MOBILE OBJECT MANAGEMENT DEVICE, MOBILE OBJECT MANAGEMENT SYSTEM, AND MOBILE OBJECT MANAGEMENT METHOD

Abstract

A mobile object management device is provided that can improve the movement efficiency of each mobile object while suppressing the amount of calculation required for route planning for a plurality of mobile objects. [Solution] The mobile object management device 601 includes a route planning unit 608 that creates a planned route for a plurality of mobile objects 101 using a plurality of first grids 201, a congestion area setting unit 609 that extracts, based on the planned route, first grids 201 from the plurality of first grids 201 where interference between two or more mobile objects 101 is expected as first congestion prediction grids and sets a collection of the first congestion prediction grids as a first congestion area, and a grid division unit 610 that divides the first congestion prediction grid into a plurality of second grids 201T, each having at least one side that is not parallel to any side of the first congestion prediction grid, and the route planning unit 608 creates the planned route using the plurality of first grids 201 after the first congestion prediction grid has been divided into the plurality of second grids 201T.

Description

[Technical Field]

[0001] The present invention relates to a mobile object management device, a mobile object management system, and a mobile object management method for managing a plurality of mobile objects. [Background technology]

[0002] With the labor shortage caused by the declining birthrate and aging population and the expansion of the e-commerce market, labor saving and improving work efficiency have become issues in logistics warehouses and factories. To solve these issues, the introduction of autonomous mobile robots (hereinafter referred to as mobile units), including AGVs (Automated Guided Vehicles) that can operate unmanned, and mobile unit management devices that operate multiple mobile units efficiently is being promoted.

[0003] The main functions of a mobile object management device are a route planning function and an exclusive control function. The route planning function sequentially calculates routes to the destinations of all mobile objects. A route is generally expressed by the grid groups that the object passes through and the order in which it passes through them. The exclusive control function prevents collisions between mobile objects by granting permission to enter each grid to only one mobile object at most.

[0004] Conventional mobile object management systems typically divide a space into a rectangular grid and limit the movement of mobile objects to moving straight ahead and turning on the spot within the grid, taking into account the computational costs required to control all mobile objects and the need to avoid collisions between them. Furthermore, by reducing the width of the rectangular grid (grid pit), it becomes possible to execute route planning and exclusive control more precisely. For example, Patent Document 1 discloses an AGV route search server for searching a route for a specific mobile object in an AGV system that uses multiple mobile objects and multiple grids that serve as markers for the mobile objects within a logistics center. The AGV route search server includes: a computing unit that virtually calculates coordinates based on route search conditions; a communication unit that can send and receive coordinate data calculated by the computing unit between the mobile object and the AGV route search server in real time; and a setting unit that can expand or reduce the grid pitch of the coordinates received from the communication unit based on the route search conditions for the mobile object that self-propels based on the coordinates. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent Publication No. 2021-128768 Summary of the Invention [Problem to be solved by the invention]

[0006] In recent years, methods have been developed to enable diagonal movement of moving objects, rather than limiting the direction to up, down, left, or right. Utilizing diagonal movement could shorten the distance traveled to a destination and the time required for a moving object to turn. When a moving object moves diagonally in a space divided by a rectangular grid, it must exclude (occupy) not only the grid diagonally adjacent to the destination, but also the grids adjacent to the grid diagonally above, below, left, and right. This significantly restricts the movement of other moving objects near the moving object, reducing the movement efficiency of those moving objects. In contrast, the AGV route search server in Patent Document 1 minimizes the area occupied by the excluded grids due to the moving object's diagonal movement by extremely small grid pitch. However, this method presents a new problem: the amount of calculation required for route planning and exclusive control increases dramatically.

[0007] The present invention has been made in consideration of the above-mentioned problems, and its purpose is to provide a mobile object management device that can improve the movement efficiency of each mobile object while reducing the amount of calculation required for route planning for multiple mobile objects. [Means for solving the problem]

[0008] In order to achieve the above object, the present invention provides a mobile object management device that manages a plurality of mobile objects that move within a predetermined movement area, comprising: a route planning unit that creates a planned route for the plurality of mobile objects using a plurality of first grids obtained by dividing the movement area; a congestion area setting unit that extracts, based on the planned route, first grids from the plurality of first grids where interference between two or more of the plurality of mobile objects is expected as first congestion prediction grids and sets a collection of the first congestion prediction grids as a first congestion area; and a grid division unit that divides the first congestion prediction grid into a plurality of second grids having at least one side that is not parallel to any of the sides of the first congestion prediction grid, and the route planning unit creates the planned route using the plurality of first grids after the first congestion prediction grid has been divided into the plurality of second grids.

[0009] The present invention also provides a mobile object management system comprising the mobile object management device and the plurality of mobile objects.

[0010] The present invention also provides a mobile object management method for managing a plurality of mobile objects moving within a predetermined mobile area, comprising: a first step of creating a planned route for the plurality of mobile objects using a plurality of first grids obtained by dividing the mobile area; a second step of extracting, based on the planned route, first grids from the plurality of first grids where interference between two or more of the plurality of mobile objects is expected as first congestion prediction grids, and setting a collection of the first congestion prediction grids as a first congested area; a third step of dividing the first congestion prediction grids into a plurality of second grids having at least one side that is not parallel to any side of the plurality of first grids; and a fourth step of creating the planned route using the plurality of first grids after the first congestion prediction grid has been divided into the plurality of second grids. [Effects of the Invention]

[0011] According to the present invention, it is possible to improve the movement efficiency of each moving object while suppressing an increase in the amount of calculation required for route planning for a plurality of moving objects. [Brief explanation of the drawings]

[0012] [Figure 1] An example of the operating environment for a transport system in a warehouse or factory [Figure 2] A diagram showing the movement area of ​​a moving object [Figure 3] Exclusive control concept [Figure 4] Schematic diagram showing a specific example of exclusive control when moving in a 45-degree diagonal direction [Figure 5] A conceptual diagram of a moving body and a functional block diagram for explaining the control operation of the moving body. [Figure 6] Functional block diagram of the mobile object group control system [Figure 7] Conceptual diagram of the space-time A* method [Figure 8]1 is a flowchart showing a series of processes executed by the control server. [Figure 9] FIG. 1 is a schematic diagram illustrating a grid division method according to a first embodiment; [Figure 10] FIG. 10 is a schematic diagram illustrating a grid division method according to a second embodiment; [Figure 11] FIG. 10 is a schematic diagram illustrating a grid division method according to a third embodiment; [Figure 12] FIG. 10 is a schematic diagram illustrating a grid division method according to a fourth embodiment; DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, an embodiment of the present invention will be described in detail with reference to Figures 1 to 12. Note that in this embodiment, an explanation will be given for an example of inter-process transport within a warehouse or factory. [Example]

[0014] FIG. 1 is a diagram showing an example of an operational environment 100 of a transportation system in a warehouse or factory. Multiple mobile objects 101 are used for transportation work. Each mobile object 101 is controlled via wireless communication by a mobile object management device 601. The mobile object management device 601 includes a control server 601a, an input device 601b such as a keyboard or mouse, and a display 601c. The input device 601b is a device that inputs information on orders (tasks) required for the entire transportation system to the control server 601a. ​​The display 601c is a device that displays the operation status of each mobile object 101 (such as the planned route and task execution status), which is the result of calculations by the control server 601a.

[0015] In the operational environment 100, a worker 105 at a station 104 transfers an item 103 transported from another area by a conveyor 102 onto a mobile object 101. The mobile object 101 loaded with the item 103 moves to another station 106. It is assumed that another worker at station 106 combines the transported item 103 and places it on another conveyor 109. The mobile object 101 repeatedly travels between the station 104 adjacent to the conveyor 102 and the combining station 106, and if charging is required or if there are no tasks that can be performed, it heads to an adjacent dock 107.

[0016] FIG. 2 is a diagram showing a movement area 200 of the moving object 101. The movement area 200 is divided into a grid of squares of the minimum size that allow the moving object 101 to turn safely. The area occupied by these squares is called a grid 201. Each grid 201 has a node 202 at its center. Whether movement between grids 201 is possible is expressed by the presence or absence of links 203 connecting the nodes 202. In this embodiment, it is assumed that movement between all adjacent nodes 202 is possible. Therefore, as shown in FIG. 2, a graph structure 204 consisting of nodes 202 and links 203 includes nodes 202 arranged in a grid pattern, links 203 in the up, down, left, and right directions, and links 203 in the 45-degree diagonal direction. Note that, although the above-mentioned assumptions are used in this embodiment, the graph structure 204 is not limited to this and any structure can be assumed.

[0017] When each mobile object 101 repeatedly travels between destinations such as stations 104 and 106 and a dock 107, the control server 601a executes route planning for each mobile object 101 to determine the specific route to follow. The route planning is executed using a graph structure 204 and various route search algorithms. The planned route for each mobile object 101 may be defined by two or more nodes 202 to be passed through and the order in which they are passed, or by two or more links 203 to be passed through and the order in which they are passed.

[0018] Furthermore, in order to avoid collisions and interference between the moving bodies 101, the control server 601a occupies (excludes) for each moving body 101 a grid 201 in a specific section on the route to each destination, and performs control (exclusion control) that does not allow other moving bodies 101 to enter the grid 201 occupied by one moving body 101. The grid 201 occupied by each moving body 101 is called an exclusive area. The exclusion control is a safety function that operates independently of route planning.

[0019] FIG. 3 is a conceptual diagram of exclusive control. In this example, there are two moving bodies 101A and 101B, and their routes to destinations 301 and 302 partially overlap. The moving body 101A has exclusive control of four grids on its route to destination 301. Therefore, the moving body 101B can only exclusive control of three grids on its route to destination 302. In the example shown in FIG. 3, the maximum number of grids that one moving body 101 can exclusive (maximum number of exclusive grids) is set to four. Increasing the maximum number of exclusive grids reduces the possibility of collisions and interference between the moving bodies 101, but increases the amount of calculations performed by the control server 601a and reduces the overall efficiency of the transportation system. On the other hand, decreasing the maximum number of exclusive grids reduces the amount of calculations performed by the control server 601a and improves the overall efficiency of the transportation system, but increases the possibility of collisions and interference between the moving bodies 101. Therefore, the maximum number of exclusive grids must be set appropriately depending on the performance of the control server 601a and the in-vehicle controller 501, and the number of moving bodies 101.

[0020] FIG. 4 is a schematic diagram showing a specific example of exclusive control for movement in a 45-degree diagonal direction. When a moving object 101 moves toward a destination 401 only by moving up, down, left, and right without utilizing movement in a 45-degree diagonal direction, only the grids 201 on the route need to be set as the exclusive region 402, as shown in FIG. 4(A). On the other hand, when moving toward the destination 401 by utilizing movement in a 45-degree diagonal direction, in order to prevent interference with other moving objects 101, it is necessary to set as the exclusive region 402 not only each grid 201 on the route but also the surrounding grids 201, as shown in FIG. 4(B). For example, when moving to a grid 201 diagonally to the upper right, it is necessary to set as the exclusive region 402 four grids 201, namely the grid 201 where the moving object 101 is currently located and the three grids 201 to the right, above, and to the upper right. Compared to typical vertical and horizontal movements, movement at a 45-degree angle requires a shorter travel distance, and since each change of direction requires only a 45-degree turn, depending on the drive configuration and control method of the mobile body 101, it is possible to change the direction of movement without having to slow down and stop each time. On the other hand, since the area already occupied by other mobile bodies 101 becomes larger (wider), this may force them to make excessive detours or wait, which may lead to a decrease in the overall efficiency of the transportation system. On the other hand, if all grids 201 are divided finely vertically and horizontally to prevent such a situation, the increased number of divisions will increase the amount of calculations required by the control server 601a.

[0021] To solve this problem, in this embodiment, each grid 201 is divided diagonally and then exclusive control is performed. Specifically, as shown in FIG. 4(C), the square grid 201 is divided into four right-angled isosceles triangular grids 201T with two diagonals as boundaries, and exclusive control is performed using the divided grids 201T. This allows the exclusive region 402 to be set smaller than in the case of FIG. 4(B), and prevents a decrease in the overall efficiency of the transportation system. Furthermore, since the number of divisions of the grid 201 is reduced, the calculation load of the control server 601a can also be reduced.

[0022] The division shown in FIG. 4C is effective in areas where many moving objects 101 exist (congested areas). On the other hand, in areas where many moving objects 101 do not exist (non-congested areas), the effect is limited despite the increased computational complexity. Therefore, in this embodiment, the grid 201 is divided and then subjected to exclusive control in congested areas, while the grid 201 is not divided and subjected to exclusive control in non-congested areas. Specifically, an exclusive area 402 like that shown in FIG. 4C is set in congested areas, and an exclusive area 402 like that shown in FIG. 4B is set in non-congested areas. This reduces the computational complexity required for route planning while enabling efficient movement by utilizing 45-degree diagonal movement even in congested areas. Although not shown in FIG. 4 for convenience of explanation, the exclusive control and exclusive area can also incorporate a time perspective. The division of the grid 201 can also incorporate a time perspective. Details of the grid division method from a temporal perspective will be described later using FIG. 7. Details of the grid division method from a spatial perspective will also be described later using FIG. 9.

[0023] The following describes in detail the specific configuration of the mobile object management system 600 that realizes the overall movement of the mobile object 101, including the above-mentioned viewpoints, and the processing of the mobile object management device 601.

[0024] FIG. 5(A) is a conceptual diagram of a mobile body 101. The mobile body 101 is configured as an autonomous mobile robot such as an AGV (Automated Guided Vehicle) that can operate unmanned. In this embodiment, the mobile body 101 is a differential two-wheel type, but the drive form of the mobile body 101 is not limited to this and may be an omni-wheel type, a Mecanum wheel type, or the like. In FIG. 5(A), x is the x-coordinate value of the mobile body 101, y is the y-coordinate value of the mobile body 101, and θ is the azimuth angle (direction) of the mobile body 101. Self-position calculation, which will be described later, means obtaining the current x, y, and θ values.

[0025] 5(B) is a functional block diagram for explaining the control operation of the moving object 101. The moving object 101 is equipped with an on-board controller 501 that performs control calculations. The on-board controller 501 includes a target route management unit 502, an on-board sensor 503, a driving map management unit 504, a control command generation unit 505, a self-position calculation unit 506, and a communication unit 509 that communicates with the control server 601a. ​​The moving object 101 also includes a drive unit 507 that includes drive wheels, and an encoder 508 that acquires the amount of rotation of the drive wheels. An overview of each function will be described below.

[0026] The target route management unit 502 receives the target route planned by the control server 601a via the communication unit 509. The target route is a set of nodes 202 and links 203, and receives sequentially updated information from the control server 601a.

[0027] The on-board sensor 503 corresponds to an external sensor mounted on the mobile object 101. In this embodiment, as an example, a LiDAR (Light Detection and Ranging) sensor is mounted. LiDAR is a sensor that measures the distance to an object within the irradiation range by changing the irradiation angle of a laser beam. Regarding group control technology for mobile objects 101, such as AGVs, a method of installing AR (Augmented Reality) tags or RFID (Radio Frequency Identification) tags on the road surface and reading these tags with a dedicated sensor to obtain the traveling position and direction of the mobile object 101 has been common. On the other hand, in recent years, position estimation technology utilizing active sensors such as the LiDAR and cameras has become inexpensive and highly accurate. Therefore, even in the graph structure 204 having the links 203 at a 45-degree angle described above, the mobile object 101 can be accurately controlled.

[0028] The driving map management unit 504 manages a driving map (an image map different from that shown in FIG. 2) that shows obstacle information in the operational environment 100. This map is created in advance before the start of operation using SLAM (Simultaneous Localization and Mapping) with input of measurement data (a set of points by LiDAR) during driving acquired from the on-board sensor 503 (LiDAR) and travel distance information of the mobile object 101 acquired from the encoder 508 (described later). Creating a grid map using SLAM is a known technique, so a description thereof will be omitted.

[0029] The self-position calculation unit 506 is a function that combines the measurement results obtained from the on-board sensor 503 and the encoder 508 to calculate the self-position (coordinate values ​​x, y) and azimuth angle θ of the mobile object 101. Specifically, map matching technology is used. Map matching is a technology that takes the measurement data acquired by the on-board sensor 503 and a driving map as input, and estimates the position of the mobile object 101 on the driving map by utilizing the similarity between the point cloud set and the driving map. For example, there is an Adaptive Monte Carlo Localization method that uses a particle filter. Since the self-position estimation technology using map matching is also a publicly known technology, a detailed description will be omitted.

[0030] The control command generation unit 505 performs calculations related to the travel control of the mobile object 101. Here, the target route and the self-position are input, and calculations are performed to determine control commands for following the target route, more specifically, speed v and angular velocity ω. For example, a process can be considered in which the node nearest to the self-position that constitutes the target route is set as a target node, and the speed v and angular velocity ω that will reach the target node are sequentially calculated. Specifically, a method such as a forward gaze model (pure pursuit method) can be considered, and since this method is also a publicly known technique, a detailed description will be omitted.

[0031] The drive unit 507 drives the drive wheels in accordance with the command value input from the control command generation unit 505. The encoder 508 estimates the travel distance and current speed of the mobile object 101 from the amount of rotation of the drive wheels, and transmits the estimated values ​​to the self-position calculation unit 506.

[0032] The above is an overview of the functions of the mobile object 101 and the on-board controller 501. Next, an overview of the mobile object management system 600 and an overview of the functions of the control server 601a, which is the main focus of this embodiment, will be described.

[0033] 6 is a functional block diagram of a mobile object management system 600. The mobile object management system 600 in this embodiment includes a mobile object management device 601, an on-board controller 501, and a mobile object 101. The mobile object management device 601 executes a route plan for each mobile object 101 while managing the progress of orders (tasks) requested for the entire transport system and the status of each mobile object 101 (the progress status of tasks assigned to each mobile object 101 and the traveling position). The mobile object management device 601 includes a graph / grid management unit 602, a mobile object information management unit 603, an exclusive state management unit 604, an exclusive control unit 605, a mobile object state management unit 606, a destination determination unit 607, a route planning unit 608, a congested area setting unit 609, a grid division unit 610, a route determination unit 611, a communication unit 612, an instruction unit 613 configured by the input device 601b shown in FIG. 1, and a display unit 614 configured by the display 601c shown in FIG. 1. In FIG. 6, lines with arrows indicate the flow of data. Below, an overview of each functional block included in the mobile object management device 601 will be described based on the configuration example shown in FIG. 6.

[0034] The graph / grid management unit 602 manages the graph structure 204 composed of node / link shapes and the division state of the grid 201. In this embodiment, as shown in FIG. 2, a graph structure 204 is created and managed by adding 45-degree diagonal links 203 to the links 203 in the up, down, left, and right directions for the nodes 202. In this embodiment, the grid 201 closest to the worker 105 (or station 104) corresponding to the task is set as the destination among the top and bottom grids 201 in the layout of FIG. 2. The mobile object 101 repeatedly travels back and forth between the top and bottom destinations. Therefore, the nodes corresponding to the top and bottom grids are set as destination nodes, and the route to the destination node (the order of links to be traversed) is determined in the route planning process described below. Although not shown in FIG. 2 for convenience of explanation, the graph structure 204 and grid 201 can also be considered in terms of the time axis. This will be described later using FIG. 7.

[0035] The mobile object information management unit 603 stores information about the mobile object 101. The information about the mobile object 101 managed includes dimensions related to vehicle size such as the width, length, height, and wheelbase of the mobile object, maximum (minimum) speed, maximum (minimum) angular velocity, maximum (minimum) acceleration, maximum battery capacity, and maximum weight of the load to be transported.

[0036] To avoid collisions and interference between the moving bodies 101, the exclusive control unit 605 sets an exclusive area on the route to the destination of each moving body 101 and prohibits other moving bodies 101 from entering. The number of grids 201 constituting the exclusive area of ​​each moving body 101 does not always match the maximum number of exclusive grids, but changes accordingly depending on the routes of the other moving bodies 101, as explained using FIG. 3. However, to avoid interference between the moving bodies 101, the grid 201 corresponding to the current position of each moving body 101 is always set in the exclusive area. Furthermore, as mentioned above, when moving in a 45-degree diagonal direction, the exclusive area setting method is selectively used as shown in FIG. 4(B) and FIG. 4(C).

[0037] The exclusive state management unit 604 manages which grids are currently exclusive (occupied) by each mobile object 101. Since the exclusive area of ​​the mobile object 101 changes from moment to moment, the information managed internally is updated in conjunction with input / output information of the route planning unit 608 and the exclusive control unit 605, which will be described later.

[0038] The mobile object status management unit 606 manages the current status of each mobile object 101. Specifically, it manages the progress of tasks assigned to each mobile object 101 and the position information of each mobile object 101 transmitted from the in-vehicle controller 501 via the communication unit 612. Furthermore, based on the information from the mobile object information management unit 603, it calculates the current remaining battery level and weight of the load of each mobile object 101. Then, it detects a mobile object 101 in a state where the remaining battery level is below a specific threshold or the weight of the load exceeds a specific threshold (abnormal status), and transmits information identifying the mobile object 101 to the route planning unit 608.

[0039] The destination determination unit 607 determines the next destination of each mobile object 101 based on information on the order (task) to be achieved by the entire transport system, input from the instruction unit 613. Although there is a method of changing the order of destinations to maximize productivity within a given time period according to the contents of the order, this is not a core part of this embodiment. Therefore, in this embodiment, the list in the order is given to the mobile objects 101 waiting for a task in order from top to bottom. However, for a mobile object 101 for which the mobile object status management unit 606 has detected overloading or low battery level (abnormal status), the dock area 205 (shown in FIG. 2) consisting of the grid 201 linked to the dock 107 (shown in FIG. 1) is set as the destination.

[0040] Since the series of processes of the route planning unit 608, the congested area setting unit 609, the grid division unit 610, and the route determination unit 611 are the main focus of this embodiment, only an outline of the processes will be described here, and the actual process flow will be described later with reference to the flowchart shown in FIG. 8.

[0041] The route planning unit 608 receives as input the graph structure 204 managed by the graph / grid management unit 602, the current position and status of each mobile object 101 output from the mobile object state management unit 606, and the destination (grid) output from the destination determination unit 607, and plans a global route from the mobile object's current position to the destination. The global route is generated based on the graph structure 204. There are many known methods for planning global routes, such as the Dijkstra algorithm and the A* (A star) algorithm, and detailed explanations will be omitted. In this embodiment, an algorithm based on the A* algorithm is used. The generated global route is represented by a set of links 203 to be passed through, and arrival at the destination is guaranteed by traveling these links 203 in order. The route 206 shown in Figure 2 is an example of a generated global route. In this embodiment, movement in a 45-degree diagonal direction is also permitted, so a route with direction changes in up to eight directions is generated.

[0042] FIG. 7 is a schematic diagram for explaining path planning and exclusive control using the space-time A* method. In this embodiment, the congested area setting unit 609 uses the output of the path planning unit 608, so the space-time A* method is used as a specific algorithm for path planning. The space-time A* is an A* with a time axis added, and can calculate the shortest path taking into account the presence of dynamic obstacles. As shown in FIG. 7, when a lattice space on a two-dimensional plane is used as the path search area, the search space is a three-dimensional map with the depth direction as the time axis. Since the positions of dynamic obstacles are managed in grid units, dynamic obstacles are handled using a hash map (a data structure consisting of pairs of position and time) in implementation. When calculating the shortest path from point A to point B, static obstacles such as walls are taken into account in the same way as with a normal A* method, and the shortest path is determined while also performing collision detection with registered dynamic obstacles. Note that in this embodiment, the moving area 200 is assumed to be a two-dimensional plane defined by the X and Y axes, but the moving area 200 is not limited to a two-dimensional plane and may be a three-dimensional space defined by the X, Y, and Z axes.

[0043] In this embodiment, a mechanism is used in which the planned routes of other moving bodies 101 are regarded as dynamic obstacles using space-time A*, thereby enabling sequential planning of the shortest routes while resolving route competition between the moving bodies 101. This makes it possible to predict which time and location each moving body 101 will pass, enabling processing by the congested area setting unit 609, which will be described later.

[0044] Furthermore, the aforementioned exclusive control can also be performed using the spatiotemporal grid 201 shown in FIG. 7. While spatial exclusive control has been described with reference to FIGS. 3 and 4, the use of the spatiotemporal grid 201 shown in FIG. 7 makes it possible to extend the concept of spatial exclusive control to the time axis direction as well. That is, by granting entry permission to each spatiotemporal grid 201 to only one moving body 101 at most, collisions between moving bodies 101 are prevented. This allows multiple moving bodies 101 to pass through the grid 201 at the same location as long as their passage times do not overlap. By using spatiotemporal exclusive control, it is possible to reduce wasted exclusive areas and enable a large number of moving bodies 101 to operate at high density.

[0045] As mentioned above with reference to FIG. 4, it is effective to spatially divide the grid 201 in a congested area. Similarly, the grid 201 can also be divided in the time axis direction in a congested area. If the time grid is coarse, the time required for the detailed movements of the mobile object 101 (going straight, turning, curving, and accelerating / decelerating) will be treated roughly, resulting in a rough spatiotemporal route plan. This is not a major problem in a scene with few mobile objects 101, but in a scene where the mobile objects 101 are congested, treating the time required for the detailed movements precisely will reduce waste in the spatiotemporal exclusive zones and allow the mobile objects 101 to operate at a higher density. As mentioned above, a large number of divisions increases the amount of calculations performed by the control server 601a. ​​Therefore, by finely dividing the time grid only in the congested area, it is possible to achieve both improved movement efficiency and reduced calculations.

[0046] The congested area setting unit 609 identifies areas with a high density of moving objects 101 and sets them as congested areas. As described above, grid division and route planning are performed with a high degree of division in congested areas and a low degree of division in non-congested areas, thereby improving movement efficiency and reducing the amount of calculation. In identifying congested areas, the planned routes of each moving object 101 planned by the route planning unit 608 are aggregated once, and grids 201 where congestion is expected are identified. Specific processing details will be described later.

[0047] 8 is a flowchart showing a series of processes executed by the control server 601a. ​​When the control server 601a starts processing, the mobile object status management unit 606 acquires the self-position of each mobile object 101 (process 801). Here, the current position and azimuth angle of each mobile object 101, which are the calculation results of the self-position calculation unit 506 provided in each mobile object 101, are acquired via the communication units 509 and 612.

[0048] Following process 801, the mobile object status management unit 606 acquires the status of each mobile object 101 (process 802). In this embodiment, the current remaining battery charge and the weight of the load are acquired as the status of the mobile object 101. Thereafter, based on the acquired information, a mobile object 101 that is overloaded or has a low remaining battery charge (abnormal status) is detected.

[0049] Following process 802, the destination determination unit 607 determines the destination of each moving object 101 (process 803). The destination is a grid 201 associated with the stations 104 and 106 shown in FIG. 2, and as described above, is a grid 201 in the vicinity of the stations 104 and 106 according to the task, among the grids 201 at the top and bottom. However, if a moving object 101 that is overloaded or has a low remaining battery (abnormal status) is detected in process 802, the destination of the moving object 101 is changed to the dock area 205.

[0050] Following process 803, the destination determination unit 607 determines the search priority (process 804). In this process, it is determined which moving body 101 to start planning a route from in the route planning process described below. In the route planning process, target moving bodies 101 are picked one by one, a route search is performed taking into account the movement status of the other moving bodies 101, and after performing exclusive control, the local target position of each moving body 101 is determined. Therefore, basically, the earlier a moving body 101 is placed in the route planning order, the more likely it is that a route that can reach the destination will be obtained with priority. There are various policies for determining the order in which moving bodies 101 are to be route planned, but as an example, a policy is adopted here in which route planning is performed starting with the moving body 101 with the shortest distance between its current position and the destination. However, if there is a moving body 101 that is overloaded or has a low remaining battery (abnormal status), the search priority of that moving body 101 is set to the last.

[0051] Following process 804, the destination determination unit 607 sets route planning parameters (process 805). Specifically, the route planning parameters may include the maximum number of exclusive grids in the exclusive control and a weighting factor for the search cost (heuristic cost) within the space-time A* algorithm, which is the base algorithm of the route planning method. In this embodiment, a preset value is used as the maximum number of exclusive grids. The smaller the maximum number of exclusive grids, the more limited the range of movement becomes depending on the exclusive status of other moving bodies 101, and the longer (slower) it may take to reach the destination. Therefore, in this embodiment, a different maximum number of exclusive grids is set depending on the status of each moving body 101 to give priority to moving bodies 101 with a normal status to reach the destination. Here, as an example, the maximum number of exclusive grids is set to 3 for moving bodies 101 with a normal status, and the maximum number of exclusive grids is set to 2 for moving bodies 101 with an abnormal status.

[0052] The above is the pre-processing that is performed before the actual route planning process. The details of the route planning process will be described below.

[0053] First, the route planning unit 608 determines the moving object 101 for which route planning is to be performed (process 806). Here, the subsequent processes are executed in accordance with the search order for the moving objects 101 determined in process 804.

[0054] Following process 806, the route planning unit 608 acquires the previous planned route and exclusive area of ​​the other moving body 101 (the moving body 101 that was not targeted for route planning in process 806) in preparation for route planning for the target moving body 101 (process 807). Here, as described in the explanation of the route planning unit 608, a three-dimensional vector is input, which is two-dimensional information specifying the grid 201 through which the other moving body 101 will pass, plus the predicted time at which the moving body 101 will arrive at the grid 201. Note that if this is the first step after control has started, there is no planned route for the other moving body 101, and so only a three-dimensional vector combining the initial position of the other moving body 101 and the current time is input.

[0055] Following process 807, the route planning unit 608 executes route planning processing (process 808). Here, route planning is executed using the planned routes and exclusive regions of other moving bodies 101 acquired in process 807, as well as the current graph structure 204 as input. Route planning is performed in accordance with the space-time A* method described above.

[0056] Following process 808, the exclusive control unit 605 updates the exclusive region (process 809). Here, in accordance with the process described in the explanation of the exclusive control unit 605, grids 201 that can be exclusive (occupied) by the target moving object 101 are found. After that, the grids that can be newly exclusive are added to the exclusive region (grids) of the target moving object 101 that is managed by the exclusive state management unit 604, and if there is a grid 201 that was exclusive in the previous step but has already completed traveling, that grid 201 is excluded from the exclusive region.

[0057] Following step 809, the route planning unit 608 determines whether route planning and exclusive area updating (steps 806 to 809) for all moving bodies 101 have been completed (step 810). If completed, the process proceeds to step 811. If not completed, the process returns to step 806, and route planning for the remaining moving bodies 101 is carried out.

[0058] In process 811, the congested area setting unit 609 predicts congestion based on the results of the route planning. Here, the planned routes of each mobile object 101 obtained in the processes up to this point are aggregated, and as a result, a grid 201 where congestion is predicted is identified. Hereinafter, this grid will be referred to as a congestion predicted grid. The following method can be considered as a specific example of the method of identification.

[0059] Consider the space-time search space and each space-time grid shown in Figure 7. A variable Nr representing the number of moving objects 101 passing nearby is set for each space-time grid, with the initial value Nr = 0. The planned movement grids of all moving objects 101 are searched one by one, and the variable Nr for the grids 201 surrounding each grid 201 (spatial axis direction: range of ±1 square vertically and horizontally, time axis direction: range of ±3 squares deep) is incremented by 1. After completing the above process for all planned movement grids of all moving objects 101, the Nr value held by each space-time grid is referenced, and space-time grids with a value exceeding a certain threshold (e.g., 3) are defined as congested. By identifying the corresponding grid and the corresponding time from the space-time grid, the congestion forecast grid and its time period (expected congestion time period) can be obtained.

[0060] Following process 811, the congested area setting unit 609 sets a congested area based on the results obtained in process 811 (process 812). Process 811 obtains multiple congestion forecast grids for each time period, and multiple consecutive congestion forecast grids are defined as a congested area. In this case, the congested area may hold a congestion level indicating the degree of congestion. Various methods for evaluating the congestion level are possible, but one example is to set the average value of the variable Nr held by the grids within the congested area as the congestion level of the area. Note that the shape of the congested area changes depending on the time period. The time interval for treating the congested area may be the same as the time interval of the space-time grid shown in Figure 7, or it may be larger. If the time interval is larger, it is possible to process a grid 201 that is set as a congestion forecast grid even for a moment during that time period under consideration under the assumption that it will be congested throughout that time period.

[0061] Following process 812, the congested area setting unit 609 divides the expected congestion grid (process 813). As described above with reference to FIG. 7, the temporal grid 201 can be divided by increasing the interval size in the time axis direction of the spatiotemporal grid 201. As described with reference to FIGS. 3 and 4, the spatial grid 201 can be divided by dividing the square grid 201 into four right-angled isosceles triangles by two diagonals. FIG. 9(A) shows the grid division result of a congested area 901 in a certain expected congestion time period. Outside the congested area 901, the square grid 201 is used as is, whereas inside the congested area 901, right-angled isosceles triangular grid 201T obtained by dividing the square grid 201 into four by two diagonals is used. In other words, the two grids 201 that share only one vertex and are in contact with each other are divided along the edge of the convex hull (the diagonal of the square) that contains the two grids 201, and the two grids 201 that share one edge and are in contact with each other are divided along the edge of the convex hull that contains the two grids 201 and are in contact with each other and share only one vertex.

[0062] After step 813, the process returns to step 806 and repeats the series of steps. This allows route planning to be performed again using the divided grid. The number of repetitions may be one or more. If no congested area exists, the route planning process may be terminated without repetition.

[0063] FIG. 9(B) is a schematic diagram showing an example of the results of exclusive control and route planning performed using the divided grid 201. By using a triangular grid 201T in the congested area 901, the exclusive area of ​​each moving object 101 is minimized, resulting in a scene in which two moving objects 101 run parallel to each other diagonally or pass each other. This makes it possible to improve movement efficiency by utilizing movement in a 45-degree diagonal direction even in the congested area 901. Note that, for the sake of convenience in FIG. 9(B), the planned route is represented by short arrows, but the length of the planned route is actually arbitrary.

[0064] In this embodiment, the division does not change or add any nodes 202 or links 203, but nodes 202 or links 203 may be added as necessary. An example of adding nodes 202 or links 203 will be described later in embodiment 3.

[0065] The above is the flow of the route planning process for multiple moving bodies 101. In this embodiment, the above processes are repeated until all moving bodies 101 reach their destinations (process 814). More precisely, even after any moving body 101 reaches its destination, the system continues to operate until the list of orders is completed, and therefore the above processes are repeated until all tasks (traveling to the destination) sequentially assigned to each moving body 101 are completed.

[0066] As described above, according to the mobile object management device of this embodiment, by using a triangular grid in which a square grid is divided into four diagonally only in congested areas, movement in a 45-degree diagonal direction can be utilized even in congested areas to improve movement efficiency, while the amount of calculation can be reduced by using a minimum number of grid divisions.

[0067] (summary) In Example 1, a mobile object management device 601 that manages a plurality of mobile objects 101 moving within a predetermined mobile area 200 includes a route planning unit 608 that creates a planned route for the plurality of mobile objects 101 using a plurality of first grids 201 obtained by dividing the mobile area 200, a congested area setting unit 609 that extracts, based on the planned route, first grids 201 from the plurality of first grids 201 where interference between two or more mobile objects 101 is expected as first congestion forecast grids and sets a collection of the first congestion forecast grids as a first congestion area, and a grid division unit 610 that divides the first congestion forecast grid into a plurality of second grids 201T having at least one side that is not parallel to any side of the first congestion forecast grid, and the route planning unit 608 creates the planned route using the plurality of first grids 201 obtained after the first congestion forecast grid has been divided into the plurality of second grids 201T.

[0068] The mobile object management system 600 in the first embodiment includes a mobile object management device 601 and a plurality of mobile objects 101.

[0069] In addition, in Example 1, a mobile object management method for managing a plurality of mobile objects 101 moving within a predetermined mobile area 200 includes a first step of creating a planned route for the plurality of mobile objects 101 using a plurality of first grids 201 obtained by dividing the mobile area 200; a second step of extracting, based on the planned route, first grids 201 from the plurality of first grids 201 where interference between two or more of the plurality of mobile objects 101 is expected as first congestion forecast grids, and setting a collection of the first congestion forecast grids as a first congestion area; a third step of dividing the first congestion forecast grid into a plurality of second grids 201T having at least one side that is not parallel to any side of the first congestion forecast grid; and a fourth step of creating the planned route using the plurality of first grids 201 after the first congestion forecast grid has been divided into the plurality of second grids 201T.

[0070] According to the first embodiment configured as described above, in the first congested area, which is a collection of first grids 201 (first congestion expected grids) where interference between two or more moving bodies 101 is expected, the exclusive area becomes smaller when each moving body 101 moves in a direction (diagonal direction) that is not parallel to any side of the first grid 201, thereby improving the movement efficiency of each moving body 101. Furthermore, since the number of divisions of the first congestion expected grid is minimized, it is possible to suppress an increase in the amount of calculation required for route planning for each moving body 101.

[0071] Furthermore, in the first embodiment, the congested area setting unit 609 sets a time period in which the two or more moving bodies 101 are expected to interfere with each other in the first congested area as a predicted congestion time period, and the grid dividing unit 610 divides the first congestion forecast grid into a plurality of second grids 201T during the predicted congestion time period, and does not divide the first congestion forecast grid into a plurality of second grids 201T during time periods other than the predicted congestion time period. This limits the time period in which the first congestion forecast grid is divided into a plurality of second grids 201T to the predicted congestion time period, thereby making it possible to further reduce the amount of calculation required for route planning for a plurality of moving bodies 101.

[0072] In the first embodiment, a plurality of nodes 202 are arranged in the movement area 200, and the planned route is defined by two or more nodes 202 that each of the plurality of moving bodies 101 is scheduled to pass through, and the order in which the two or more nodes 202 are to be passed through. This makes it possible to easily define the planned route for the plurality of moving bodies 101.

[0073] In the first embodiment, one node 202 is arranged in each of the plurality of first grids 201. This allows the mobile object 101 to turn within all of the first grids 201.

[0074] In the first embodiment, each of the first grids 201 is square, the first grids 201 are arranged in a lattice pattern, one node 202 is arranged at the center of each of the first grids 201, the path planning unit 608 enables the movement of the multiple moving bodies 101 along a line connecting two nodes 202 arranged on two adjacent first grids 201 that share only one vertex, the sides of the convex hull are diagonals of the square, and each of the multiple second grids 201T is shaped like an isosceles right triangle. This makes it possible to improve the movement efficiency of each moving body 101 while suppressing the amount of calculation required for path planning for the multiple moving bodies 101 in the movement region 200 that allows movement in a 45-degree diagonal direction. [Example]

[0075] The mobile object management device 601 according to the second embodiment of the present invention will be described, focusing on the differences from the first embodiment.

[0076] In the first embodiment, an example was shown in which a square grid 201 is divided into four right-angled isosceles triangle grids 201T in a movement area 200 that allows movement in a 45-degree diagonal direction. On the other hand, to realize more flexible movement, it is desirable to be able to utilize movement at angles other than a 45-degree diagonal angle. This embodiment realizes movement at angles other than a 45-degree diagonal angle.

[0077] FIG. 10 is a schematic diagram illustrating a grid division method in the second embodiment. In this embodiment, as in the first embodiment, the grid 201 is assumed to be square. Consider a case where a link 203 is set between non-adjacent nodes 202, such as a link 203XY connecting a node 202X to a node 202Y that is located one node to the right and two nodes above the node 202X, as shown in FIG. 10(A). In such a case, it is desirable to set a minimum exclusive region 1001 as shown in FIG. 10(B). To achieve this, the grid 201 located between the grid 201 corresponding to the node 202X and the grid 201 corresponding to the node 202Y may be divided along the edges of a convex hull that includes these two grids 201X and 201Y as boundaries. When the division is applied taking into account all the surrounding edges, each grid 201 is divided into 32 polygonal grids 201Z, as shown in FIG. 10(C).

[0078] As described above, according to the mobile object management device 601 of this embodiment, even when the nodes 202 are connected at an angle other than 45 degrees, the grid 201 can be divided according to the angle, thereby enabling exclusive control with a minimum exclusive area 1001. It is also possible to use the grid division method described in this embodiment and the grid division method described in embodiment 1 together.

[0079] (summary) In the second embodiment, the shape of each of the multiple first grids 201 obtained by dividing the movement area 200 is a square of a size that allows each of the multiple moving bodies 101 to rotate inside, and the grid division unit 610 divides the first grids (first congestion expected grids) where interference between two or more moving bodies is expected into multiple second grids 201Z, using the edges of a convex hull that includes two first grids 201X and 201Y that do not share any sides as boundaries.

[0080] According to the second embodiment configured as described above, in the movement area 200 where the moving bodies 101 can travel at angles other than 45 degrees, it is possible to improve the movement efficiency of each moving body 101 while suppressing the amount of calculation required for route planning for the moving bodies 101. [Example]

[0081] The mobile object management device 601 according to the third embodiment of the present invention will be described, focusing on the differences from the first and second embodiments.

[0082] In the first and second embodiments, a movement area 200 as shown in FIG. 1 is assumed, but there are also cases where the moving objects 101 are operated in a movement area 200 that is much larger than that shown in FIG. 1. In such cases, there is a possibility that a bias occurs, such that the moving objects 101 are extremely sparse in some areas, while the moving objects 101 are extremely dense in other areas. In such cases, if the size of the basic grid 201 is equal to the size of each moving object 101, as assumed in the first or second embodiment, an unnecessary amount of calculation will be required in areas where the moving objects 101 are extremely sparse. This embodiment is intended to solve such a problem.

[0083] FIG. 11 is a schematic diagram for explaining a grid division method in the third embodiment. A vast movement area 200L is divided into grids 201L that are sufficiently larger than the size of the moving object 101, and nodes 202L and links 203L are defined. These large grids 201L are used for route planning and congested area setting. However, in this embodiment, a congested area setting process different from that in the first and second embodiments is performed. First, large grids 201L in which two or more moving objects 101 are expected to exist in a specific time period are set as congested areas.

[0084] A large grid 201L set in a congested area is divided into small grids 201S of a size that allows each moving object 101 to turn safely. New nodes 202S are set within each divided grid 201S, and new links 203SL connect the nodes 202S located on the periphery of the grid 201L to the nodes 202L in the large grid 201L adjacent to the congested area. By dividing the large grid 201L in this way and further modifying the graph structure 204L, it is possible to reduce the amount of calculations by using large grids 201L in areas where the moving objects 101 are extremely sparse in a vast movement area 200L, and to achieve efficient movement by using small grids 201S in areas where the moving objects 101 are densely populated.

[0085] In this embodiment, the small grids 201S are described as being square in shape, but any polygonal shape (e.g., hexagonal) can be used, as long as the size allows each moving object 101 to turn safely. Similarly, the large grids 201L can also be polygonal in shape (e.g., hexagonal). Furthermore, the shape and size of the small grids 201S do not need to be uniform. For example, if the large grid 201L cannot be filled with small grids 201S of a uniform shape, the large grid 201L may be filled with smaller grids 201S of a slightly different shape, as long as the large grid 201L can be turned safely.

[0086] It is also possible to use the grid division method described in this embodiment in combination with the grid division method described in embodiments 1 and 2. For example, a congested area set using large square grid 201L can be defined as a first congested area, and within the first congested area, a small square grid 201S can be used to set the congested area as described in embodiments 1 and 2, the congested area set as a result can be defined as a second congested area, and the grid 201S within the second congested area can be divided into right-angled isosceles triangular grid 201T as described in embodiments 1 and 2.

[0087] (summary) In the third embodiment, the congested area setting unit 609 divides the first congestion forecast grid 201L into a plurality of third grids 201S, and based on a planned route created using the plurality of first grids 201L after the first congestion forecast grid 201L has been divided into the plurality of third grids 201S, extracts, from the plurality of third grids 201S, third grids 201S where interference between two or more moving bodies 101 is expected as second congestion forecast grids, and sets a set of the second congestion forecast grids as a second congested area, the grid dividing unit 610 divides the second congestion forecast grid into a plurality of second grids 201T, and the route planning unit 608 creates the planned route using the plurality of first grids 201L after the first congestion forecast grid has been divided into the plurality of third grids 201S and the second congestion forecast grid has been divided into the plurality of second grids 201T.

[0088] According to the third embodiment configured as described above, in the movement area 200L where there is a bias in the degree of congestion of the moving bodies 101, it is possible to improve the movement efficiency of each moving body 101 while suppressing the amount of calculation required for route planning for multiple moving bodies 101. [Example]

[0089] A mobile object management device 601 according to the fourth embodiment of the present invention will be described, focusing on differences from the first to third embodiments.

[0090] In Examples 1 to 3, it is assumed that the shape of the grid 201 is a square. This is suitable for use in a building with a rectangular floor, but for use in a building with a floor of a more complex shape (for example, a building with curved walls), it may be desirable to define the grid 201 using various polygons instead of a square. In this example, a method for dividing the grid 201 defined using various polygons is disclosed.

[0091] Fig. 12 is a schematic diagram for explaining a grid division method in Example 4. In an actual site, grids 201 with a slightly distorted square shape would typically be used, for example, to fit along a curved wall surface, but in Fig. 12, the shapes of the grids 201 are intentionally varied to explain that the processing described below is generalized processing that can handle a variety of cases.

[0092] 12(A) shows grids 201 defined by various polygons, nodes 202 arranged in each grid 201, and links 203 between the nodes 202. Each link 203 is set to allow direct movement between two nodes 202 set in two adjacent grids 201 that share one side. In this embodiment, it is also assumed that the mobile object 101 can safely turn within each grid 201.

[0093] 12(B) shows an exclusive area 1201 when exclusive control is performed without dividing the grid 201. If direct movement between two nodes 202 located on two grids 201A and 201B that share only one vertex is allowed (by setting a link 203AB), without dividing the grid, the grids 201A and 201B and the grids 201C and 201D that share one edge with each of the grids 201A and 201B must be combined into the exclusive area 1201, which would result in an excessively large size of the exclusive area 1201.

[0094] 12C shows an exclusive area 1201 when exclusive control is performed after grid division. In this embodiment, grids 201C and 201D are divided using the edges of the convex hull containing grids 201A and 201B as boundaries, as in the second embodiment. This minimizes the size of the exclusive area 1201, enabling efficient movement even in congested areas.

[0095] As described above, in the mobile object management device according to this embodiment, even if the grid is defined using various polygons, it is possible to appropriately divide the grid according to the direction of movement and realize efficient movement in various directions.

[0096] (summary) In Example 4, the shape of each of the multiple first grids 201 is a polygon of a size that allows each of the multiple moving bodies 101 to rotate inside, and the grid division unit 610 divides the first congestion forecast grids 201C, 201D into multiple second grids 201C1, 201C2, 201D1, 201D2 using the edges of a convex hull that includes two first grids 201A, 201B that do not share any edges as boundaries.

[0097] According to the fourth embodiment configured as described above, it is possible to improve the movement efficiency of multiple moving bodies 101 while reducing the amount of calculation required for path planning for each moving body 101 in a movement area 200 in which a grid 201 is defined by various polygons.

[0098] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to add part of the configuration of one embodiment to the configuration of another embodiment, or to delete part of the configuration of one embodiment or replace it with part of another embodiment. [Explanation of symbols]

[0099] 100...operational environment, 101, 101A, 101B...moving body, 102...conveyor, 103...item, 104...station, 105...worker, 106...station, 107...dock, 109...conveyor, 200, 200L...moving area, 201, 201A, 201B, 201C, 201C1, 201C2, 201D, 201D1, 201D2, 201L ,201S, 201T, 201X, 201Y, 201Z... Grid, 202, 202L, 202S, 202X, 202Y... Node, 203, 203AB, 203L, 203M, 203XY... Link, 204, 204L... Graph structure, 205... Dock area, 206... Route, 301, 302, 401... Destination, 402... Exclusive area, 501... In-vehicle control controller, 502...target route management unit, 503...on-board sensor, 504...driving map management unit, 505...control command generation unit, 506...self-position calculation unit, 507...drive unit, 508...encoder, 509...communication unit, 600...mobile object management system, 601...mobile object management device, 601a...control server, 601b...input device, 601c...display, 602...graph / grid management unit, 603...mobile object information management unit, 604...exclusion state management unit, 605...exclusion control unit, 606...mobile object state management unit, 607...destination determination unit, 608...route planning unit, 609...congestion area setting unit, 610...grid division unit, 611...route determination unit, 612...communication unit, 613...instruction unit, 614...display unit, 901...congestion area, 1001, 1201...exclusion area.

Claims

1. A mobile object management device that manages a plurality of mobile objects moving within a predetermined movement area, a route planning unit that creates planned routes for the plurality of moving objects using a plurality of first grids obtained by dividing the movement area; a congested area setting unit that extracts, from the plurality of first grids based on the planned route, first grids in which interference between two or more of the plurality of moving objects is expected as first congestion forecast grids, and sets a set of the first congestion forecast grids as a first congested area; a grid dividing unit that divides the first congestion forecast grid into a plurality of second grids, each having at least one side that is not parallel to any side of the first congestion forecast grid; The route planning unit creates the planned route using the first grids obtained by dividing the first congestion forecast grid into the second grids. A mobile object management device characterized by:

2. 2. The mobile object management device according to claim 1, the congested area setting unit sets a time period in which interference between the two or more moving bodies is expected in the first congested area as an expected congested time period; The grid division unit Dividing the first congestion forecast grid into the plurality of second grids during the congestion forecast time period; The first congestion forecast grid is not divided into the plurality of second grids during a time period other than the congestion forecast time period. A mobile object management device characterized by:

3. 2. The mobile object management device according to claim 1, each of the plurality of first grids has a polygonal shape large enough for each of the plurality of moving bodies to rotate therein; The grid dividing unit divides the first congestion forecast grid into the plurality of second grids using, as a boundary line, an edge of a convex hull including two first grids that do not share any edge among the plurality of first grids. A mobile object management device characterized by:

4. 4. The mobile object management device according to claim 3, A plurality of nodes are arranged in the movement area, The planned route is defined by two or more nodes that each of the plurality of moving objects is scheduled to pass through among the plurality of nodes, and the order in which the two or more nodes are passed through. A mobile object management device characterized by:

5. 5. The mobile object management device according to claim 4, One node is arranged in each of the plurality of first grids. A mobile object management device characterized by:

6. 6. The mobile object management device according to claim 5, each of the plurality of first grids has a square shape; the plurality of first grids are arranged in a lattice pattern, One node is arranged at the center position of each of the plurality of first grids, the path planning unit enables the plurality of moving objects to move along a straight line connecting two nodes arranged on two first grids that share only one vertex, The sides of the convex hull are the diagonals of the square, The shape of each of the plurality of second grids is a right-angled isosceles triangle. A mobile object management device characterized by:

7. 2. The mobile object management device according to claim 1, the grid dividing unit divides the first congestion forecast grid into a plurality of third grids; the congested area setting unit extracts, from among the plurality of third grids, third grids in which interference between the two or more moving bodies is expected as second congestion forecast grids based on the planned route created using the plurality of first grids obtained after the first congestion forecast grid is divided into the plurality of third grids, and sets a set of the second congestion forecast grids as a second congested area; the grid dividing unit divides the second congestion forecast grid into the plurality of second grids; The route planning unit creates the planned route using the first grids obtained after the first congestion forecast grid is divided into the third grids and the second congestion forecast grid is divided into the second grids. A mobile object management device characterized by:

8. The mobile object management device according to claim 1; the plurality of moving bodies A mobile object management system characterized by:

9. A mobile object management method for managing a plurality of mobile objects moving within a predetermined movement area, comprising: a first step of creating a planned route for the plurality of moving objects using a plurality of first grids obtained by dividing the movement area; a second step of extracting, from among the plurality of first grids based on the planned route, first grids in which interference by two or more of the plurality of moving bodies is expected as first congestion forecast grids, and setting a set of the first congestion forecast grids as a first congested area; a third step of dividing the first congestion forecast grid into a plurality of second grids each having at least one side that is not parallel to any side of the plurality of first grids; and a fourth step of creating the planned route using the plurality of first grids obtained after the first congestion forecast grid is divided into the plurality of second grids. A mobile object management method comprising:

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