Method of controlling logistics robots, and control device

Abstract

A method of controlling a plurality of logistics robots operating within a preset operation boundary comprises the steps of: grouping the plurality of logistics robots to configure a plurality of work groups; and performing a mission defined for each of the configured plurality of work groups by a plurality of logistics robots grouped in a corresponding work group.

Description

Method and control device for controlling a logistics robot

[0001] The present invention relates to a method and a control device for controlling a logistics robot that implements automatic logistics optimization through organic grouping within an operation boundary.

[0002] Logistics robots are being introduced not only in general logistics warehouses and factories, but also in smart factories that manufacture products with different specifications using various parts, to ensure flexible and efficient supply and transport of parts.

[0003] Logistics robots are a general term for autonomous mobile robots (AMRs) and automated guided vehicles (AGVs), and these logistics robots can move and perform tasks under the control of a control device.

[0004] In a smart factory, logistics robots can move along optimal paths based on path planning to perform missions assigned by control devices.

[0005] Meanwhile, given the nature of logistics robots moving in smart factories, their work is non-stop. Furthermore, the more evenly the number of logistics robots assigned to a given task is operated, the more efficient the smart factory can be. Therefore, a method for grouping the number of logistics robots assigned to a given task is needed to increase overall factory efficiency.

[0006] 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.

[0007] Accordingly, the present invention aims to solve the technical problem of implementing automatic logistics optimization through organic grouping within an operational boundary.

[0008] 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.

[0009] A method for controlling a plurality of logistics robots operating within a preset operational boundary according to one embodiment may include a step of grouping the plurality of logistics robots to set a plurality of work groups; and a step of performing a mission defined for each of the plurality of set work groups by the plurality of logistics robots grouped into the corresponding work groups.

[0010] For example, the method may further include a step of adjusting group settings of the plurality of logistics robots grouped into each of the plurality of work groups based on the performance results of the missions performed by each of the plurality of work groups.

[0011] For example, the setting step may include a step of setting the number of logistics robots for each of the plurality of work groups under the operation limit number or distribution rate limit of the logistics robots set for each of the plurality of work groups.

[0012] For example, the method may further include a step of generating work commands for the plurality of logistics robots according to priorities set for each of the plurality of work groups.

[0013] For example, the plurality of work groups are defined according to a plurality of group classifications, and the group classifications may be configured as a tree structure including a top-level group classification and at least one or more subgroup classifications.

[0014] For example, the adjusting step may include a step of determining the mission performance results for each of the plurality of work groups based on the operating status or operating indicators of the plurality of logistics robots.

[0015] For example, the operating state may correspond to either an idle state or an operating state.

[0016] For example, the above operating indicator may be determined by the time required to supply parts compared to the time required to request supply of parts in a given process.

[0017] For example, the setting step may include a step of assigning logistics robots to each of the plurality of work groups under a limit on the number of operation limits or distribution rates of logistics robots set for each of the plurality of work groups, and the adjusting step may include a step of reallocating logistics robots to each of the plurality of work groups by adjusting the limit on the number of operation limits or distribution rates of logistics robots set for each of the plurality of work groups.

[0018] For example, in the above setting step, at least one individual logistics robot among the logistics robots can be simultaneously grouped into multiple work groups.

[0019] A control device for controlling a plurality of logistics robots operating within a preset operational boundary according to one embodiment may include a group management unit for grouping the plurality of logistics robots to set a plurality of work groups; and a work schedule management unit for determining the results of performing a mission defined for each of the plurality of set work groups by the plurality of logistics robots grouped into the corresponding work groups.

[0020] For example, the control device may further include a group adjustment unit that adjusts group settings of the plurality of logistics robots grouped into each of the plurality of work groups based on the result.

[0021] For example, the group management unit is a control device that sets the number of logistics robots for each of the plurality of work groups under the operation limit number or distribution rate limit of the logistics robots set for each of the plurality of work groups.

[0022] For example, the group management unit can generate work commands for the plurality of logistics robots according to priorities set for each of the plurality of work groups.

[0023] For example, the plurality of work groups are defined according to a plurality of group classifications, and the group classifications may be configured as a tree structure including a top-level group classification and at least one or more subgroup classifications.

[0024] For example, the work schedule management unit can determine the result for each of the plurality of work groups based on the operating status or operating indicator of the plurality of logistics robots.

[0025] For example, the operating state may correspond to either an idle state or an operating state.

[0026] For example, the above operating indicator may be determined by the time required to supply parts compared to the time required to request supply of parts in a given process.

[0027] For example, the group management unit may assign logistics robots to each of the plurality of work groups under the restrictions on the number of operational restrictions or distribution rates of logistics robots set for each of the plurality of work groups, and the group adjustment unit may reallocate logistics robots to each of the plurality of work groups by adjusting the restrictions on the number of operational restrictions or distribution rates of logistics robots set for each of the plurality of work groups.

[0028] For example, the group management unit can simultaneously assign at least one individual logistics robot among the logistics robots to multiple work groups.

[0029] According to the present invention, the work efficiency of the entire process can be increased by implementing automatic logistics optimization through organic grouping within the operation boundary.

[0030] 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.

[0031] FIG. 1 is a block diagram showing an example of an operational boundary configuration that can be applied to embodiments of the present invention.

[0032] FIG. 2 is a block diagram showing an example of a control device configuration that can be applied to embodiments of the present invention.

[0033] FIG. 3 is a block diagram showing an example of a logistics robot configuration that can be applied to embodiments of the present invention.

[0034] FIG. 4 is a perspective view showing an example of the exterior of a logistics robot that can be applied to embodiments of the present invention.

[0035] Figure 5 is a flowchart showing an example of a driving process of a logistics robot that can be applied to embodiments of the present invention.

[0036] Figure 6 is a flowchart for explaining the basic settings and operation of a control method of a logistics robot according to one embodiment of the present invention.

[0037] Figure 7 is a flowchart for explaining operational changes according to the progress of mission execution of a control method of a logistics robot according to one embodiment of the present invention.

[0038] FIG. 8 and FIG. 9 are drawings for explaining the operation of a group management unit according to one embodiment of the present invention.

[0039] 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 will be given the same reference numbers and redundant descriptions thereof will be omitted. The suffixes "module" and "part" used for components in the following description are assigned or used interchangeably only for the convenience of writing the specification, and do not in themselves have distinct meanings or roles. In addition, when describing the embodiments disclosed in this specification, if it is determined that a specific description of a related known technology may obscure the gist of the embodiments disclosed in this specification, a detailed description thereof will be omitted. In addition, the attached drawings are only intended to facilitate easy understanding of the embodiments disclosed in this specification, and the technical ideas disclosed in this specification are not limited by the attached drawings, and should be understood to include all modifications, equivalents, and substitutes included in the spirit and technical scope of the present invention.

[0040] 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.

[0041] 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.

[0042] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0043] 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.

[0044] 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.

[0045] First, the configuration of the operational boundary in which the logistics robot according to the embodiment is deployed and operated is described with reference to Fig. 1.

[0046] Figure 1 is a block diagram showing an example of an operational boundary configuration that can be applied to embodiments.

[0047] Referring to FIG. 1, the operation boundary (100) may include a logistics robot (110), a production device (120), a monitoring device (130), and a control device (140).

[0048] The operational boundary (100) may be equipped with multiple logistics robots (110), multiple production devices (120), and multiple detection devices (130) depending on the production process and target production speed of the product. The operational boundary (100) may be implemented as a smart factory, but is not necessarily limited thereto. Each component is described below.

[0049] First, the logistics robot (110) may include an autonomous mobile robot (hereinafter, referred to as "AMR" for convenience) and an automated guided vehicle (hereinafter, referred to as "AGV" for convenience). Depending on the operation policy of the logistics robot (110) in the operation boundary (100), only one type of AGV or AMR may be operated, or both AGV and AMR may be operated together within the operation boundary (100).

[0050] AGVs generally perform required actions (movement, direction change, stop, etc.) within the operating boundary (100) by recognizing and following guidance devices placed on the floor for guidance of the AGV. Here, guidance devices may refer to optically recognizable markers (spots, 2D codes, etc.), tags that can be recognized contactlessly at close range (e.g., NFC tags, RFID tags, etc.), magnetic strips, wires, etc., but these are examples and are not necessarily limited thereto. Guidance devices may be placed continuously on the floor or may be placed discontinuously and spaced apart from each other. Since AGVs fundamentally perform operations by recognizing and following guidance devices, they require guidance devices to be installed in advance before operation. Therefore, when moving the AGV to a new path or modifying an existing path, the guidance devices must be physically installed or modified. In addition, since AGVs do not deviate from the path set by the guidance devices, if an obstacle is detected on or around the path, the AGV typically stops until the detected obstacle disappears or separate control is applied. In the operation of AGV, the control device (140) must control the AGV based on the guidance equipment, so commands such as 'drive until the third marker is recognized' or 'change the heading direction by 90 degrees when the third marker is recognized' from the current location can be transmitted to the AGV as individual command units or mission units (e.g., recovery, supply, charging, patrol, etc.) including multiple commands.

[0051] AMR can determine its current location by sensing its surroundings (i.e., positioning), and its ability to perform path planning using positioning and a map is what most distinguishes it from AGVs. Therefore, if a map with compatible coordinates is shared between the AMR and the control device (140), the control device (140) can control the AMR by instructing the AMR on a path based on the coordinates. In addition, if an obstacle is detected while driving, the AMR can set an avoidance path on its own, avoid the obstacle, and then return to the original path. The function of the control device (140) setting the path of the AMR to one or more transit coordinates can be referred to as global path planning, and the function of the AMR setting a movement path or an avoidance path between transit coordinates according to the global path planning can be referred to as local path planning.

[0052] A more detailed configuration of the logistics robot (110) will be described later with reference to FIGS. 4 and 5, and the driving control process of the AMR will be described later with reference to FIG. 6.

[0053] Next, the production device (120) may refer to a device (e.g., a robot arm, a conveyor belt, etc.) that performs a production process of a product in the operation boundary (100), and in a broader sense, may refer to a device arranged to assist in the performance of missions such as entry and exit of a logistics robot (110) when the production process is performed by a person. The device arranged to assist in the performance of a mission may be, but is not necessarily limited to, a device that detects the status of a designated location where a pallet carried by a logistics robot (110) can be put down or collected within an area where a specific production process is performed, a device that determines the progress of the process, a means for blocking entry and exit within an area, etc.

[0054] For example, the production device (120) is controlled through a PLC (Programmable Logic Controller) and can communicate with a control device (140) in relation to the process progress.

[0055] The monitoring device (130) can perform a function of acquiring information for determining the situation within the operating boundary (100) and transmitting the information to the control device (140). For example, the monitoring device (130) may include a camera, a proximity sensor, etc., but is not necessarily limited thereto.

[0056] The control device (140) can communicate with the aforementioned components (110, 120, 130) to obtain information necessary for the operation of the operation boundary (100) or control each component. For example, the control device (140) can perform dispatching of the logistics robot (110), route setting, mission assignment, process management by product, material management, etc.

[0057] In implementation, the control device (140) may include a local control device (ACS: AMR / AGV Control System) that controls surrounding process facilities based on the location of the AGV / AMR and performs mission-based control of the AGV / AMR, and an integrated control device (MoRIMS: Mobile Robot Integrated Monitoring System) that integrates and controls two or more local control devices. The integrated control device may perform status and route, logistics flow setting, and traffic control of all logistics robots (110) within the operation boundary (100) from each of a plurality of local control devices. For example, when the local control device (ACS) is equipped in units of logistics robots of the same manufacturer or the same model, the integrated control device may perform integrated control for collision prevention, such as bottleneck level analysis of intersection / overlapping areas, driving acceleration / deceleration control, and regeneration of avoidance paths, through traffic distribution control between heterogeneous types based on information acquired through a plurality of local control devices (ACS).

[0058] In addition, the integrated control device can have a manufacturing execution system (MES) as its upper control subject, and the manufacturing execution system (MES) can be linked to an automated scheduler (APS: Advanced Planning & Scheduling).

[0059] In addition to the configuration (110, 120, 130, 140) of the operation boundary (100) described above, it goes without saying that devices for mutual communication between components such as beacons, repeaters, APs (Access Points), chargers for charging logistics robots (110), loading spaces for storing or loading parts, spaces for storing finished or intermediate products, traffic lights, circuit breakers, waiting spaces for idle logistics robots (110), etc. can be appropriately placed within the operation boundary (100).

[0060] Below, the configuration of a control device (140) that can be applied to embodiments of the present invention is described with reference to FIG. 2.

[0061] FIG. 2 is a block diagram illustrating an example of a control device configuration applicable to embodiments of the present invention. Each component illustrated in FIG. 2 primarily represents components related to embodiments of the present invention, and in the actual implementation of the control device (140), more or fewer components may be included.

[0062] Referring to FIG. 2, the control device (140) may include a firmware management unit (141), a traffic control unit (142), a process management unit (143), a production / logistics management unit (144), an inventory management unit (145), an optimal route calculation unit (146), a group control unit (147), a map management unit (148), and a work schedule management unit (149). Although not explicitly illustrated in FIG. 2, the control device (140) may further include a communication unit for exchanging signals with the remaining components (110, 120, 130) of FIG. 1.

[0063] The firmware management unit (141) can obtain the latest firmware of the logistics robot (110) through the communication unit and transmit it to the logistics robot (110) to perform a firmware update, thereby keeping the firmware of the logistics robot (110) up to date.

[0064] The traffic control unit (142) controls traffic lights and barriers based on the route of the logistics robot (110), and can also recalculate the route of the logistics robot (110) according to traffic.

[0065] The process management department (143) can define the process for each product and manage missions such as process progress and progress location.

[0066] The production / logistics management department (144) can dispatch logistics robots (110) based on missions.

[0067] The inventory management unit (145) manages the location and quantity of each material, and this information can be useful for more efficient process operation, such as sending the logistics robot (110) to the destination earlier than the time when actual assembly / consumption of materials is detected for pallet pickup or retrieval.

[0068] The optimal path generation unit (146) can generate a global path so that each logistics robot (110) constituting the work group can move along the optimal path within the work boundary according to the mission within the work group assigned by the group management unit (147b).

[0069] The group control unit (147) manages a work group for a plurality of logistics robots (110) and can operate and manage the logistics robots (110) within the work group. To this end, the group control unit (147) may include a group adjustment unit (147a) that performs group adjustment according to the operation results, as illustrated in FIGS. 6 and 7 to be described later, and a group management unit (147b) that performs work group management and control of the logistics robots accordingly. More specific operations of the group control unit (147) will be described later with reference to FIGS. 6 to 9.

[0070] The map management unit (148) may obtain map data in the form of a grid map obtained when an AMR among logistics robots (110) drives within the operation boundary (100), and may provide a tool that allows a factory manager to edit the obtained map data. By editing the map data, a zone, a virtual lane, an intersection, a no-entry zone, etc., in which one or more preset actions are performed when the logistics robot (110) enters, may be set, but this is merely an example and is not necessarily limited thereto. In addition, the map management unit (148) may distribute the corresponding map to the remaining logistics robots (110) other than the logistics robot (110) that initially obtained the grid map through actual driving, through the communication unit (146).

[0071] The work schedule management unit (149) can manage and monitor the mission of the logistics robot (110) based on the process information of the operation boundary (100) received from the production device (120) and the monitoring device (130) through the communication unit. In addition, the work schedule management unit (149) can select a specific logistics robot (110) and assign a mission to it.

[0072] Referring to FIG. 3, the logistics robot (110) may include a driving unit (111), a sensing unit (112), a loading unit (113), a communication unit (114), and a control unit (115). Each component is described below.

[0073] The driving unit (111) may include a driving source, wheels, suspension, etc. involved in the movement, steering, and stopping of the logistics robot (110). The driving source may be an electric motor supplied with power from a built-in battery (not shown). The wheels may include one or more driving wheels that receive driving power from the driving source, and non-driving wheels that rotate by the movement of the vehicle body without receiving driving power. Depending on the implementation, when multiple driving wheels are provided, the driving source may be matched to each driving wheel so that the rotation of each driving wheel can be independently controlled. In this case, by making the rotation directions of different driving wheels different, the vehicle body can be rotated and steering can be performed without a separate steering means. At least some of the non-driving wheels may be configured as caster-type wheels, but this is exemplary and is not necessarily limited thereto.

[0074] The sensing unit (112) is for detecting the surrounding environment of the logistics robot (110) or its own operating status, and may include at least one of a 2D laser scanner (e.g., LiDAR), a 3D vision (stereo) camera, a multi-axis gyro sensor, an acceleration sensor, a wheel encoder, and a proximity sensor.

[0075] An encoder can output information that can determine how much the wheel has rotated by using light emitted from a light-emitting element (e.g., a photodiode). For example, the encoder can count the number of slits arranged along the circumference of the wheel or a disk rotating with the wheel per unit time. The control unit (115) can perform odometry, which estimates displacement by analyzing the amount of position change over time using data acquired through the encoder and gyro sensor. However, the displacement estimated based on the encoder data may have an error from the actual displacement due to wheel slip or wear (change in diameter along with the wheel). Therefore, when performing odometry, the control unit (115) can perform noise and error correction on the information collected from the wheel and gyro sensor using a predetermined algorithm (e.g., EKF: Extended Kalman Filter) to output a result that tends to be close to the actual value. This odometry can be particularly useful when localization using a 2D laser scanner, as described later, is not possible.

[0076] 2D laser scanners scan their surroundings by projecting laser light onto a rotating reflector and detecting the reflected signal. By analyzing the intensity of the reflected signal and the time difference between the projection and reception, they can output detection results in the form of a point cloud.

[0077] A 3D vision camera can calculate the distance to an object based on the parallax between two cameras spaced a certain distance apart, i.e., the pixel distance between the images captured by each camera. A texture projector that projects infrared light in a predetermined pattern may also be included to enable detection of objects of the same color, such as flat surfaces (e.g., white walls).

[0078] Typically, 2D laser scanners are used for mapping, navigation, object recognition, etc., and 3D cameras can be used for navigation, especially for obstacle avoidance, but these are examples and are not necessarily limited to this.

[0079] The loading section (113) is a means for loading items to be transported, and may be a top plate on the upper part of the vehicle body itself, a table placed on the top plate, a lift, a turntable rotating along a vertical axis, a forklift, a conveyor, or a combination thereof. Similar to a forklift, a forklift may also support telescopic and tilting functions.

[0080] The communication unit (114) can communicate with other components within the operation boundary (100), such as the production device (120) and the control device (140), and can also support communication between logistics robots (110), and can also communicate with the charger when performing a charging mission.

[0081] The control unit (115) is a subject that performs overall control of each of the aforementioned components (111, 112, 113, 114), and can perform current mission, current location, destination determination, route planning, load control, etc. based on information obtained from the control device (140) through the communication unit (114).

[0082] FIG. 4 is a perspective view showing an example of the exterior of a logistics robot that can be applied to embodiments of the present invention.

[0083] Referring to FIG. 4, an example of an AMR is illustrated as a logistics robot (110). The body may have a track-shaped planar shape having a long axis extending along a single axis direction as a whole. One drive wheel (111-1) may be arranged in the center of the body in the single-axis direction, may be arranged on one side in the double-axis direction, and another drive wheel (not shown) may be arranged on the other side to face one drive wheel (111-1) in the double-axis direction. This arrangement of the drive wheels may be referred to as a 'differential drive (DD)'. Although not illustrated in FIG. 4, two or more non-drive wheels may be arranged on the lower part of the body. In this case, if two drive wheels rotate in the same direction at the same speed, forward or backward movement is possible along a single axis direction, and if they rotate in opposite directions at the same speed, they may extend along a three-axis direction and rotate around a rotation axis passing through the plane center (C) of the body. In addition, a sensor unit (112) may be placed on the front of the body, and a loading unit (113) may be placed on the upper surface. The loading unit (113) may be configured to be able to be raised and lowered along three axes, and a rack or tray may be fixed to the upper surface through a guide (113-1).

[0084] However, the AMR shape of the above-described Fig. 5 is exemplary, and it is obvious that the AGV may have a similar shape or the AMR may have a different shape.

[0085] Next, the driving process of the logistics robot (110) will be described with reference to Fig. 5.

[0086] Figure 5 is a flowchart illustrating an example of a driving process of a logistics robot (110) applicable to embodiments of the present invention. In Figure 5, for convenience, it is assumed that the logistics robot (110) is an AMR capable of positioning and local path planning.

[0087] Referring to Fig. 5, first, while the AMR drives within the operating boundary (100), it can obtain a real-world grid map through lidar, etc. (S501).

[0088] When the AMR transmits the acquired grid map to the control device (140), a grid map editing and matching process can be performed in the map management unit (148) of the control device (140) (S502). Here, the editing process can include a process of setting the aforementioned various zones in the aforementioned grid map, a process of assigning a cost to each grid, etc. Here, the cost assignment can be performed in a direction in which a higher cost is assigned the closer the AMR is to an obstacle or a no-entry area so that the AMR does not move around an obstacle or into an area that it should not enter. This is because, when the AMR sets a local route, it selects a set of cells with the lowest cost among waypoints as the route.

[0089] Additionally, the map matching process may mean a process of matching coordinates between a CAD map used in the design of the operational boundary (100), a real-world grid map (lidar map), and a topology map that has undergone an editing process.

[0090] Afterwards, the control device (140) can share the topology map with all AMRs in the factory through the communication unit (S503).

[0091] Subsequent steps may be applied to individual AMRs.

[0092] The AMR can determine (localize) its current location on the map using sensor data from the sensing unit (112) and the acquired map (S504). For example, the AMR can determine its current location by comparing the surrounding terrain acquired via lidar with the map based on feature points.

[0093] The control device (140) can select a specific AMR and assign a mission, and the mission can be assigned one or more waypoints, which are generally determined through global path planning. The waypoints can be defined by coordinates on a map, and can be accompanied by information about the direction (i.e., heading) that the AMR should head from the coordinates. Based on this mission assignment, a destination can be set for the AMR (Yes in S505), and the AMR can perform local path planning between waypoints based on the cost of the topology map (S506).

[0094] Once the path is determined, the AMR begins driving (S507). If an obstacle is detected by the sensing unit (112) during driving (Yes in S508), the AMR may perform an evasive maneuver by performing a local route search to bypass the detected obstacle (S509). In some cases, depending on the evasive maneuver or the failure of the evasive maneuver, the control device (140) may update the mission of the AMR.

[0095] Additionally, the AMR can also compensate for position errors during movement using the aforementioned odometry technique until it reaches its destination (S510).

[0096] After reaching the destination (S511), the AMR can perform mission-based maneuvers (S512). For example, the AMR can determine whether conditions for entering a specific process area are cleared, retrieve empty pallets at the destination, or drop off loads loaded on the loading section (113).

[0097] In the above, the configuration and operation method of the logistics robot (110), production device (120), monitoring device (130), and control device (140) included in the operation boundary (100) that can be applied to embodiments of the present invention have been described.

[0098] Hereinafter, a method of operating a logistics system in which a control device (140) controls a plurality of logistics robots (110) operating within a preset operational boundary, performs a mission through organic grouping within the operational boundary, and changes the settings of the group according to the result of the mission execution, thereby increasing the work efficiency of the entire process is described.

[0099] FIG. 6 is a flowchart illustrating the basic settings and operation of a control method for a logistics robot according to one embodiment of the present invention. As illustrated in FIG. 6, the group control unit (147) may include a group coordination unit (147a) and a group management unit (147b). For convenience, in the following drawings, including FIG. 6, it is assumed that the logistics robot (110) is an AMR capable of positioning and local path planning.

[0100] Referring to FIG. 6, information necessary for the initial setup of a work group may first be transmitted to the group management unit (147b) (S610, S620, S630). More specifically, production sequence information of a manufacturing execution system (MES) 210 may be transmitted to the group management unit (147b) via a logistics management system (220) (S610). In addition, process setup information from a production device (120) and monitoring device setup information from a monitoring device (130) may each be transmitted to the group management unit (147b) (S620). In addition, logistics robot information, including identification information and current location information, may be transmitted from each logistics robot (110) to the group management unit (147b) (S630).

[0101] The group management unit (147b) can perform initial setup of work groups (S640) based on the information acquired through the aforementioned processes (S610, S620, S630). For example, the group management unit (147b) can set up group definitions based on missions, initial assignment of logistics robots to each group, and logistics robot organization through designation of distribution rates (or quantities) for each group. The group definitions based on missions can be in the form of a tree, including one top-level group and at least one subgroup, but this is merely exemplary and is not necessarily limited thereto.

[0102] In addition, the group management unit (147b) can set up multiple work groups by grouping the multiple logistics robots (110) based on their current locations. For example, the group management unit (147b) can set up a group of logistics robots whose current locations are in a first process area (e.g., trim process) as a first work group, and can set up a group of logistics robots whose current locations are in a second process area (e.g., final process) as a second work group. At this time, the group management unit (147b) can set up the number of logistics robots (110) for each of the multiple work groups so as to satisfy the distribution ratio or quantity of logistics robots (110) set up for each of the multiple work groups.

[0103] The specific work group setting form will be described later with reference to FIGS. 8 and 9.

[0104] After completing the work group setup, the group management unit (149b) can transfer the work group setup information to the group coordination unit (147a) for future group coordination (S650).

[0105] Once the above-described setup procedure is completed, logistics robot control for process progress can be performed. To this end, operation boundary status information can first be collected from the work schedule management unit (149). Specifically, production sequence information from the production management system (210) can be transmitted to the work schedule management unit (149) via the logistics management system (S660). In addition, the logistics management system (220) can provide parts supply information, the production device (120) can provide process status information, and the monitoring device (130) can provide surrounding monitoring information to the work schedule management unit (149) (S671).

[0106] The work schedule management unit (149) can determine the mission required within the operation boundary based on each piece of information obtained, and transmit mission information (e.g., supply, recovery, charging, etc.) including the departure point and destination information to the group management unit (147b) (S672).

[0107] The group management unit (147b) can determine the task group to perform each mission (S673) and assign the mission to individual logistics robots within the group in charge based on the determined mission task group information (S674).

[0108] Mission information assigned to each logistics robot is transmitted to an optimal path calculation unit (146), and the optimal path calculation unit (146) can determine an optimal path for each logistics robot based on the mission. Logistics robot control can be performed in such a way that the determined optimal path information is transmitted to each logistics robot (S675).

[0109] Here, the logistics robot control process (S670) through the mission judgment of the work schedule management unit (149) based on real-time updated process information, group management of the group management unit (147b), mission assignment, and optimal path judgment of the optimal path calculation unit (146) through the same can be continuously and repeatedly performed along with the process progress.

[0110] When a mission is carried out by controlling a logistics robot through group configuration according to the process described above with reference to Figure 6, operational changes can be made based on the degree of mission completion. This is explained with reference to Figure 7.

[0111] Figure 7 is a flowchart illustrating operational changes according to mission execution progress in a method for controlling a logistics robot according to one embodiment of the present invention. Figure 7 may be a subsequent process following the process of controlling a logistics robot through Figure 6.

[0112] Referring to FIG. 7, the work schedule management unit (149) can obtain process status information from the production device (120) (S710), surrounding surveillance information from the monitoring device (130) (S720), and logistics robot information (identification information, route information, location information, etc.) from the logistics robot (110) (S730). The work schedule management unit (149) can determine the logistics robot mission execution result based on the obtained information and provide it to the group coordination unit (147a) (S740). The logistics robot mission execution result may include whether the mission execution time requirement is satisfied, the execution time deviation for each mission, the movement time ratio of the logistics robot during the mission, the mission execution ratio for each logistics robot, the occurrence or degree of mission delay due to traffic congestion, unnecessary waiting, work delay due to lack of logistics robots, or a score or index calculated through a combination thereof, but this is exemplary and is not necessarily limited to this as long as it can indicate whether a problem occurred in the mission execution and is not restricted in any form.

[0113] For example, the mission execution result may include an operating status and an operating index. At this time, the operating status of the logistics robot (110) may correspond to either an idle state or a run state depending on whether a task is assigned. Here, the idle state may correspond to a state in which no task is assigned to the logistics robot (110), and the run state may correspond to a state in which a task is assigned to the logistics robot (110). In addition, the operating index of the logistics robot (110) may be determined by the time required for supplying parts compared to the time required for requesting supply of parts in a given process. At this time, the time required for requesting supply of parts may be set differently for each process, and the time required for supplying parts may correspond to the time period from the time the logistics robot (110) receives a request for supply work to the time it drops the load in the corresponding process area, but is not necessarily limited thereto. The operating index of the logistics robot (110) may be set to 100 (%) if the time required for supplying parts is less than or equal to the time required for requesting supply of parts.

[0114] The group coordination unit (147a) updates the distribution ratio of logistics robots by work group based on the mission performance results (S750), and can reallocate logistics robots by group according to the updated distribution ratio (S760).

[0115] This process (S750, S760) is not performed if there is no problem with the mission performance result (e.g., the pre-set evaluation element conditions are satisfied), but can be performed if it is determined that there is a problem with the mission performance result.

[0116] If the work group settings are updated / adjusted through steps S750 to S760, the updated / adjusted group settings information can be transmitted to the group management unit (147b) (S770).

[0117] Each detailed step (S781, S782, S783, S784, S785) of the control process (S780) of the logistics robot performed based on the updated setting information thereafter corresponds to each detailed step (S671, S672, S673, S674, S675) of the step S670 described above with reference to FIG. 6, and thus, any overlapping description will be omitted.

[0118] Figures 8 and 9 are diagrams illustrating the operation of a group management unit according to one embodiment of the present invention. In Figures 8 and 9, it is assumed that the operational boundary is a smart factory for vehicle production.

[0119] As described above, the functions of the group management unit (147b) may include group definition, group-specific logistics robot assignment, etc.

[0120] For example, the group management unit (147b) can define three upper groups, Trim, Chassis, and Final C, as shown in FIG. 8, through information collected through steps S610, S620, and S630 of FIG. 6. Group definition can be made based on various criteria, and in the case of FIGS. 8 and 9, it can be made based on the process type in a production plant.

[0121] Additionally, subgroups can be defined for each parent group based on group items corresponding to different missions. For example, for the trim group, three subgroups can be defined based on the supply / recovery missions for parts A, B, and C, respectively.

[0122] For logistics robot (AMR) allocation ratios, the upper group can be set based on the overall distribution ratio of logistics robots within the task boundary, while the lower group can be set based on the distribution ratio within that upper group. The allocation of individual logistics robots can be automated based on their location and number of logistics robots, or can be manually configured by the operator.

[0123] Furthermore, as illustrated in Figure 9, a specific logistics robot (No. 1) may be assigned to multiple subgroups. For example, assuming a total of 16 logistics robots, the trim group accounts for 50% of the total, resulting in eight logistics robots belonging to the trim group. The trim groups are further assigned to components A, B, and C in a ratio of 4:4:2. Through the redundant assignment of logistics robot No. 1, this ratio can be satisfied with eight logistics robots.

[0124] To aid understanding, Figures 8 and 9 illustrate the subgroup classification by component-specific supply / retrieval missions. However, this is merely exemplary, and various user-defined functions are possible, such as waiting at specific locations within boundaries, rearranging logistics objects, speed synchronization, and group driving. Furthermore, the group classification is illustrated as a tree structure of upper and lower groups. This is also exemplary, and the tree structure can be configured in various stages and forms depending on the contents and missions of each stage.

[0125] As discussed above, the present invention can increase the work efficiency of a smart factory by adjusting the settings of groups and agents according to the results of mission execution of logistics robots in a smart factory, and can implement automatic logistics optimization through organic grouping within the operation boundary.

[0126] Meanwhile, the present invention described above can be implemented as computer-readable code on a medium in which a program is recorded. A computer-readable medium includes 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 in the scope of the present invention.

Claims

1. A method for controlling multiple logistics robots operating within a preset operating boundary, A step of setting up multiple work groups by grouping the above multiple logistics robots; and A method for controlling a logistics robot, comprising a step of performing a mission defined for each of the plurality of work groups set above by a plurality of logistics robots grouped into the corresponding work groups.

2. In paragraph 1, A method for controlling a logistics robot, further comprising a step of adjusting group settings of the plurality of logistics robots grouped into each of the plurality of work groups based on the results of performing the missions performed by each of the plurality of work groups.

3. In paragraph 1, The steps to set up above are: A method for controlling a logistics robot, comprising a step of setting the number of logistics robots for each of the plurality of work groups under the limitation of the number of operation limits or distribution rates of the logistics robots set for each of the plurality of work groups.

4. In paragraph 1, A method for controlling a logistics robot, further comprising the step of generating work commands for the plurality of logistics robots according to priorities set for each of the plurality of work groups.

5. In paragraph 1, The above multiple work groups are defined according to multiple group classifications, A method for controlling a logistics robot, wherein the group classification is composed of a tree structure including a top-level group classification and at least one sub-group classification.

6. In paragraph 1, The above adjustment steps are: A method for controlling a logistics robot, comprising a step of determining the results of mission performance for each of the plurality of work groups based on the operating status or operating indicators of the plurality of logistics robots.

7. In paragraph 6, The above operating status is, A method of controlling a logistics robot in either an idle state or an operating state.

8. In paragraph 6, The above operating indicators are, A method of controlling a logistics robot, wherein the time required to supply parts is determined by the time required to request parts for supply in a given process.

9. In paragraph 2, The steps to set up above are: A step of assigning logistics robots to each of the plurality of work groups under the limitation of the number of operational restrictions or distribution ratios of logistics robots set for each of the plurality of work groups is included. The above adjustment steps are: A method for controlling a logistics robot, comprising a step of reallocating the logistics robots for each of the plurality of work groups by adjusting the operating limit number or distribution rate limit of the logistics robots set for each of the plurality of work groups.

10. In paragraph 1, The steps to set up above are: A method for controlling a logistics robot, characterized in that at least one individual logistics robot among the above logistics robots is simultaneously grouped into multiple work groups.

11. In a control device that controls multiple logistics robots operating within a preset operating boundary, A group management unit that groups the above-mentioned multiple logistics robots to set up multiple work groups; and A control device including a work schedule management unit that determines the results of performing a mission defined for each of the plurality of work groups set above by a plurality of logistics robots grouped into the corresponding work group.

12. In paragraph 11, A control device further comprising a group adjustment unit that adjusts group settings of the plurality of logistics robots grouped into each of the plurality of work groups based on the results.

13. In paragraph 11, The above group management department, A control device that sets the number of logistics robots for each of the plurality of work groups under the operation limit number or distribution rate limit of the logistics robots set for each of the plurality of work groups.

14. In paragraph 11, The above group management department, A control device that generates work commands for the plurality of logistics robots according to priorities set for each of the plurality of work groups.

15. In paragraph 11, The above multiple work groups are defined according to multiple group classifications, A control device, wherein the above group classification is composed of a tree structure including a top-level group classification and at least one sub-group classification.

16. In paragraph 11, The above work schedule management department, A control device that determines the results for each of the plurality of work groups based on the operating status or operating indicators of the plurality of logistics robots.

17. In paragraph 16, The above operating status is, A control device that is in either an idle or operating state.

18. In paragraph 16, The above operating indicators are, A control device that determines the time required to supply parts compared to the time required to request parts for a given process.

19. In paragraph 12, The above group management department, Assigning logistics robots to each of the plurality of work groups under the limitation of the number of operational restrictions or distribution ratio of logistics robots set for each of the plurality of work groups, The above group coordination department, A control device that reallocates logistics robots to each of the plurality of work groups by adjusting the operating limit number or distribution rate limit of the logistics robots set for each of the plurality of work groups.

20. In paragraph 11, The above group management department, A control device characterized in that at least one individual logistics robot among the above logistics robots is assigned to multiple work groups simultaneously.

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