at least one of the no-fly areas of the drone 20 and the weather. For example, the mobile control device 10 sets the delivery area so that the drone 20 does not fly in the no-fly areas. Details of the delivery area will be described later.

[0029] In this case, in a delivery service, when a delivery request is made for an item to be delivered to a certain delivery destination, if the drone 20 is not waiting at a station whose delivery area includes the delivery destination, the item will not be delivered until the station is stocked with drones 20. This causes delivery delays and leads to a decline in the quality of the delivery service.

[0030] Therefore, the mobile object control device 10 of the present embodiment controls the placement of the drones 20 at each station so as to prevent delivery delays. At this time, the mobile object control device 10 controls the placement taking into consideration not only the number of drones 20 but also the charging status of the drones 20.

[0031] The configuration of the mobile object control device 10 will be described with reference to Fig. 2. Fig. 2 is a functional block diagram showing an overview of the mobile object control device according to the embodiment.

[0032] As shown in FIG. 2, the mobile object control device 10 includes a communication unit 11, a storage unit 12, and a control unit 13.

[0033] The communication unit 11 is connected to the network N by wire or wirelessly. The communication unit 11 transmits and receives information to and from the drone 20 via the network N.

[0034] The storage unit 12 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk drive (HDD), a solid state drive (SSD), an optical disk, etc. Various programs and various data are stored in the storage unit 12. The storage unit 12 stores area information 121, demand information 122, and remaining battery information 123.

[0035] The area information 121 is information indicating a delivery area. The area information 121 indicates a delivery area for each station. As described above, the delivery area is set according to the flight range of the drone 20. First, the flight range of the drone 20 will be described.

[0036] FIG. 3 is a diagram showing an example of a flight range according to an embodiment. In FIG. 3, the flight range is shown superimposed on a geographical map in which the service area is divided by a grid. Note that the grid shown here is an example. The map may be divided by a fine grid or a coarse grid. Furthermore, the grid is not limited to a rectangular shape. The grid may be triangular or hexagonal. Further, the following description will be given with grids shown for the demand information 122 and the battery remaining amount information 123, but the grids shown in each piece of information may be the same size and shape or may be different sizes and shapes.

[0037] The columns of the grid are assigned letters. The rows of the grid are assigned numbers. The cells of the grid are represented by a combination of letters and numbers. For example, the cell in column B, row 3 where station 31 is located in Figure 3, is cell B3.

[0038] The range of a rectangle is represented by the cell at the top left corner and the cell at the bottom right corner of the rectangle. For example, the range of the rectangle with the pattern in Figure 3 is represented as A1:E6.

[0039] 3 also shows a station 31, a station 32, and a station 33. Note that although the number of stations is assumed to be three here, the number of stations may be two or less, or four or more.

[0040] 3 also shows flight ranges 311, 321, and 331. Flight range 311 is a range in which the drone 20 placed at station 31 can fly with goods loaded. Flight range 321 is a range in which the drone 20 placed at station 32 can fly with goods loaded. Flight range 331 is a range in which the drone 20 placed at station 33 can fly with goods loaded.

[0041] In the example of FIG. 3, flight range 311, flight range 321, and flight range 331 are ranges indicated by circles of radius R centered on station 31, station 32, and station 33, respectively.

[0042] Note that, here, flight range 311, flight range 321, and flight range 331 are all assumed to have the same radii R, but flight range 311, flight range 321, and flight range 331 may each have a different radii.

[0043] Furthermore, the shapes of flight range 311, flight range 321, and flight range 331 are not limited to circles. The shapes of flight range 311, flight range 321, and flight range 331 may be set based on the number of residents covered by the delivery service, the flight range of drone 20, the tolerance for deterioration of the quality of goods over time, and the like. Flight range 311, flight range 321, and flight range 331 may be set using cells obtained by dividing a geographical map of the service area into a grid.

[0044] In the following description, when there is no need to distinguish between the flight range 311, the flight range 321, and the flight range 331, they will be simply referred to as the flight range 310. The flight range 310 is assumed to be stored in the storage unit 12 as the area information 121, for example.

[0045] Here, the drone 20 may not necessarily be able to fly within the entire flight range 310. For example, there may be cases where areas where flight is prohibited for the drone 20 are set by law or the like. Furthermore, there may be cases where areas where the drone 20 cannot fly arise due to rain, strong winds, or the like. Such areas where the drone 20 cannot fly are referred to as no-fly areas 300. In the example of FIG. 3, the range F5:G7 is the no-fly area 300.

[0046] The mobile object control device 10 corrects the flight range 310 in accordance with this no-fly area 300, and sets the delivery area. For example, the mobile object control device 10 sets the delivery area excluding the flight range 310.

[0047] 4 is a diagram showing an example of a delivery area according to an embodiment. The delivery area 311A ​​is an area in which the drone 20 placed in the station 31 delivers goods. The delivery area 311A ​​is an area obtained by excluding the no-fly area 300 from the flight range 311.

[0048] The delivery area 321A is an area in which the drone 20 placed at the station 32 delivers goods. The delivery area 321A is an area obtained by excluding the no-fly area 300 from the flight range 321.

[0049] The delivery area 331A is the range in which the drone 20 deployed at the station 33 delivers goods. The delivery area 331A is the range in which goods can be delivered within a specified time (or a specified distance) when the no-fly area 300 is excluded from the flight range 331 and the drone 20 flies while avoiding the no-fly area 300. Note that hereinafter, when there is no need to distinguish between the delivery area 311A, the delivery area 321A, and the delivery area 331A, they are also simply referred to as the delivery area 310A.

[0050] The delivery area 330A is set by the mobile object control device 10 and stored in the storage unit 12 as area information 121.

[0051] Demand information 122 is information that indicates the demand for delivery services at each location within the service area. Demand information 122 indicates the demand for each cell obtained by dividing a geographical map of the service area into a grid. Demand is, for example, the frequency with which locations designated as delivery destinations are included in each cell.

[0052] Fig. 5 is a diagram illustrating an example of demand information according to an embodiment. The demand information 122 can be visualized as a heat map as shown in Fig. 5. Fig. 5 illustrates a grid superimposed on a geographic map of the service area.

[0053] 5 also shows stations 31, 32, and 33. Also shown are delivery area 311A, delivery area 321A, and delivery area 331A.

[0054] Here, the demand information 122 is a numerical representation of the magnitude of demand in each cell. The magnitude of demand may be the sum of the actual values ​​of the number of times each cell was designated as a delivery destination in a certain period of time in the past. Alternatively, the magnitude of demand may be the number of times each cell will be designated as a delivery destination in a certain period of time, predicted based on explanatory variables such as the past actual values, the number of residents, weather, and time of day. The prediction is performed, for example, by a machine learning model.

[0055] In Fig. 5, a pattern is applied to each cell according to the level of demand. For example, a cell with a higher demand is filled with a darker color or a denser pattern.

[0056] The range A1:E6 in Figure 5 has a higher demand than the other cells. Within the range A1:E6, the range B2:D5 has an even higher demand.

[0057] The demand information 122 may be generated by the mobile body control device 10, or may be acquired from an external device (such as a server device) that communicates with the mobile body control device 10. The demand information 122 may be generated or acquired prior to the placement process each time the placement process described below is performed, or may be generated or acquired, for example, at a predetermined cycle or in a predetermined time period, regardless of the placement process.

[0058] The battery remaining information 123 is information indicating the battery status of the drone 20 at each location in the service area. Like the demand information 122, the battery remaining information 123 indicates the battery status for each cell obtained by dividing the geographical map of the service area into a grid.

[0059] For example, the more drones 20 waiting at a station, the less likely delivery delays will occur within the area in which goods can be delivered from that station.

[0060] On the other hand, when the remaining battery charge of the drone 20 falls below a certain value, the drone 20 moves to a charging station and charges the battery. While the battery is being charged, the drone 20 cannot deliver goods. For this reason, a drone 20 with a low remaining battery charge will need to be charged immediately, and it is considered that the drone 20 cannot fully meet demand.

[0061] The battery remaining amount information 123 is information regarding the number of drones 20 present in each cell and the remaining battery amount of each drone 20. Note that the drone 20 present in the cell may be waiting at a station that includes the cell in its range, or may be moving through the cell.

[0062] In addition, the battery remaining amount information 123 may be an actual measured value of the number of drones 20 and the remaining battery amount at a certain point in time, or a predicted value after a certain period of time.

[0063] The battery remaining amount information 123 is generated by the mobile object control device 10 based on the position information and the battery remaining amount acquired from the drone 20. The mobile object control device 10 stores the generated battery remaining amount information 123 in the storage unit 12.

[0064] The battery remaining amount information 123 may be generated prior to the deployment process each time the deployment process described below is performed, or may be generated, for example, at a predetermined cycle or during a predetermined time period, regardless of the deployment process.

[0065] Fig. 6 is a diagram showing an example of battery remaining amount information according to an embodiment. Battery remaining amount information 123 can be visualized as shown in Fig. 6. Fig. 6 shows a grid superimposed on a geographical map of the service area, similar to Fig. 5.

[0066] Here, when the remaining battery level falls below 30% and the drone 20 is not currently making a delivery, it is assumed that the drone 20 will charge. Also, it is assumed that approximately 10% to 20% of the battery is consumed in one delivery. Therefore, it is assumed that the drone 20 with the remaining battery level of 30% to 50% will need to be charged after making one or two remaining deliveries, and therefore cannot fully meet demand.

[0067] 6, a pattern is applied to each cell according to the number of drones 20 with a remaining battery charge of 50% or more. For example, a first color (or a first pattern) is applied to cells in which the number of drones 20 with a remaining battery charge of 50% or more is equal to or greater than a threshold (e.g., 10), and a second color (or a second pattern) is applied to cells in which the number of drones 20 with a remaining battery charge of less than 50% is equal to or greater than a threshold.

[0068] In addition, the color intensity and pattern density may vary depending on the number of drones 20 with battery levels above 50% or below 50%.

[0069] For example, in the range A1:E5 in Fig. 6, the number of drones 20 whose remaining battery power is less than 50% is equal to or greater than the threshold. Also, for example, in the range F8:J10 in Fig. 6, the number of drones 20 whose remaining battery power is 50% or more is equal to or greater than the threshold.

[0070] Even if there are many drones 20 in range A1:E5, if most of them have less than 50% battery remaining, the demand may not be fully met within that range.

[0071] In addition, if the condition that the number of drones 20 with remaining battery levels of less than 50% is greater than or equal to a threshold and the condition that the number of drones 20 with remaining battery levels of 50% or more is greater than or equal to a threshold are simultaneously met, the condition that the number of drones 20 with remaining battery levels of 50% or more is greater than or equal to a threshold takes priority.

[0072] For example, in the range A1:E5, the number of drones 20 with a remaining battery level of 50% or more is unlikely to be equal to or greater than the threshold. On the other hand, in the range F8:J10, the number of drones 20 with a remaining battery level of less than 50% may be equal to or greater than the threshold. This is because the remaining battery level information 123 is information intended to identify areas (stations) where demand is not being met.

[0073] 2, the control unit 13 is a controller and includes, for example, a microcomputer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM, an input / output port, and various other circuits. The control unit 13 may also be configured with hardware such as an integrated circuit, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 13 includes a setting unit 131, a specifying unit 132, and a placement control unit 133.

[0074] The setting unit 131 sets the delivery area. For example, the setting unit 131 sets the delivery area prior to the placement process each time the placement process described below is performed. Alternatively, the setting unit 131 may generate the delivery area, for example, at a predetermined cycle or in a predetermined time period, regardless of the placement process.

[0075] First, the setting unit 131 acquires the flight range 310 from the storage unit 12. The setting unit 131 also acquires the no-fly area 300. For example, if the no-fly area 300 is a no-fly area 300 that is predetermined by law or the like, the setting unit 131 acquires the no-fly area that is stored in advance in the storage unit 12.

[0076] For example, if the no-fly area 300 is an area that changes with time, such as the weather, the setting unit 131 acquires the no-fly area 300 from an external device (such as a server device). Alternatively, the setting unit 131 may acquire weather information, etc., and set the no-fly area 300 from the acquired weather information, etc. The weather information may be information about the weather at the time the setting unit 131 sets the no-fly area, or may be forecast information for a certain period of time after the weather.

[0077] The setting unit 131 sets the delivery area 310A according to the flight range 310 and the no-fly area 300. For example, when the no-fly area 300 is located on the outer periphery of the flight range 320, the setting unit 131 sets the range excluding the no-fly area 300 from the flight range 320 as the delivery area 310A. When the no-fly area 300 is included inside the flight range 320, the setting unit 131 sets the delivery area to the range in which the no-fly area 300 can be delivered within a predetermined time (or a predetermined distance) when the drone 20 flies while avoiding the no-fly area 300 after excluding the no-fly area 300 from the flight range 320.

[0078] The setting unit 131 stores the set delivery area 310A in the storage unit 12 as the area information 121. The setting unit 131 may generate at least one of the demand information 122 and the battery remaining amount information 123.

[0079] The identification unit 132 identifies a station among the multiple stations whose drone 20 deployment status does not satisfy a condition based on the positions and remaining battery power of multiple drones 20, each of which is deployed at one of the multiple stations and delivers goods to an area corresponding to the deployed station.

[0080] For example, each time the drone 20 takes off from any of the multiple stations, the identification unit 132 identifies a station among the multiple stations where the deployment status of the drone 20 does not satisfy a condition.

[0081] The placement control unit 133 places the drone 20 at the station (destination station) identified by the identification unit 132.

[0082] The processing of the identification unit 132 and the arrangement control unit 133 will be specifically described with reference to the examples of FIG. 5 and FIG.

[0083] The identification unit 132 identifies stations among the multiple stations whose drone 20 deployment conditions do not satisfy the conditions based on the number of drones 20 present and the remaining battery power of the drones 20 present in each cell obtained by dividing all areas in which goods are distributed into a grid.

[0084] First, as shown in Figure 5, the range A1:E6 is an area with high demand, and the range B2:D5 is an area with particularly high demand.

[0085] A part of the range A1:E6 is not included in the delivery area 321A or the delivery area 331A, but is included in the delivery area 311A. In other words, delivery of goods to the part of the range A1:E6 needs to be performed by a drone 20 arranged at a station 31 that can deliver to the delivery area 311A.

[0086] Therefore, sufficient drones 20 must be deployed at station 31 to prevent delivery delays.

[0087] In this way, the identification unit 132 identifies stations that require sufficient drones 20 to be deployed based on the demand information 122. For example, the identification unit 132 identifies stations that can deliver to areas with high demand. The identification unit 132 may also prioritize each station based on the amount of demand in the areas included in the range. If a no-fly area 300 exists between the area with high demand and a station, the identification unit 132 may assign a lower priority to the station.

[0088] Next, the identification unit 132 refers to the remaining battery information 123 shown in Fig. 6. Fig. 6 shows that there are many drones 20 with remaining battery power of less than 50% in the range A1:E5. Note that cells without any pattern indicate that the number of drones 20 is small to begin with, that is, the number of drones 20 with remaining battery power of less than 50% and the number of drones 20 with remaining battery power of 50% or more do not exceed the threshold.

[0089] The identification unit 132 identifies a station where a sufficient number of drones 20 need to be deployed and where there are not enough drones 20 within range with a remaining battery level of 50% or more. For example, in the examples of FIGS. 5 and 6, the identification unit 132 identifies the station 31.

[0090] The placement control unit 133 places the drone 20 at the station 31 identified by the identification unit 132. Specifically, the placement control unit 133 transmits a placement instruction to the drone 20. Furthermore, the drone 20 that receives the instruction moves to the placement destination station and waits at the station. Note that the drone 20 to which the placement control unit 133 transmits an instruction may be a drone 20 waiting at the placement source station, or may be a drone 20 delivering an item within the range of the placement source station.

[0091] For example, there are a sufficient number of drones 20 with battery levels of 50% or more in the range F8:J10, and the demand for the delivery area 311A ​​is not high. For this reason, the placement control unit 133 places the drones 20 placed at the station 33 at the station 31.

[0092] The flow of the placement process of the mobile body control device 10 will be described with reference to Fig. 7. Fig. 7 is a flowchart illustrating the placement process of the mobile body control device 10 according to the embodiment. The placement process is executed by the mobile body control device 10 when the drone 20 departs from the station, for example. Alternatively, the placement process may be executed at a fixed cycle.

[0093] 7, first, the mobile object control device 10 sets a delivery area 310A by the drone 20 (step S101). For example, the mobile object control device 10 sets the delivery area 310A according to the no-fly area 300 based on a predetermined flight range 310.

[0094] The mobile object control device 10 identifies an area where there is a high demand for delivery by drone (step S102). The mobile object control device 10 can identify an area where there is a high demand based on the demand information 122.

[0095] Next, the mobile object control device 10 identifies the drone deployment status for each area taking into account the remaining battery power (step S103). In particular, the mobile object control device 10 can identify areas where there are many drones 20 but the remaining battery power is insufficient, based on the remaining battery power information 123.

[0096] Then, the mobile object control device 10 deploys the drones so that the demand is met while ensuring the remaining battery power (step S104). For example, the mobile object control device 10 changes the deployment of the drones 20 from an area where there are many drones 20 with sufficiently charged batteries and where there is not much demand to an area where there are many drones 20 with insufficiently charged batteries and where there is high demand.

[0097] [About placement processing] The placement process by the mobile object control device 10 is not limited to that described with reference to Figures 5 to 7. For example, the mobile object control device 10 may specify the number of drones 20 to be placed at each station, and determine the placement of the drones 20 according to the specified number of drones 20, the remaining battery power of the drones 20, and the positions of the drones 20.

[0098] As described above, the range A1:E6 shown in FIG. 5 is an area with high demand. In addition, the range B2:D5 is an area with particularly high demand. The delivery area 311A ​​includes the entire range A1:E6. The delivery area 321A and the delivery area 331A each include a part of the range A1:E6.

[0099] The identification unit 132 of the mobile control device 10 determines the number of drones 20 to be placed at the station according to the area (e.g., the number of cells) of the high-demand area included in the delivery area 310A. When the high-demand area is included in multiple delivery areas 310A, the identification unit 132 determines the number of drones 20 to be placed at multiple stations according to, for example, the distance between the area and the station.

[0100] In the example of FIG. 5, range A1:D2 and range A3:C3 are included in delivery area 311A. Of these ranges, range B2:D2 and range B3:C3 are areas of particularly high demand. Range A4:C6 is included in delivery area 311A ​​and delivery area 321A. Of these ranges, range B4:C5 is an area of ​​particularly high demand. Range E2:E4 is included in delivery area 311A ​​and delivery area 331A. Range D4:D5 and range E5:E6 are included in delivery area 311A, delivery area 321A, and delivery area 331A. Of these ranges, range D4:D5 is an area of ​​particularly high demand.

[0101] For example, it is assumed that the number of drones 20 to be deployed according to the area of ​​the area with high demand is determined in advance. The identification unit 132 identifies the number of drones 20 to be deployed at the station according to the area of ​​the area with high demand included in the delivery area 311A. The identification unit 132 may change the number of drones 20 to be deployed in the area with high demand and the area with particularly high demand. The identification unit 132 may set the number of drones 20 to be deployed according to the area of ​​the area with particularly high demand to be greater than the number of drones 20 to be deployed according to the area of ​​the area with high demand.

[0102] When delivery areas 310A including areas of high demand overlap, the identification unit 132 determines that a number of drones 20 according to the area of ​​the area should be placed at stations closer to the areas of high demand.

[0103] Alternatively, the identification unit 132 may determine the number of drones 20 to be deployed according to the distance between the area with high demand and the multiple stations. For example, the range E2:E4 is included in the delivery area 311A ​​and the delivery area 331A. The range E2:E4 is closer to the station 31 than to the station 33. Therefore, the identification unit 132 determines the number of drones 20 to be deployed at each station such that the number of drones 20 to be deployed at the station 31 is greater than the number of drones 20 to be deployed at the station 33.

[0104] Next, the identification unit 132 identifies the number of drones 20 deployed at each station (including drones 20 within the delivery area 310A of each station) among the drones 20 with sufficient remaining battery power.

[0105] The identification unit 132 identifies how many drones 20 should be moved to which station depending on the number of drones 20 placed at each station and the number of drones 20 to be placed at each station. Also, the identification unit 132 determines which drones 20 should be moved to which station depending on the position of the drones 20.

[0106] The placement control unit 133 moves the drone 20 to the station in accordance with the determination by the identification unit 132.

[0107] In this embodiment, the identification unit 132 determines the number of drones 20 to be deployed at the station, but the identification unit 132 may determine the ratio of drones 20 to be deployed. The identification unit 132 determines the ratio of the number of drones 20 to be deployed at the station according to the area of ​​the high-demand area, the delivery area 310A, and the distance between the high-demand area and the station. When a no-fly area 300 exists between the high-demand area and the station, the identification unit 132 may reduce the ratio of the station.

[0108] The identification unit 132 determines the number of drones 20 to be deployed at the station based on the total number of drones 20 with sufficient remaining battery power, in accordance with the determined ratio.

[0109] In this way, by the identification unit 132 determining the ratio of drones 20, the mobile control device 10 can appropriately place the drones 20 at the stations even if the total number of drones 20 with sufficient remaining battery power is small.

[0110] [Deployment of 20 drones with low battery] 6 described above, the battery remaining amount information 123 is information in which a pattern is applied to each cell according to the remaining battery amount of the drone 20. Instead of this, the mobile object control device 10 may generate a plurality of pieces of battery remaining amount information 123 (heat map) according to the remaining battery amount.

[0111] For example, the mobile object control device 10 may generate a heat map (first battery remaining information) according to the number of drones 20 that are sufficiently charged, and a heat map (second battery remaining information) according to the number of drones 20 that need charging. Here, a drone 20 that is sufficiently charged refers to a drone 20 with a remaining battery level of 50% or more, for example. Also, a drone 20 that needs charging refers to a drone 20 with a remaining battery level of 30% or more and less than 50%, for example.

[0112] 8 is a diagram showing an example of the second battery remaining amount information according to the embodiment. Note that the first battery remaining amount information is omitted from the illustration because it is the same as the battery remaining amount information in which the second color (or second pattern) is not applied to the range A1:E5 in FIG. 6 and the first color (or first pattern) is applied to the range F8:J10.

[0113] FIG. 8, like FIG. 6, shows a grid superimposed on a geographic map of the service area.

[0114] For example, in Fig. 8, a second color (or a second pattern) is applied to cells in which the number of drones 20 with remaining battery power of 30% or more and less than 50% is equal to or greater than a threshold value. In addition, the color intensity and pattern density may change depending on the number of drones 20 with remaining battery power of 50% or more or less than 50%.

[0115] For example, in the range B1:E5 of FIG. 8, the number of drones 20 with remaining battery power of 30% or more and less than 50% is equal to or greater than a threshold value (e.g., 10).

[0116] As described above, in this embodiment, when the remaining battery level falls below 30% and delivery is not in progress, the drone 20 charges. Also, approximately 10% to 20% of the battery is consumed in one delivery. Therefore, the drone 20 with a remaining battery level of 30% to 50% will need to be charged after making one or two remaining deliveries.

[0117] Here, the mobile control device 10 may determine the charging station for a drone 20 with a remaining battery charge of 30% or more but less than 50% (hereinafter also referred to as a drone 20 requiring charging) based on the delivery area 310A, an area with high demand, and the location of the drone 20.

[0118] In this case, the mobile control device 10 generates (or acquires) demand information 122 (delivery demand forecast) at the time when charging of the drone 20 requiring charging is completed, and determines the charging destination station for the drone 20 requiring charging based on the demand information 122.

[0119] In addition, the mobile body control device 10 sets a delivery area 310A at the time when charging of the drone 20 that needs to be charged is completed, and determines a charging destination station for the drone 20 that needs to be charged based on the delivery area 310A.

[0120] In addition, when the charging completion times of multiple drones 20 requiring charging are different, the mobile object control device 10 may determine the demand information 122 and the delivery area 310A at the average time when charging is completed. Alternatively, the mobile object control device 10 may determine the demand information 122 and the delivery area 310A at the latest (or earliest) charging completion time.

[0121] Fig. 9 is a diagram showing another example of the demand information 122 according to the embodiment. Fig. 9 shows the demand information 122 at the time when charging of the charge-requiring drone 20 is completed. Note that, here, the delivery area 310A at the time when charging is completed is the same as the delivery area 310A shown in Fig. 4, and therefore the description will be omitted.

[0122] In Figure 9, the range A1:D3 and the range H3:J7 have higher demand than the other cells. Within the range A1:D3, the range B2:C2 has even higher demand. Within the range 3:J7, the range H4:I6 has even higher demand.

[0123] The placement process of the drone 20 requiring charging by the identification unit 132 and the placement control unit 133 is the same as the process described using Figures 5 and 6, except that the drone 20 to be placed is a drone 20 requiring charging, so the explanation here is omitted.

[0124] The flow of the process of arranging the drone 20 that needs to be charged will be described with reference to Fig. 10. Fig. 10 is a flowchart illustrating the process of arranging the drone 20 that needs to be charged according to the embodiment. The process of arranging the drone 20 that needs to be charged is executed by the mobile body control device 10, for example, when charging of the drone 20 that needs to be charged is completed. Alternatively, the process of arranging may be executed at a fixed interval.

[0125] 10, first, the mobile object control device 10 sets a delivery area 310A by the drone 20 after the first period has elapsed (step S201). Here, the first period is the period until the drone 20 that needs charging completes charging.

[0126] The mobile object control device 10 identifies an area where there is a high demand for delivery by drone after the first period has elapsed (step S202). The mobile object control device 10 can identify an area where there is a high demand based on the demand information 122.

[0127] Next, the mobile object control device 10 identifies the drone deployment status for each area taking into account the remaining battery power (step S203). In particular, the mobile object control device 10 can identify areas where there are many drones 20 but the remaining battery power is insufficient, or in other words, areas where there are many drones 20 that need charging, based on the remaining battery power information 123.

[0128] Then, the mobile body control device 10 deploys the drone so that the demand after the first period is met (step S204). For example, the mobile body control device 10 changes the deployment of the drone 20 that needs to be charged from an area with low demand to an area with high demand. In other words, the mobile body control device 10 selects a charging destination station so that the drone 20 that needs to be charged is charged at a station in an area with high demand.

[0129] In this way, the mobile object control device 10 determines at which station charging will be performed depending on the position of the drone 20 that requires charging. This allows the mobile object control device 10 to meet delivery demands without changing the location of the drone 20 after charging is completed.

[0130] [About remaining battery information] The battery remaining amount information 123 is not limited to that described in FIG. 6, and may be, for example, a score obtained by multiplying the number of drones 20 present in each cell by the remaining battery amount. This score represents the capacity to meet the demand of each cell. That is, the identification unit 132 identifies a cell having a low score relative to the demand. The placement control unit 133 places the drone 20 in a station including the identified cell. Also, the score of each cell may be visualized as a heat map, similar to FIG. 6.

[0131] However, a battery remaining amount of 30% or less is replaced with 0%. This is because a drone 20 with an extremely low battery remaining amount (for example, 30% or less) is charging and therefore does not contribute to meeting the demand.

[0132] For example, assume that cell A1 contains one drone 20 with a battery remaining amount of 60% and one drone 20 with a battery remaining amount of 55%. In this case, the score of cell A1 is 0.6×1+0.55×1=1.15.

[0133] Also, for example, assume that cell B1 contains one drone 20 with a battery remaining amount of 25%, two drones 20 with a battery remaining amount of 35%, and one drone 20 with a battery remaining amount of 90%. In this case, 25% is replaced with 0%, and the score of cell B1 is 0×1+0.35×2+0.9×1=1.6.

[0134] 11 is a diagram showing an example of a computer hardware configuration functioning as a mobile control device. A program installed in the computer 1200 can cause the computer 1200 to function as one or more "parts" of the device according to the present embodiment, or cause the computer 1200 to execute operations or one or more "parts" associated with the device according to the present embodiment, and / or cause the computer 1200 to execute a process or steps of the process according to the present embodiment. Such a program can be executed by the CPU 1212 to cause the computer 1200 to execute specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0135] The computer 1200 according to this embodiment includes a CPU 1212, a RAM 1214, and a graphic controller 1216, which are connected to each other by a host controller 1210. The computer 1200 also includes input / output units such as a communication interface 1222, a storage device 1224, a DVD drive, and an IC card drive, which are connected to the host controller 1210 via an input / output controller 1220. The DVD drive may be a DVD-ROM drive, a DVD-RAM drive, etc. The storage device 1224 may be a hard disk drive, a solid state drive, etc. The computer 1200 also includes input / output units such as a ROM 1230 and a keyboard, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0136] The CPU 1212 operates according to a program stored in the ROM 1230 and the RAM 1214, thereby controlling each unit. The graphic controller 1216 acquires image data generated by the CPU 1212 into a frame buffer or the like provided in the RAM 1214 or into itself, and causes the image data to be displayed on the display device 1218.

[0137] The communication interface 1222 communicates with other electronic devices via a network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive reads programs or data from a DVD-ROM or the like and provides them to the storage device 1224. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0138] The ROM 1230 stores therein a boot program or the like that is executed by the computer 1200 upon activation, and / or a program that depends on the hardware of the computer 1200. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via a USB port, a parallel port, a serial port, a keyboard port, a mouse port, and the like.

[0139] The programs are provided by a computer-readable storage medium such as a DVD-ROM or an IC card. The programs are read from the computer-readable storage medium, installed in the storage device 1224, the RAM 1214, or the ROM 1230, which are also examples of computer-readable storage media, and executed by the CPU 1212. Information processing described in these programs is read by the computer 1200, and brings about cooperation between the programs and the various types of hardware resources described above. An apparatus or method may be constructed by implementing operations or processing of information according to the use of the computer 1200.

[0140] For example, when communication is performed between the computer 1200 and an external device, the CPU 1212 may execute a communication program loaded in the RAM 1214 and instruct the communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 1212, the communication interface 1222 reads transmission data stored in a transmission buffer area provided in the RAM 1214, the storage device 1224, a DVD-ROM, or a recording medium such as an IC card, and transmits the read transmission data to the network, or writes reception data received from the network to a reception buffer area or the like provided on the recording medium.

[0141] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external recording medium such as the storage device 1224, a DVD drive (DVD-ROM), an IC card, etc. to be read into the RAM 1214, and perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

[0142] Various types of information, such as various types of programs, data, tables, and databases, may be stored in the recording medium and undergo information processing. The CPU 1212 may perform various types of processing on the data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequence of the program, and write back the results to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. in the recording medium. For example, when a plurality of entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording medium, the CPU 1212 may search for an entry whose attribute value of the first attribute matches a specified condition from among the plurality of entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0143] The above-mentioned programs or software modules may be stored in a computer-readable storage medium on the computer 1200 or in the vicinity of the computer 1200. In addition, a recording medium such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet can be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0144] The blocks in the flowcharts and block diagrams in the present embodiment may represent stages of a process in which an operation is performed or "parts" of an apparatus responsible for performing the operation. Particular stages and "parts" may be implemented by dedicated circuitry, programmable circuitry provided with computer readable instructions stored on a computer readable storage medium, and / or a processor provided with computer readable instructions stored on a computer readable storage medium. The dedicated circuitry may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. The programmable circuitry may include reconfigurable hardware circuits, such as, for example, field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and the like, including AND, OR, XOR, NAND, NOR, and other logical operations, flip-flops, registers, and memory elements.

[0145] A computer-readable storage medium may include any tangible device capable of storing instructions that are executed by a suitable device, such that a computer-readable storage medium having instructions stored thereon comprises an article of manufacture that includes instructions that can be executed to create means for performing the operations specified in the flowcharts or block diagrams. Examples of computer-readable storage media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, and the like. More specific examples of computer-readable storage media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disk read-only memories (CD-ROMs), digital versatile disks (DVDs), Blu-ray disks, memory sticks, integrated circuit cards, and the like.

[0146] The computer readable instructions may include either assembler instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and conventional procedural programming languages ​​such as the “C” programming language or similar programming languages.

[0147] Computer readable instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, or to a programmable circuit, either locally or over a local area network (LAN), a wide area network (WAN), such as the Internet, etc., to cause the processor of the general purpose computer, special purpose computer, or other programmable data processing apparatus, or to a programmable circuit, to execute the computer readable instructions to generate means for performing the operations specified in the flowcharts or block diagrams. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0148] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It is clear to those skilled in the art that various modifications or improvements can be made to the above embodiments. It is clear from the claims that such modifications or improvements can also be included in the technical scope of the present invention.

[0149] It should be noted that the order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before" or "prior to," and that the process may be performed in any order unless the output of a previous process is used in a later process. Even if the operational flow in the claims, specifications, and drawings is described using "first," "next," etc. for convenience, it does not mean that the process must be performed in this order. [Explanation of symbols]

[0150] N Network 10 Mobile control device 11 Communications Department 12 Storage section 13 Control section 20, 20a, 20b, 20c Drone Stations 31, 32, and 33 311A, 321A, 331A Delivery Area 121 Area Information 122 Demand information 123 Battery level information 131 Setting section 132 Specific part 133 Placement control unit

Claims

1. An identification unit that identifies a station where a plurality of drones are to be placed based on the positions and remaining battery power of a plurality of drones that deliver goods within a delivery area of ​​the station where the drones are placed, and A deployment control unit that deploys the drone at the deployment destination station identified by the identification unit; having The delivery area is set according to an area where the drone cannot fly. Mobile control device.

2. The mobile control device according to claim 1 , wherein the delivery area is set according to a no-fly area for the drone.

3. The mobile object control device according to claim 1 , wherein the delivery area is set according to weather conditions.

4. The mobile control device according to claim 1 , wherein the identification unit identifies the destination station each time a drone takes off from any of the plurality of stations.

5. The identification unit is Determine the number or ratio of the drones to be placed at each station according to delivery demand within the delivery area; Identifying a station where the drone will be deployed according to the number or the ratio of the drones to be deployed at each station and the position of the drone whose remaining battery charge is equal to or greater than a predetermined value; The mobile object control device according to claim 1 .

6. The mobile control device according to claim 1, wherein the identification unit identifies the destination station based on the number of drones present in each cell obtained by dividing all areas in which the goods are delivered into a grid, and the remaining battery power of the drones present.

7. The identification unit is Determine the number or ratio of the drones to be deployed at each station according to a delivery demand forecast within the delivery area after a predetermined time; Identifying the station where the drone will be placed according to the number or the ratio of the drones to be placed at each station and the position of the drone where the remaining battery charge when charged for the specified period of time will be equal to or greater than a specified value; The mobile object control device according to claim 1 .

8. A step of identifying stations to which a plurality of drones are to be deployed based on the positions and remaining battery power of the plurality of drones, each of which is deployed at one of a plurality of stations and delivers goods within the delivery area of ​​the station at which the drones are deployed; A deployment control process of deploying the drone at the deployment station identified by the identification process; Including, The delivery area is set according to an area where the drone cannot fly. A method for controlling a moving object.

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