Logistics robot simulation system and method

Abstract

Provided are a logistics robot simulating system and method, the system comprising: a performance unit for performing product production simulation using logistics robots; and an operation control unit, which determines a reference operation quantity of logistics robots on the basis of performance results of the product production simulation performed by the performance unit on the basis of a preset initial operation quantity of logistics robots, changes the reference operation quantity according to a preset change rule, and determines an optimal operation quantity of logistics robots on the basis of additional performance results of the product production simulation additionally performed by the performance unit on the basis of the changed reference operation quantity.

Description

Simulation system and method for logistics robots

[0001] The present invention relates to a simulation system and method for a logistics robot for optimally operating a logistics robot within an operational boundary including the logistics robot.

[0002]

[0003] Recently, logistics robots are being introduced not only in general logistics warehouses and factories, but also in operational boundaries where various parts are used to manufacture products of different specifications, for the flexible and efficient supply and transport of parts.

[0004] Logistics robots are a general term for autonomous mobile robots (AMRs) and automated guided vehicles (AGVs). These logistics robots can move and perform tasks under the control of a control system.

[0005] In particular, with the recent introduction of logistics robots, interest in simulations to check the operating environment of logistics robots is increasing.

[0006] However, most commercial simulations use the number of logistics robots in operation as a fixed variable, deriving results such as operational efficiency and work time. While this approach may be appropriate for factories with fixed production targets, such as existing conveyor belt factories, this approach is less appropriate for factories equipped with cell production systems for flexible multi-vehicle production, as the number of logistics robots in operation can vary depending on factors such as market conditions, consumer spending patterns, and production plans.

[0007] Therefore, in the case of factories equipped with cell production methods for flexible production of multiple vehicles, a different simulation method than the existing one needs to be applied.

[0008]

[0009] The matters described as background technology above are only intended to enhance understanding of the background of the present invention, and should not be taken as an admission that they correspond to prior art already known to those skilled in the art.

[0010]

[0011] The present invention has been proposed to achieve the above-described purpose, and provides a simulation system and method for logistics robots capable of determining the optimal number of logistics robots to be operated by dynamically changing the number of logistics robots to be operated and performing a simple simulation before performing a normal simulation by setting the number of logistics robots to be operated.

[0012]

[0013] The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by a person having ordinary skill in the technical field to which the present invention belongs from the description below.

[0014]

[0015] In order to achieve the above object, the simulation system of a logistics robot according to the present invention may include: a performing unit that performs a simulation based on the number of logistics robots in operation; and an operating control unit that determines a standard operating number of the logistics robots based on a result of a simple simulation performed by the performing unit based on a preset initial operating number of the logistics robots, changes the standard operating number according to a preset change rule, and determines an optimal operating number of the logistics robots based on an additional performing result of the simple simulation additionally performed by the performing unit based on the changed standard operating number.

[0016]

[0017] In addition, a simulation method of a logistics robot according to the present invention for achieving the above purpose may include a step of determining a standard operating number of logistics robots based on a result of a simple simulation performed based on a preset initial operating number of logistics robots; a step of changing the standard operating number according to a preset change rule; a step of additionally performing the simple simulation based on the changed standard operating number; and a step of determining an optimal operating number of logistics robots based on a result of the additional performance of the simple simulation.

[0018]

[0019] According to the above, the simulation system and method of the logistics robot of the present invention can flexibly change the operating conditions, such as the number of operating units for the logistics robot, and can derive the result values ​​of the simulation that take into account the changed operating conditions according to the change in the operating conditions.

[0020] In addition, by performing a simple simulation with changing operating conditions before a normal simulation is performed and then determining the optimal number of logistics robots based on the results, time resources for deriving the optimal value can be saved.

[0021]

[0022] The effects that can be obtained from the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by a person having ordinary skill in the art to which the present invention belongs from the description below.

[0023]

[0024] FIG. 1 is a block diagram illustrating a simulation system of a logistics robot according to one embodiment of the present invention.

[0025] FIG. 2 is a block diagram for explaining an operation control unit provided in a simulation system of a logistics robot according to one embodiment of the present invention.

[0026] FIG. 3 is a diagram for explaining a process for determining a reference operating number according to one embodiment of the present invention.

[0027] Figure 4 is a flowchart for explaining a simulation method of a logistics robot according to one embodiment of the present invention.

[0028]

[0029] In describing the embodiments disclosed in this specification, detailed descriptions of related known technologies will be omitted if it is determined that such detailed descriptions may obscure the gist of the embodiments disclosed in this specification. In addition, the attached drawings are provided solely to facilitate understanding of the embodiments disclosed in this specification, and the technical concepts disclosed in this specification are not limited by the attached drawings, and should be understood to include all modifications, equivalents, and substitutes included within the spirit and technical scope of the present invention.

[0030] Terms that include ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by these terms. These terms are used solely to distinguish one component from another.

[0031] When a component is referred to as being "connected" or "connected" to another component, it should be understood that it may be directly connected or connected to that other component, but that there may be other components intervening. Conversely, when a component is referred to as being "directly connected" or "connected" to another component, it should be understood that there are no other components intervening.

[0032] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0033] In this specification, terms such as “include” or “have” are intended to specify the presence of a feature, number, step, operation, component, part or combination thereof described in the specification, but should be understood not to exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts or combinations thereof.

[0034] In addition, the term "Unit" or "Control Unit" included in the internal configuration names of logistics robots or control devices is merely a term widely used to name a control device (Controller) that controls a specific function, and does not mean a generic function unit. For example, each control device may include a modem / transceiver that communicates with other control devices or sensors to control the function it is responsible for, a memory that stores an operating system or logic commands and input / output information, and one or more processors that perform judgments, calculations, and decisions necessary for controlling the function it is responsible for. Depending on the implementation, one processor may be responsible for calculations for multiple control devices.

[0035] Hereinafter, embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Regardless of the drawing numbers, identical or similar components are given the same reference numbers and redundant descriptions thereof will be omitted.

[0036]

[0037] The present invention aims to determine the optimal number of logistics robots to be operated by dynamically changing the number of logistics robots in operation, performing a simple simulation, and then performing a normal simulation based on the determined optimal number of logistics robots. To achieve this goal, a logistics robot simulation system and method according to one embodiment of the present invention will be described below.

[0038] Meanwhile, the normal simulation mentioned above may refer to a simulation that is performed repeatedly at least once, based on the optimal number of logistics robots set. Furthermore, the simple simulation, named to distinguish it from the normal simulation, may refer to a simulation that is performed only once, with the number of logistics robots changed accordingly. These names are for convenience of explanation, and the meaning of each simulation is not limited to their respective names.

[0039] In addition, the logistics robots mentioned in the following specification are used as a general term for smart logistics vehicles equipped within the operational boundary, such as autonomous mobile robots (AMRs), automated guided vehicles (AGVs), and unmanned forklifts.

[0040]

[0041] Referring to FIG. 1 below, a simulation system for a logistics robot according to one embodiment of the present invention will be described.

[0042] FIG. 1 is a block diagram illustrating a simulation system of a logistics robot according to one embodiment of the present invention.

[0043] Referring to Fig. 1, a simulation system (100) for a logistics robot according to one embodiment of the present invention may include a planning unit (110), an execution unit (120), and an operation control unit (130). Fig. 1 mainly illustrates components related to one embodiment of the present invention, and it is obvious that fewer or more components may be included when implementing an actual simulation system.

[0044] Below, each component is described.

[0045] The planning unit (110) can collect demand information, logistics information, and material information and establish a product production plan based on this information. Furthermore, the planning unit (110) can generate a list of tasks to be performed by the logistics robot to produce products according to the established product production plan. The planning unit (110) can provide the product production plan and task list to the execution unit (120).

[0046] The execution unit (120) can perform a simulation that imitates the operating environment of a logistics robot, and can set the number of logistics robots to be operated based on the product production plan and work list provided by the planning unit (110), and perform a simulation based on the set number of operations. For example, the execution unit (120) may include a constraint generation module (not shown) that creates constraints on the operation of logistics robots, such as the starting position, movement path, and number of logistics robots to be operated, based on the work list generated by the planning unit (110), and a simulation execution module (not shown) that simulates the operating environment of logistics robots in 3D and performs a simulation based on the product production plan and work list provided by the planning unit (110) while taking into account the constraints provided from the driving model.

[0047] For example, the simulation system (100) of a logistics robot may refer to a system equipped with a digital twin function, but this is an example and is not necessarily limited thereto.

[0048]

[0049] In the case of the existing simulation system (100), the number of logistics robots in operation was set based on code, and simulations were performed by assigning logistics robots to each task list. However, since the number of logistics robots in operation was set based on code, there was a problem that when the number of logistics robots in operation needed to be changed, it took a long time to change the number of logistics robots in operation, resulting in a waste of time.

[0050] To solve this problem, a simulation system (100) of a logistics robot according to one embodiment of the present invention may be equipped with an operation control unit (130).

[0051] According to one embodiment of the present invention, the operation control unit (130) sets the number of logistics robots to be operated, and before the execution unit (120) performs a normal simulation, the number of logistics robots to be operated is dynamically changed, and a simple simulation is performed to determine the optimal number of logistics robots to be operated. A detailed description of the operation control unit (130) will be described with reference to FIGS. 1 and 2.

[0052] FIG. 2 is a block diagram for explaining an operation control unit provided in a simulation system of a logistics robot according to one embodiment of the present invention.

[0053] Referring to FIG. 2, an operation control unit (130) according to one embodiment of the present invention may include a dynamic control unit (131), an allocation unit (132), and a result analysis unit (133). FIG. 2 mainly illustrates components related to one embodiment of the present invention, and it is obvious that fewer or more components may be included when implementing an actual operation control unit (130).

[0054] Below, the functions of each component of the operation control unit (130) that can be applied to one embodiment of the present invention are briefly described.

[0055] The dynamic control unit (131) can set the number of logistics robots in operation or change the number of operational units when a change in the number of operational units is required. At this time, the dynamic control unit (131) can pop up a list of logistics robots so that the number of logistics robots in operation can be set or changed by the worker, and the number of operational units can be set or changed according to pre-stored setting or change logic. In addition, the dynamic control unit (131) can provide information on the set or changed number of operational units to the allocation unit (132).

[0056] The allocation unit (132) can collect information about the task list generated by the planning unit (110), and collect information about the number of operating units set or changed in the dynamic control unit (131) to sequentially assign the task list to each logistics robot corresponding to the set or changed number of operating units. For example, the allocation unit (132) can first sort the list of tasks to be performed based on the planned start time so that the task list is sequentially assigned to the logistics robots at first, and then the task list is sequentially assigned to the logistics robots that have completed the task.

[0057] In addition, the allocation unit (132) can generate a work schedule by sequentially allocating a work list to each logistics robot corresponding to the number of operations. The allocation unit (132) can transmit the generated work schedule to the execution unit (120) so that the execution unit (120) can perform a simulation according to the work schedule.

[0058] The result analysis unit (133) collects the performance results of the simulation performed in the execution unit (120) based on the work schedule generated in the allocation unit (132), and can analyze the change in the number of operations and the operational efficiency of the logistics robot based on the performance results.

[0059] In addition, the dynamic control unit (131), allocation unit (132), and result analysis unit (133) can transmit and receive data to each other and perform cooperative control.

[0060]

[0061] Hereinafter, the function of the operation control unit (130) will be specifically described with reference to FIGS. 1 and 2 based on the functions of the dynamic control unit (131), allocation unit (132), and result analysis unit (133) described above.

[0062] An operation control unit (130) according to one embodiment of the present invention may determine a standard operating number of logistics robots based on the results of a simple simulation performed by the execution unit (120) based on a preset initial operating number of logistics robots, change the standard operating number according to a preset change rule, and determine an optimal operating number of logistics robots based on the results of an additional simple simulation performed by the execution unit (120) based on the changed standard operating number.

[0063] Specifically, the dynamic control unit (131) can set the initial number of logistics robots to be operated, and can transmit information about the set initial number of operations to the allocation unit (132). Based on the information about the initial number of operations, the allocation unit (132) can sequentially allocate a task list to each logistics robot corresponding to the initial number of operations to generate a task schedule. The allocation unit (132) can transmit the generated task schedule to the execution unit (120), and the execution unit (120) can perform the simple simulation based on the task schedule until the number of times the simple simulation is performed reaches a preset reference number.

[0064] At this time, the dynamic control unit (131) can change the initial number of operations until the number of times the simple simulation is performed in the execution unit (120) reaches a reference number. More specifically, the dynamic control unit (131) can change the initial number of operations so that the initial number of operations decreases at a certain rate as the number of times the simple simulation is performed increases until the number of times the simple simulation is performed reaches the reference number. For example, when the initial number of operations is set to 48, the dynamic control unit (131) can change the initial number of operations from 48 to 24 and from 24 to 12 as the number of times the simple simulation is performed increases, so that the initial number of operations decreases by half. However, this is merely an example and is not necessarily limited thereto, and it is of course possible to change the initial number of operations by applying various rates.

[0065] Meanwhile, whenever the initial operating number is changed in the dynamic control unit (131), the allocation unit (132) can change the work schedule based on the changed initial operating number and transmit it to the execution unit (120), and the execution unit (120) can receive the changed work schedule from the allocation unit (132) whenever the initial operating number is changed and perform a simple simulation based on it.

[0066] And, when the number of times the simple simulation is performed reaches a preset standard number of times, the dynamic control unit (131) can determine the standard operating number based on the results of the simple simulation performed the standard number of times. This will be explained with reference to Fig. 3.

[0067]

[0068] FIG. 3 is a diagram for explaining a process for determining a reference operating number according to one embodiment of the present invention.

[0069] The graph shown in Fig. 3 may be a graph based on the results of a simple simulation performed a standard number of times. Accordingly, referring to Fig. 3, the x-axis of the graph may represent the number of logistics robots in operation, and the y-axis may represent the total running time of the logistics robots according to the results of the simple simulation. For example, the initial number of operations may be The number of operations that can be performed until the number of simple simulations reaches the reference number is changed. , It could be.

[0070] The dynamic control unit (131) can determine the standard operating number by performing the least square method (LSM) based on the results of a simple simulation performed a standard number of times according to the change in the operating number of logistics robots. For example, the dynamic control unit (131) , , Based on the performance results for each operation log, a quadratic function is predicted, and the operation log (e.g., t shown in FIG. 3) corresponding to the time (e.g., t shown in FIG. 3) at which the total driving time according to the performance results in the predicted quadratic function is the minimum value is calculated. ) can be judged as the standard operating logarithm.

[0071] Once the standard operating number is determined, the dynamic control unit (131) can transmit the determined standard operating number to the allocation unit (132), and the allocation unit (132) can create a work schedule based on the standard operating number and transmit it to the execution unit (120). The execution unit (120) can perform a simple simulation based on the work schedule according to the standard operating number.

[0072] And, after performing a simple simulation based on a work schedule according to the number of reference operating logs, the execution unit (120) can additionally perform a simple simulation based on the number of reference operating logs. At this time, the dynamic control unit (131) can change the number of reference operating logs according to a preset change rule. For example, the preset change rule may be a rule that changes the number of reference operating logs with an increase or decrease as the number of additional executions of the simple simulation increases based on the number of reference operating logs, and accordingly, the dynamic control unit (131) can change the number of reference operating logs in the order of +1, -1, +2, -2 as the number of additional executions increases based on the number of reference operating logs. As the number of reference operating logs is changed in the dynamic control unit (131), the execution unit (120) can additionally perform a simple simulation based on the changed number of reference operating logs.

[0073]

[0074] The result analysis unit (133) can receive additional performance results of the simple simulation additionally performed by the execution unit (120), and can determine the optimal number of logistics robots to be operated based on the additional performance results provided.

[0075] More specifically, the result analysis unit (133) can determine whether there is a need for additional changes in the changed reference operating number based on the additional execution results of the additionally performed simple simulation. For example, the result analysis unit (133) can determine the total running time of the logistics robot according to the changed reference operating number included in the additional execution results of the additionally performed simple simulation, and determine whether there is a need for additional changes in the changed reference operating number based on the determined total running time. The result analysis unit (133) can compare the determined total running time with the total running time included in the execution results of the previously performed simple simulation, and determine that there is no need for additional changes in the changed reference operating number if the determined total running time is greater than the total running time included in the execution results of the previously performed simple simulation.

[0076] Meanwhile, if the determined total driving time is less than the total driving time included in the previously performed execution results, the result analysis unit (133) may determine that an additional change in the changed reference operating number is necessary. Accordingly, the result analysis unit (133) may generate a command for the additional change and transmit it to the dynamic allocation unit (131), and the dynamic allocation unit (131) may further change the changed reference operating number based on the command for the additional change according to a preset change rule. In addition, the dynamic allocation unit (131) may transmit the additionally changed operating number to the allocation unit (132), and the allocation unit (132) may generate a work schedule according to the additionally changed operating number and transmit it to the execution unit (120). The execution unit (120) may additionally perform a simple simulation based on the work schedule generated according to the additionally changed operating number, and the result analysis unit (133) may again determine whether to further change the additionally changed operating number based on the performance result of the additionally performed simple simulation.

[0077] If no further change in the changed standard operating number is required, the result analysis unit (133) can determine the optimal operating number based on the results of all simple simulations performed up to the point at which it is determined that no further change is required. For example, the results of the simple simulations may include at least one of the total driving time, deviation rate, number of bottleneck occurrences, and delay occurrence times in addition to the number of operating vehicles. Accordingly, the result analysis unit (133) can determine at least one of the total driving time, deviation rate, number of bottleneck occurrences, and delay occurrence times included in the results of all simple simulations performed up to the point at which it is determined that no further change is required, and compare the determined at least one among all simple simulations.

[0078] The result analysis unit (133) can compare at least one of the judged values ​​among all simple simulations and determine the number of logistics robots in operation corresponding to the result of the simple simulation with the smallest value as the optimal number of operations. For example, the result analysis unit (133) can determine the number of logistics robots in operation corresponding to the simple simulation with the smallest total driving time, the smallest deviation value, the smallest number of bottleneck occurrences, or the shortest delay occurrence time among all simple simulations performed before the point at which it is determined that no additional changes are necessary as the optimal number of operations.

[0079] In addition, when comparing two or more of the total driving time, deviation rate, number of bottleneck occurrences, and delay occurrence times included in the results of the simple simulation in the result analysis unit (133), the judgment priority may be set in advance among the total driving time, deviation rate, number of bottleneck occurrences, and delay occurrence times, and the comparison results may be derived by sequentially comparing each result data according to the preset judgment priority. However, this is an example and is not necessarily limited thereto.

[0080] The result analysis unit (133) can determine the optimal number of operations and transmit information about the determined optimal number of operations to the allocation unit (132). The allocation unit (132) can generate a work schedule according to the optimal number of operations and provide it to the execution unit (120), and the execution unit (120) can perform a normal simulation based on the work schedule generated according to the optimal number of operations.

[0081] That is, by performing a simple simulation once before repeatedly performing a normal simulation in the execution unit (120) and determining the optimal number of operations through the operation control unit (130) based on the result of the simple simulation, time resources for deriving an optimal value can be saved.

[0082]

[0083] Hereinafter, a simulation method of a logistics robot according to one embodiment of the present invention will be described with reference to FIG. 4 based on the configuration of the simulation system of the logistics robot described above through FIGS. 1 to 3.

[0084] For convenience of explanation, below, it is assumed that the functions of the dynamic control unit (131), allocation unit (132), and result analysis unit (133) are all performed in the operation control unit (130), and the description of each step is omitted as it has been specifically described in detail through FIGS. 1 to 3.

[0085] Figure 4 is a flowchart for explaining a simulation method of a logistics robot according to one embodiment of the present invention.

[0086] Referring to FIG. 4, the operation control unit (130) can set the initial number of operations (S401) and sequentially assign a work list to each logistics robot corresponding to the initial number of operations to create a work schedule (S402).

[0087] The operation control unit (130) transmits the generated work schedule to the execution unit (120), and the execution unit (120) can perform a simple simulation based on the generated work schedule (S403). The execution unit (120) determines whether the number of times the simple simulation is performed reaches a reference number (S404), and can perform the simple simulation until the number of times the simple simulation is performed reaches the reference number. At this time, if the number of times the simple simulation is performed does not reach the reference number (No in S404), the operation control unit (130) can change the initial number of operations (S405) and perform steps S402 to S404 again.

[0088] When the number of times the simple simulation is performed reaches the standard number of times (Yes in S404), the operation control unit (130) can determine the standard number of operations based on the results of the simple simulation performed the standard number of times (S406). Then, the operation control unit (130) can create a work schedule according to the determined standard number of operations (S407) and transmit the created work schedule to the execution unit (120). The execution unit (120) can perform the simple simulation based on the work schedule created according to the standard number of operations (S408).

[0089] Thereafter, if additional simple simulations are performed beyond the standard number of times, the operation control unit (130) can change the standard number of operations according to preset change rules (S409). Then, the operation control unit (130) can create a work schedule based on the changed standard number of operations (S410), and transmit the created work schedule back to the execution unit (120). The execution unit (120) can additionally perform simple simulations based on the transmitted work schedule (S411).

[0090] The operation control unit (130) can determine whether additional changes are required in the changed reference operating number based on the total driving time included in the additional execution result of the additionally performed simple simulation performed by the execution unit (120) (S412). If the total driving time according to the additional execution result of the additionally performed simple simulation is less than the total driving time according to the execution result of the previously performed simple simulation (No in S412), the operation control unit (130) determines that additional changes in the changed reference operating number are required (S413), and returns to step S409 to further change the changed reference operating number according to the preset change rules.

[0091] If the total driving time according to the additional performance result of the additionally performed simple simulation is greater than the total driving time according to the performance result of the previously performed simple simulation (Yes in S412), the operation control unit (130) determines that no additional change in the changed reference number of operations is necessary, and can determine the optimal number of operations based on the performance results of all simple simulations performed up to the point where it is determined that no additional change is necessary (S414).

[0092] Thereafter, the operation control unit (130) can generate a final work schedule based on the determined optimal number of operations (S415) and transmit the final generated work schedule to the execution unit (120). The execution unit (120) can perform a normal simulation based on the final generated work schedule (S416).

[0093]

[0094] According to the above, the simulation system and method of the logistics robot of the present invention can flexibly change the operating conditions, such as the number of operating units for the logistics robot, and can derive the result values ​​of the simulation that take into account the changed operating conditions according to the change in the operating conditions.

[0095] In addition, by performing a simple simulation with changing operating conditions before a normal simulation is performed and then determining the optimal number of logistics robots based on the results, time resources for deriving the optimal value can be saved.

[0096]

[0097] Although the present invention has been illustrated and described with respect to specific embodiments thereof, it will be apparent to those skilled in the art that the present invention may be variously improved and modified without departing from the technical spirit of the invention as defined by the claims below.

[0098] The present invention described above can be implemented as computer-readable code on a medium having a program recorded thereon. Computer-readable media include all types of recording devices that store data that can be read by a computer system. Examples of computer-readable media include hard disk drives (HDDs), solid-state disks (SSDs), silicon disk drives (SDDs), ROMs, RAMs, CD-ROMs, magnetic tapes, floppy disks, and optical data storage devices. Therefore, the above detailed description should not be construed as limiting in any respect, but rather as illustrative. The scope of the present invention should be determined by a reasonable interpretation of the appended claims, and all changes within the equivalent scope of the present invention are intended to be included within the scope of the present invention.

Claims

1. A performance unit that performs simulation based on the number of operational logs of logistics robots; and A simulation system for a logistics robot, comprising: an operation control unit for determining a standard operation number of the logistics robots based on the results of a simple simulation performed by the execution unit based on a preset initial operation number of the logistics robots, changing the standard operation number according to a preset change rule, and determining an optimal operation number of the logistics robots based on the results of an additional execution of the simple simulation additionally performed by the execution unit based on the changed standard operation number.

2. In claim 1, The above operation control unit A simulation system for logistics robots, characterized in that when the number of operational units for the above logistics robots is set or changed, a work list is sequentially assigned to each logistics robot corresponding to the set or changed number of operational units to create a work schedule.

3. In claim 1, The above-mentioned execution unit performs the above-mentioned simple simulation until the number of times the above-mentioned simple simulation is performed reaches a preset standard number of times, The above operation control unit A simulation system for a logistics robot, characterized in that the initial number of operations is changed until the number of times the simple simulation performed in the above-mentioned execution unit reaches the reference number of operations, and when the number of times the simple simulation is performed reaches the preset reference number of operations, the reference number of operations is determined based on the performance results of the simple simulation performed the reference number of operations.

4. In claim 3, The above operation control unit A simulation system for a logistics robot, characterized in that the initial number of operations is changed so that the initial number of operations decreases at a certain rate as the number of operations increases until the number of operations reaches the reference number.

5. In claim 1, The above operation control unit A logistics robot simulation system characterized in that it determines whether additional changes to the changed reference operating number are necessary based on the additional performance results of the additionally performed simple simulation, and if additional changes to the changed reference operating number are not necessary, it determines the optimal operating number based on the performance results of all simple simulations performed up to the point at which it is determined that additional changes are not necessary.

6. In claim 5, The above operation control unit A simulation system for a logistics robot, characterized in that the total running time of the logistics robot according to the changed reference operating number included in the additional execution result of the additionally performed simple simulation is determined, and whether additional change to the changed reference operating number is necessary is determined based on the determined total running time.

7. In claim 6, The above operation control unit A simulation system for a logistics robot, characterized in that if the total driving time determined above is greater than the total driving time included in the results of a previously performed simple simulation, it is determined that no additional change in the changed standard operating number is necessary.

8. In claim 5, The above operation control unit A simulation system for logistics robots, characterized in that at least one of the total driving time, deviation rate, number of bottleneck occurrences, and delay occurrence time included in the performance results of all of the above simple simulations is determined for each of the above simple simulations, and the determined at least one is compared among all of the above simple simulations, and the number of operational units for the logistics robots corresponding to the performance result of the simple simulation having the smallest value is determined as the optimal number of operational units.

9. In claim 1, The above operation control unit generates a work schedule according to the determined optimal operation number and provides it to the execution unit. A simulation system for a logistics robot, characterized in that the above-mentioned performing unit performs a normal simulation based on the provided work schedule.

10. A step of determining the standard operating number of logistics robots based on the results of a simple simulation performed based on the initial operating number set for the logistics robots; A step of changing the above-mentioned standard operating number according to a preset change rule; A step of additionally performing the above simple simulation based on the above changed standard operating number; and A simulation method for a logistics robot, comprising: a step of determining the optimal number of logistics robots to be operated based on the additional performance results of the above simple simulation.

11. In claim 10, The step for determining the above standard operating number is A step of generating a work schedule by sequentially assigning a work list to each logistics robot corresponding to the initial operating number; and A simulation method for a logistics robot, characterized by including a step of performing a simulation of the production of the goods based on the generated work schedule.

12. In claim 10, The step for determining the above standard operating number is The above-mentioned execution unit performs the simple simulation while changing the initial operating number until the number of times the simple simulation is performed reaches a preset standard number of times; and A simulation method for a logistics robot, characterized in that it includes a step of determining the standard number of operations based on the results of a simple simulation performed the standard number of times when the number of executions reaches a preset standard number of times.

13. In claim 12, The steps for performing the above product production simulation are: A step of changing the initial number of operations so that the initial number of operations decreases at a certain rate as the number of operations increases until the number of operations reaches the reference number; and A simulation method for a logistics robot, characterized by including a step of performing the simple simulation based on the changed initial operating number.

14. In claim 10, The step of determining the above optimal operating number is A step of determining whether additional changes are necessary in the changed reference operating number based on the additional performance results of the above simple simulation; and A simulation method for a logistics robot, characterized in that it includes a step of determining the optimal operating number based on the additional performance results of all simple simulations performed up to the point in time at which it is determined that no additional change is necessary, when no additional change is necessary in the above-mentioned changed reference operating number.

15. In claim 14, The above judging steps are A step for determining the total running time of the logistics robot according to the changed reference operating number included in the additional execution results of the above simple simulation; and A simulation method for a logistics robot, characterized by including a step of determining whether additional changes are necessary in the changed standard operating number based on the determined total driving time.

16. In claim 15, The step to determine whether additional changes are necessary is A simulation method for a logistics robot, characterized in that if the total driving time determined above is greater than the total driving time included in the results of a previously performed simple simulation, it is determined that no additional change in the changed reference operating number is necessary.

17. In claim 14, The step of determining the above optimal operating number is A step of determining at least one of the total driving time, deviation rate, number of bottleneck occurrences, and delay occurrence time included in the performance results of all of the above simple simulations for each of the above simple simulations; and A simulation method for a logistics robot, characterized by comprising: a step of determining the number of operational units for the logistics robot corresponding to the result of the simple simulation having the smallest value among all the simple simulations by comparing at least one of the above-determined values as the optimal number of operational units.

18. In claim 10, After the step of determining the optimal operating number, A step of generating a work schedule according to the above-determined optimal operating number; and A simulation method for a logistics robot, characterized in that it further includes a step of performing a normal simulation based on the generated work schedule.

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