Intelligent logistics vehicle control method and control device

Abstract

The invention discloses an intelligent logistics vehicle control method and a control device. The method comprises the following steps: controlling at least one intelligent logistics vehicle to move to a position corresponding to a plurality of candidate destinations related to a currently allocated task and used for identifying the destinations; in the moving process of the intelligent logistics vehicle, when the intelligent logistics vehicle enters the position used for identifying the destination, whether the intelligent logistics vehicle can enter at least one candidate destination in the multiple candidate destinations or not is determined; the candidate destinations that can be entered among the plurality of candidate destinations are configured as final destinations.

Description

Technical Field

[0001] This invention relates to a method and device for controlling intelligent logistics vehicles, which provides a movement path that allows intelligent logistics vehicles to move from a starting point to a selected destination. Background Technology

[0002] In recent years, intelligent logistics vehicles have been introduced not only in conventional logistics warehouses and factories, but also in smart factories that use various components to manufacture goods of different specifications, in order to flexibly and efficiently supply and transport components.

[0003] Intelligent logistics vehicles are a collective term for autonomous mobile robots (AMRs) and automated guided vehicles (AGVs). These intelligent logistics vehicles can move and perform tasks under the control of a control system.

[0004] For example, when an intelligent logistics vehicle performs a task from its origin to its destination, the control system can generate a movement path connecting the origin and accessible points to the destination by determining the conditions at the destination. Furthermore, the control system can control the intelligent logistics vehicle to perform the task from origin to destination based on the generated movement path.

[0005] However, even if the destination is determined to be accessible when the movement path is generated, it may become inaccessible due to the status of other smart logistics vehicles or processes while the smart logistics vehicle is moving. In this case, the smart logistics vehicle that is heading to the destination according to the existing task may be unable to enter the destination and therefore cannot fully perform the existing task. The smart logistics vehicle fails to enter the destination and remains near the destination, resulting in a stalemate with other smart logistics vehicles near the destination.

[0006] Furthermore, if the initially determined destination is inaccessible when generating a movement path, a movement path may not be generated, or an alternative accessible destination may be determined to generate a movement path. In this case, the initially determined destination may become accessible, but even if it becomes accessible, the following problems may arise: the intelligent logistics vehicle may remain in a waiting state at the departure point because it was previously unable to access the initially determined destination, or it may move to a different destination than the initially determined destination.

[0007] Therefore, it is necessary to propose a solution that can perform existing tasks even when the conditions at the destination change as the intelligent logistics vehicle moves along the movement path connecting the origin and destination.

[0008] The above description of the background technology is intended only to enhance the understanding of the background of the present invention and should not be regarded as an admission that it corresponds to the prior art known to those skilled in the art. Summary of the Invention

[0009] Technical issues The present invention is proposed to solve the above-mentioned problems and aims to provide an intelligent logistics vehicle control method and control device, which can determine in advance whether the destination is accessible when the intelligent logistics vehicle moves from the starting point to the selected destination.

[0010] The technical tasks to be achieved by the present invention are not limited to those described above, and those skilled in the art to which the present invention pertains can clearly understand other unmentioned technical tasks through the following description.

[0011] Technical solution The intelligent logistics vehicle control method according to the present invention for achieving the above objectives includes: controlling at least one intelligent logistics vehicle to move to a destination confirmation location corresponding to a plurality of candidate destinations related to a currently assigned task; when at least one intelligent logistics vehicle moves, determining whether at least one of the plurality of candidate destinations is accessible upon entering the destination confirmation location; and setting the accessible candidate destination among the plurality of candidate destinations as the final destination.

[0012] Furthermore, the control device according to the invention for achieving the above objectives includes a communication unit and a route selection unit; the communication unit is used to communicate with at least one intelligent logistics vehicle; the route selection unit is used to control at least one intelligent logistics vehicle to move to a destination confirmation location corresponding to a plurality of candidate destinations related to the currently assigned task, and when at least one intelligent logistics vehicle moves, upon entering the destination confirmation location, determines whether at least one of the plurality of candidate destinations is accessible, and sets the accessible candidate destination among the plurality of candidate destinations as the final destination.

[0013] Beneficial effects As described above, the intelligent logistics vehicle control method and control device of the present invention can determine whether the predetermined destination is accessible when the intelligent logistics vehicle moves from the starting point to the predetermined destination. When the predetermined destination is inaccessible, the destination can be changed to another accessible destination that performs the same task, thereby smoothly executing the task previously assigned to the intelligent logistics vehicle.

[0014] The effects achievable by this invention are not limited to those described above. Through the following description, those skilled in the art will clearly understand other effects not mentioned. Attached Figure Description

[0015] Figure 1This is a block diagram illustrating an example of the configuration of a smart factory applicable to exemplary embodiments of the present invention.

[0016] Figure 2 This is a block diagram illustrating an example of the configuration of a control device applicable to exemplary embodiments of the present invention.

[0017] Figure 3 This is a block diagram illustrating an example of the configuration of an intelligent logistics vehicle applicable to exemplary embodiments of the present invention.

[0018] Figure 4 This is a perspective view showing an example of the appearance of an intelligent logistics vehicle applicable to exemplary embodiments of the present invention.

[0019] Figure 5 This is a flowchart illustrating an example of the driving process of an intelligent logistics vehicle applicable to an exemplary embodiment of the present invention.

[0020] Figure 6 This is a block diagram illustrating the operation of a control device according to an exemplary embodiment of the present invention.

[0021] Figure 7 This is a schematic diagram illustrating the determination of candidate destinations for intelligent logistics vehicles according to an exemplary embodiment of the present invention.

[0022] Figure 8 This is a schematic diagram illustrating an intelligent logistics vehicle control method according to an exemplary embodiment of the present invention. Detailed Implementation

[0023] In describing the exemplary embodiments disclosed in this specification, detailed descriptions of relevant known technologies may be omitted where it is determined that such detailed descriptions might obscure the essential points of the exemplary embodiments disclosed herein. Furthermore, the accompanying drawings are intended only to facilitate understanding of the exemplary embodiments disclosed herein; the technical concepts disclosed herein are not limited to the drawings and should be understood to include all modified, equivalent, or alternative embodiments encompassed within the spirit and scope of the invention.

[0024] Terms including ordinal numbers such as first and second can be used to describe various components, but components are not limited by these terms. These terms are only used to distinguish one component from another.

[0025] When it is said that a component is "connected" or "joined" to another component, it should be understood that the component can be directly connected or joined to the other component, but other components can also be inserted between them. On the other hand, when it is said that a component is "directly connected" or "directly joined" to another component, it should be understood that there are no other components in between.

[0026] Unless the context clearly indicates otherwise, singular expressions may include plural expressions.

[0027] In this specification, terms such as “comprising” or “having” are intended to indicate the presence of the features, values, steps, operations, components, parts or combinations thereof described in the specification, and should not be construed as excluding the presence or addition of one or more other features, values, steps, operations, components, parts or combinations thereof.

[0028] In the following description, exemplary embodiments disclosed in this specification will be described in detail with reference to the accompanying drawings. However, regardless of the drawing numbers, the same or similar components will be given the same reference numerals, and redundant descriptions will be omitted.

[0029] Furthermore, the terms "unit," "control unit," or "control device" included in the names of the internal components of intelligent logistics vehicles are broadly used to refer to controllers used to control specific functions, and do not refer to general-purpose functional units. For example, to control the functions they are responsible for, each controller may include a modem / transceiver for communicating with other control devices or sensors, a memory for storing operating system or logic instructions and input / output information, and one or more processors for performing the determinations, calculations, and decisions required to control the functions it is responsible for. According to embodiments, one processor may be responsible for the calculations of multiple control devices.

[0030] First, refer to Figure 1 This describes the configuration of a smart factory set up and operated by smart logistics vehicles according to an exemplary embodiment.

[0031] Figure 1 This is a block diagram illustrating an example of the configuration of a smart factory applicable to exemplary embodiments of the present invention.

[0032] Reference Figure 1 The smart factory 100 may include a smart logistics vehicle 110, a production device 120, a monitoring device 130, and a control device 140.

[0033] The smart factory 100 can be equipped with multiple smart logistics vehicles 110, multiple production units 120, and multiple monitoring devices 130, depending on the product's production process and target production speed. Each component will be described below.

[0034] First, the intelligent logistics vehicle 110 may include autonomous mobile robots (hereinafter referred to as "AMRs" for convenience) and automated guided vehicles (hereinafter referred to as "AGVs" for convenience). Depending on the operating policy of the intelligent logistics vehicle 110, only one of AGVs or AMRs may be operated in the intelligent factory 100, or both AGVs and AMRs may be operated simultaneously in a single intelligent factory 100.

[0035] AGVs typically perform the operations required within a smart factory (movement, direction change, stopping, etc.) by recognizing and following guide facilities set up on the ground to guide them. In this document, guide facilities can refer to optically identifiable markers (marking points, QR codes, etc.), short-range contactless identifiable tags (e.g., NFC tags, RFID tags, etc.), magnetic strips, wires, etc., but this is exemplary and not necessarily limited to these. Guide facilities can be set up continuously on the ground or spaced discontinuously between each other. Since AGVs essentially operate by recognizing and following guide facilities, these facilities need to be pre-installed before operation and physically established or modified when moving the AGV along a new path or modifying an existing path. Furthermore, AGVs will not deviate from the path set up by the guide facilities; therefore, when an obstacle is detected on or around the path, the AGV will typically stop until the detected obstacle is removed or individual control is provided. During the operation of the AGV, the control device 140 should control the AGV based on the guidance facility. Therefore, instructions such as "travel to the third mark" and "change the direction of travel by 90 degrees when the third mark is detected" can be sent to the AGV as a single instruction unit or as a task unit including multiple instructions (e.g., retrieval, supply, charging, patrolling, etc.).

[0036] The AMR can determine its current position (i.e., localization) by detecting its surrounding environment, and it can perform path planning using localization and a map, which is the biggest difference between it and an AGV. Therefore, when the AMR and control device 140 share a map with compatible coordinates, the control device 140 can control the AMR by instructing it on a path based on coordinates. Furthermore, when an obstacle is detected during travel, the AMR can autonomously set an avoidance path to bypass the obstacle and return to the existing path. The function of the control device 140 in setting the AMR's path using one or more transit coordinates can be called global path planning, and the function of the AMR in setting a movement path or avoidance path between transit coordinates based on the global path planning can be called local path planning.

[0037] A more detailed description of the intelligent logistics vehicle 110 will be provided in reference to... Figure 3 and Figure 4 The driving control process of AMR will be described later with reference to Figure 5 Described later.

[0038] Next, production device 120 can refer to a device (e.g., a robotic arm, conveyor belt, etc.) that performs the production process of a product in the smart factory 100. In a broader sense, when the production process is performed by humans, it can refer to a device installed to assist in tasks such as the entry and exit of the smart logistics vehicle 110. Devices installed to assist in the execution of tasks may include, but are not limited to: devices for detecting the status of a designated position in the area where a pallet carried by the smart logistics vehicle 110 can be unloaded or retrieved, devices for determining the progress of the process, and devices for preventing entry and exit within the area.

[0039] For example, the production unit 120 can be controlled by a programmable logic controller (PLC) and can communicate with the control unit 140 regarding process progress.

[0040] The monitoring device 130 can perform the following functions: acquiring information to determine the situation within the smart factory 100 and sending it to the control device 140. For example, the monitoring device 130 may include, but is not limited to, cameras, proximity sensors, etc.

[0041] The control device 140 can communicate with the aforementioned components 110, 120, and 130 to obtain the information required for the operation of the smart factory 100 or to control the components. For example, the control device 140 can perform tasks such as scheduling, route setting, task allocation, process management of each product, and material management for the smart logistics vehicle 110.

[0042] In an implementation, the control unit 140 may include local control units (ACS: AMR / AGV control system) and integrated control units (MoRIMS: Mobile Robot Integrated Monitoring System). The local control units control surrounding process equipment based on the position of the AGV / AMR and perform task-based control of the AGV / AMR. The integrated control unit is used to comprehensively control two or more local control units. The integrated control unit can acquire the status and paths of all intelligent logistics robots 110 within the smart factory 100 from each of the multiple local control units and perform logistics process setup and traffic control. For example, when the local control units (ACS) are set up as units of intelligent logistics robots from the same manufacturer or of the same model, the integrated control unit can perform integrated control such as bottleneck analysis of intersecting / overlapping areas, acceleration / deceleration control, and collision avoidance path regeneration for collision prevention, based on information obtained through multiple local control units (ACS), through heterogeneous traffic allocation control.

[0043] In addition, the integrated control unit can have a manufacturing execution system (MES) as the upper-level control body, and the manufacturing execution system can be linked with the advanced planning and scheduling (APS) system again.

[0044] Obviously, in addition to the above-mentioned components 110, 120, 130, and 140 of the smart factory 100, devices such as beacons, repeaters, or access points (APs) for communication between components, chargers for charging the smart logistics vehicle 110, loading spaces for storing or loading components, spaces for storing final or intermediate products, traffic lights, barriers, and waiting spaces for idle smart logistics vehicles 110 can also be appropriately installed within the smart factory 100.

[0045] In the following text, reference will be made to Figure 2 The configuration of a control device 140 applicable to an exemplary embodiment of the present invention is described.

[0046] Figure 2 This is a block diagram illustrating an example of the configuration of a control device applicable to exemplary embodiments of the present invention. Figure 2 The components shown may primarily represent those relevant to exemplary embodiments of the invention, and may include more or fewer components in the actual implementation of the control device 140.

[0047] Reference Figure 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, a communication unit 146, a vehicle monitoring unit 147, and a map management unit 148.

[0048] The firmware management unit 141 can obtain the latest firmware of the intelligent logistics vehicle 110 through the communication unit 146 and send it to the intelligent logistics vehicle 110 to perform firmware update, thereby keeping the firmware of the intelligent logistics vehicle 110 up-to-date.

[0049] The traffic control unit 142 can control traffic lights and barriers based on the path of the intelligent logistics vehicle 110, and can recalculate the path of the intelligent logistics vehicle 110 according to traffic conditions.

[0050] The process management unit 143 can define the processes for each product and manage tasks such as process progress and location.

[0051] The production / logistics management unit 144 can schedule intelligent logistics vehicles 110 based on tasks.

[0052] The inventory management unit 145 can manage the location and quantity of each material, which can help to operate more efficiently, for example, by enabling the smart logistics vehicle 110 to depart in advance to the destination for pallet picking or recycling before the actual assembly or consumption of materials is detected.

[0053] The communication unit 146 can communicate with internal components of the smart factory 100, such as the smart logistics vehicle 110, production unit 120, and monitoring device 130, as well as external entities such as firmware update servers.

[0054] The vehicle monitoring unit 147 can monitor the location, path, battery status, communication status, and powertrain status of each intelligent logistics vehicle 110. In this document, the path can be a concept encompassing both global paths based on waypoints and real-time local paths. Furthermore, battery status can include voltage, current, temperature, peak voltage and current, state of charge (SOC), state of health (SOH), etc. Communication status can include information about the currently active communication protocol (e.g., Wi-Fi), the connected access point (AP), the distance to the AP, and the channel being used. Additionally, powertrain status can include the load, temperature, and RPM of the drive system.

[0055] In addition, the vehicle monitoring unit 147 can identify the tasks, operating modes, firmware versions, etc. currently assigned to each intelligent logistics vehicle 110.

[0056] The map management unit 148 can obtain raster map data acquired by the AMR in the intelligent logistics vehicle 110 while it is driving within the intelligent factory 100, and can provide factory managers with tools to edit the acquired map data. By editing the map data, areas, virtual lanes, intersections, and restricted areas that the intelligent logistics vehicle 110 performs one or more preset operations upon entry can be set, but this is exemplary and not necessarily limited to. In addition, the map management unit 148 can distribute the corresponding map to other intelligent logistics vehicles 110 besides the intelligent logistics vehicle 110 that obtained the initial raster map through actual driving via the communication unit 146.

[0057] Next, we will refer to Figure 3 and Figure 4 Describe intelligent logistics vehicles.

[0058] Figure 3 This is a block diagram illustrating an example of the configuration of an intelligent logistics vehicle applicable to exemplary embodiments of the present invention.

[0059] Reference Figure 3The intelligent logistics vehicle 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 will be described below.

[0060] The driving unit 111 may include a drive source, wheels, suspension, etc., involved in the movement, steering, and stopping of the intelligent logistics vehicle 110. The drive source may be a motor powered by a built-in battery (not shown). The wheels may include one or more drive wheels that receive driving force from the drive source, and non-drive wheels that rotate by the movement of the vehicle body without receiving driving force. According to an embodiment, when multiple drive wheels are provided and a drive source is matched to each drive wheel, the rotation of each drive wheel can be controlled independently. In this case, steering can be performed by changing the rotation direction of the different drive wheels without a separate steering device. At least some of the non-drive wheels may be configured as caster-type wheels, but this is exemplary and not a limitation.

[0061] The sensing unit 112 can be used to sense the surrounding environment of the intelligent logistics vehicle 110 or its own operating status, and may include at least one of a two-dimensional laser scanner (e.g., LiDAR), a three-dimensional vision (stereo) camera, a multi-axis gyroscope sensor, an accelerometer, a wheel encoder, and a proximity sensor.

[0062] An encoder can use light emitted from a light-emitting element (e.g., a photodiode) to output information for determining the amount of wheel rotation. For example, an encoder can count the number of slits arranged circumferentially on the wheel or a disk rotating with the wheel per unit time. Control unit 115 can use data obtained from the encoder and gyroscope sensors to analyze the change in position relative to time, thereby performing odometry to estimate displacement. However, due to wheel slippage or wear (change in the dynamic diameter of the wheel), the displacement estimated based on encoder data may differ from the actual displacement. Therefore, when performing odometry, control unit 115 can use a predetermined algorithm (e.g., an EKF: Extended Kalman Filter) to correct for noise and errors in the information collected from the wheel and gyroscope sensors, thereby outputting a result that tends to be close to the actual value. This odometry can be particularly useful when the current position (location) cannot be determined using a two-dimensional laser scanner, as described later.

[0063] A two-dimensional laser scanner can scan its surroundings by emitting laser beams through a rotating mirror and sensing the reflected and returning signals. In this case, by analyzing the intensity of the reflected signals and the time difference between emission and reception, detection results in the form of point clouds can be output.

[0064] A 3D vision camera can calculate the distance to an object based on the parallax between two cameras spaced at a predetermined distance (i.e., the pixel distance between images captured by each camera). In this case, a texture projector that projects infrared light in a predetermined pattern can be set up, thus enabling the detection of planar objects of the same color (e.g., a white wall).

[0065] Typically, 2D laser scanners can be used for surveying, navigation, object recognition, etc., while 3D cameras can be used specifically to avoid obstacles during navigation, but this is exemplary and not necessarily limited to these.

[0066] Loading unit 113 can be a device for loading goods to be transported, and can be the top plate itself on the upper part of the vehicle body or a work platform, lift, turntable rotating along a vertical axis, forklift, conveyor, or combination thereof mounted on the top plate. In the case of a forklift, it is similar to a forklift and can support telescopic and tilting functions.

[0067] The communication unit 114 can communicate with other components in the smart factory 100, such as the production unit 120 and the control unit 140, and can also support communication between smart logistics vehicles 110 and communicate with the charging device when performing charging tasks.

[0068] The control unit 115 can be a subject that performs overall control over each of the aforementioned components 111, 112, 113, and 114, and can perform tasks such as current task determination, current location determination, destination determination, path planning, and control of the loading unit based on information obtained from the control device 140 through the communication unit 114.

[0069] Figure 4 This is a perspective view showing an example of the appearance of an intelligent logistics vehicle applicable to exemplary embodiments of the present invention.

[0070] Reference Figure 4 An example of an AMR can be shown as an intelligent logistics vehicle 110. The vehicle body can be integrally formed with a long axis extending along axis 1. One drive wheel 111-1 can be positioned in the central portion of the vehicle body along axis 1 and on one side along axis 2, while another drive wheel (not shown) can be positioned on the other side along axis 2, facing drive wheel 111-1. This arrangement of the drive wheels can be referred to as differential drive (DD). Although Figure 4Not shown, but the lower part of the vehicle body may be equipped with two or more non-drive wheels. In this case, when two drive wheels rotate in the same direction at the same speed, it can move forward or backward along axis 1; when two drive wheels rotate in opposite directions at the same speed, it can rotate based on a rotation axis extending along axis 3 and passing through the center (C) of the vehicle body. Furthermore, sensing unit 112 may be disposed on the front surface of the vehicle body, and loading unit 113 may be disposed on the upper surface. Loading unit 113 may be configured to rise along axis 3, and racks, trays, etc., may be fixed to the upper surface via guides 113-1.

[0071] However, the above Figure 4 The AMR form is exemplary; obviously, AGVs can also have similar forms, or AMRs can have different forms.

[0072] Next, we will refer to Figure 5 Describe the driving process of intelligent logistics vehicle 110.

[0073] Figure 5 This is a flowchart illustrating an example of the driving process of an intelligent logistics vehicle 110 applicable to an exemplary embodiment of the present invention. Figure 5 For the sake of convenience, we assume that the intelligent logistics vehicle 110 is an AMR capable of positioning and local route setting.

[0074] Reference Figure 5 First, AMR can obtain measured grid maps (S501) by using LiDAR and other methods when driving within 100 smart factories.

[0075] When the AMR sends the obtained raster map to the control device 140, the raster map editing and matching process (S502) can be performed in the map management unit 148 of the control device 140. In this document, the editing process may include setting various regions on the raster map, assigning a cost to each raster, etc. In this document, the cost is assigned as follows: the closer the AMR is to an obstacle or restricted area, the higher the cost is assigned, so that the AMR does not move around the obstacle or restricted area. This is because when setting a local path, the AMR selects the set of cells with the lowest cost among the path points as the path.

[0076] In addition, the map matching process can refer to the process of matching coordinates between CAD maps, measured grid maps (LiDAR maps), and edited topology maps used in the design of Smart Factory 100.

[0077] Subsequently, the control device 140 can share the topology map with all AMRs in the plant via the communication unit 146 (S503).

[0078] The subsequent steps can be a process applied to a single AMR.

[0079] The AMR can determine its current location on a 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 obtained by LiDAR with the map based on feature points.

[0080] The control device 140 can select a specific AMR to assign a task, which can typically be assigned to one or more waypoints determined through global path planning. Waypoints can be defined as coordinates on a map and can include information about the direction the AMR should face (i.e., the direction of travel) at the corresponding coordinates. Depending on the task assignment, a destination can be set in the AMR ("Yes" in S505), and the AMR can perform local path planning between waypoints based on the cost of the topology map (S506).

[0081] When a path is determined, the AMR can begin driving (S507). When an obstacle is detected by the sensing unit 112 during driving (S508 "Yes"), a local path search to avoid the detected obstacle can be performed, thereby performing an evasive maneuver (S509). In some cases, based on the evasive maneuver or the failure of the evasive maneuver, the control device 140 can update the corresponding AMR's task.

[0082] Furthermore, during the journey of the AMR until it reaches its destination, the position error during the movement can be corrected using the aforementioned mileage measurement method (S510).

[0083] Then, upon reaching the destination (S511), the AMR can perform task-based maneuvers (S512). For example, the AMR can determine whether the conditions for entering a specific process area are met, retrieve an empty pallet from the destination, or unload the load loaded on the loading unit 113.

[0084] In an exemplary embodiment of the present invention, the objective is to predetermine whether the destination is accessible when the intelligent logistics vehicle moves from the starting point to the selected destination.

[0085] In the following text, reference will be made to Figure 6 The operation of the control device 140 according to an exemplary embodiment of the present invention is described.

[0086] Figure 6 This is a block diagram illustrating the operation of a control device according to an exemplary embodiment of the present invention.

[0087] Reference Figure 6According to an exemplary embodiment of the present invention, the control device 140 may include a communication unit 146, a map management unit 148, and a route selection unit 149. Figure 6 The components primarily shown are those related to exemplary embodiments of the present invention, and in implementing the actual control device 140, as described above... Figure 2 As described above, it can obviously include more components.

[0088] Furthermore, for ease of explanation, Figure 6 The description covers the scenario of setting up one control device 140 and one intelligent logistics vehicle 110, but it should be understood that this also applies to the scenario of setting up multiple intelligent logistics vehicles and multiple control devices.

[0089] The components will be described below.

[0090] First, the communication unit 146 can communicate with at least one intelligent logistics vehicle 110 located within the operating range 100. Specifically, the communication unit 146 can communicate with the communication unit 114 of at least one intelligent logistics vehicle 110 to receive information including the location of the at least one intelligent logistics vehicle 110 and whether it is performing a task. Furthermore, the communication unit 146 can send information generated by the control device 140 to the communication unit 114 of the at least one intelligent logistics vehicle 110.

[0091] The map management unit 148 can set a destination confirmation location for at least one interval within the operating range. In this case, the destination confirmation location can be a location where at least one intelligent logistics vehicle 110 can determine whether a destination is accessible while in motion. For example, the destination confirmation location can be a location used to determine whether multiple candidate destinations related to the task currently assigned to at least one intelligent logistics vehicle 110 are accessible; in this case, the destination confirmation location can be set to correspond to multiple candidate destinations. However, this is exemplary and not necessarily limited to this.

[0092] Furthermore, the destination confirmation location can be set to correspond to at least one node, area, and lane existing on the movement path of at least one intelligent logistics vehicle 110. That is, the map management unit 148 can set a destination confirmation location consisting of at least one node, area, and lane for at least a portion of the operating range.

[0093] In addition, the map management unit 148 can provide the route selection unit 149 with information about the confirmed location of the set destination.

[0094] The route selection unit 149 can control at least one intelligent logistics vehicle 110 to move toward the destination location.

[0095] Specifically, the route selection unit 149 can collect information about the current location of at least one intelligent logistics vehicle 110, set the current location as the starting point, and generate a movement path from the starting point to the destination confirmation location set by the map management unit 148 based on the collected information. However, this is exemplary and not necessarily limited to this. For example, the route selection unit 149 can generate a movement path connecting the starting point and the destination by setting the current location of at least one intelligent logistics vehicle 110 as the starting point and setting multiple candidate destinations related to the task of at least one intelligent logistics vehicle 110 as the destination. In this case, the destination confirmation location set by the map management unit 148 can be taken into account when generating the movement path, such that the destination confirmation location is formed on the movement path.

[0096] The route selection unit 149 can send the generated movement route to the communication unit 114 of at least one intelligent logistics vehicle 110. For example, it can send information about multiple waypoints included in the movement route to the communication unit 114 of at least one intelligent logistics vehicle 110. At least one intelligent logistics vehicle 110 can move from its starting point to its destination confirmation location based on the received information about the multiple waypoints. However, this is exemplary and not necessarily limited to this.

[0097] At least one intelligent logistics vehicle 110 can move from a starting point to a destination confirmation location while identifying multiple waypoints. Specifically, the route selection unit 149 according to an exemplary embodiment of the invention can determine whether at least one of a plurality of candidate destinations is accessible when at least one intelligent logistics vehicle 110 enters the destination confirmation location during its movement, and can set the accessible candidate destination from the plurality of candidate destinations as the final destination. This will refer to... Figure 7 Provide a detailed description.

[0098] Figure 7 This is a schematic diagram illustrating the determination of candidate destinations for intelligent logistics vehicles according to an exemplary embodiment of the present invention.

[0099] Reference Figure 7 Virtual lanes (e.g., lanes) can be set within an operating range of 100, and the path selection unit 149 can generate a movement path based on the virtual lanes (lanes). Figure 7 In this example, it is assumed that a movement path for a recycling task of any smart logistics vehicle 110 has been generated. However, this is exemplary and not necessarily limited to this. Furthermore, in Figure 7 In this example, we assume that the destination confirmation part is formed by a single node, but this is just an example and it can obviously be formed based on areas on the movement path or based on lanes.

[0100] The following can describe a smart logistics vehicle 110, but this also applies to each of the at least one smart logistics vehicle provided within the operating range 100.

[0101] Reference Figure 7 The intelligent logistics vehicle 110 can move along a pre-generated movement path to a destination confirmation location corresponding to multiple candidate destinations (e.g., CP1, CP2, CP3). While moving along the movement path, the intelligent logistics vehicle 110 can periodically send its own location to the control device 140, and the map management unit 148 can determine whether the intelligent logistics vehicle 110 has moved to a destination confirmation location that exists as a node on the movement path. When the intelligent logistics vehicle 110 moves to a destination confirmation location, the path selection unit 149 can control the intelligent logistics vehicle 110 to temporarily stop at the destination confirmation location, and can perform the content described later during the temporary stop.

[0102] Meanwhile, multiple smart logistics vehicles can move along the same path within an operating range of 100, and these vehicles may temporarily stop along the path once they reach the destination confirmation location. Therefore, multiple smart logistics vehicles may occupy the destination confirmation location, causing a stalemate with other smart logistics vehicles subsequently attempting to reach it.

[0103] Therefore, the path selection unit 149 can determine the occupancy status of the destination confirmation location by the intelligent logistics vehicle 110, thereby determining whether the destination confirmation location is accessible. When the destination confirmation location is accessible, the path selection unit 149 can direct the intelligent logistics vehicle 110 to travel along the movement path to enter the destination confirmation location. On the other hand, when the destination confirmation location is inaccessible, the path selection unit 149 can direct the intelligent logistics vehicle 110 to perform a detour task nearby. When the destination confirmation location becomes accessible again, the path selection unit 149 can direct the intelligent logistics vehicle 110 to stop the detour task and re-enter the destination confirmation location. However, this is exemplary and not necessarily limited to this.

[0104] When the intelligent logistics vehicle 110 is determined to have entered the confirmed destination location, the route selection unit 149 can collect information about multiple candidate destinations (CP1, CP2, CP3). In this case, the route selection unit 149 can, for example, […]. Figure 6The production device 120 or monitoring device 130, located within the operating range 100, collects information about multiple candidate destinations (CP1, CP2, CP3). The production device 120 can provide status information about the multiple candidate destinations (CP1, CP2, CP3), and the monitoring device 130 can provide sensing information from sensors located at the multiple candidate destinations (CP1, CP2, CP3). However, this is exemplary and not necessarily limited to this.

[0105] The route selection unit 149 can determine whether at least one of the multiple candidate destinations (CP1, CP2, CP3) is accessible based on information about the multiple candidate destinations (CP1, CP2, CP3). For example, based on information about the multiple candidate destinations (CP1, CP2, CP3), when at least one of the multiple candidate destinations (CP1, CP2, CP3) (e.g., CP1) is occupied by another smart logistics vehicle, or when at least one of the multiple candidate destinations (CP1, CP2, CP3) (e.g., CP1) becomes disabled, the corresponding candidate destination can be determined to be inaccessible. However, this is exemplary and not necessarily limited to this.

[0106] Furthermore, when at least one candidate destination is determined to be inaccessible, the route selection unit 149 can set an accessible candidate destination (CP1, CP2, CP3) from among multiple candidate destinations as the final destination.

[0107] For example, among multiple candidate destinations (CP1, CP2, CP3), besides the inaccessible candidate destinations, there may be multiple accessible candidate destinations. In this case, the route selection unit 149 can determine information about the accessible candidate destinations (e.g., CP2, CP3). The multiple candidate destinations (CP1, CP2, CP3) may be destinations related to the task of the intelligent logistics vehicle 110. In order to perform the task assigned to the intelligent logistics vehicle 110, information about the accessible candidate destinations (e.g., CP2, CP3) among the multiple candidate destinations (CP1, CP2, CP3) related to the task can be determined. In this case, the route selection unit 149 can determine the information about the accessible candidate destinations (e.g., CP2, CP3) based on previously collected information about the multiple candidate destinations (CP1, CP2, CP3).

[0108] Furthermore, the route selection unit 149 can set any one of the candidate destinations (CP2, CP3) (e.g., CP2) as the final destination based on the determined information.

[0109] Subsequently, the path selection unit 149 can generate a movement path from the current location of the intelligent logistics vehicle 110 to an accessible candidate destination (e.g., CP2) and send the generated movement path to the intelligent logistics vehicle 110. In this way, the path selection unit 149 can enable the intelligent logistics vehicle 110 to move along the generated movement path and can control the intelligent logistics vehicle 110 to smoothly perform the assigned tasks.

[0110] In the following text, references to the above will be used as a basis. Figures 6 to 7 The configuration and operation of the control device 140, and reference Figure 8 An intelligent logistics vehicle control method according to an exemplary embodiment of the present invention will be described.

[0111] Figure 8 This is a schematic diagram illustrating an intelligent logistics vehicle control method according to an exemplary embodiment of the present invention.

[0112] Reference Figure 8 The map management unit 148 can set destination confirmation locations corresponding to multiple candidate destinations of the intelligent logistics vehicle 110 for some sections within the operating range 100 (S801). In addition, the map management unit 148 can send information about the set destination confirmation locations to the route selection unit 149 (S802).

[0113] The path selection unit 149 can receive information about the current location of the intelligent logistics vehicle 110 from the communication unit 114 of the intelligent logistics vehicle 110 (S803-1, S803-2). In addition, the path selection unit 149 can set the current location of the intelligent logistics vehicle 110 as the starting point based on the received information, and can generate a movement path from the starting point to the destination location (S804).

[0114] The path selection unit 149 can send information about the generated movement path to the communication unit 114 (S805-1) of the intelligent logistics vehicle 110. The communication unit 114 can send the information to the control unit 115 (S805-2), and the control unit 115 can control the intelligent logistics vehicle 110 to move along the movement path.

[0115] When the intelligent logistics vehicle 110 moves, it can periodically provide its current location to the communication unit 146 (S806-1), and the communication unit 146 can provide the current location to the map management unit 148 (S806-2). Based on this, the map management unit 148 can determine whether the intelligent logistics vehicle 110 has entered the destination confirmation location set on the movement path (S807). When it is determined that the intelligent logistics vehicle 110 has entered the destination confirmation location, the map management unit 148 can send the determination result to the route selection unit 149 (S808).

[0116] In addition, when the intelligent logistics vehicle 110 enters the destination confirmation location, the route selection unit 149 can receive status information about multiple candidate destinations from the production device 120 (S809-1, S809-2), or receive sensing information from sensors installed at multiple candidate destinations from the monitoring device 130 (S810-1, S810-2).

[0117] The route selection unit 149 can determine whether at least one of a plurality of candidate destinations is accessible based on information sent through the production device 120 and the monitoring device 130, thereby determining an accessible candidate destination (S811). The route selection unit 149 can set the accessible candidate destination as the final destination and generate a movement path connecting the starting point and the destination by setting the current position of the intelligent logistics vehicle 110 as the starting point and the final destination as the destination (S812).

[0118] Furthermore, the route selection unit 149 can send the generated movement path to the communication unit 114 of the intelligent logistics vehicle 110 (S813-1), and the communication unit 114 can send it to the control unit 115 (S813-2). The control unit 115 can control the intelligent logistics vehicle 110 to move to an accessible candidate destination based on the received movement path.

[0119] As described above, when a predetermined destination becomes inaccessible due to a change in its state, the intelligent logistics vehicle control method and control device according to an exemplary embodiment of the present invention can change the destination to an accessible destination among other destinations that can perform the same task, thereby smoothly performing the task previously assigned to the intelligent logistics vehicle.

[0120] Although specific exemplary embodiments of the invention have been illustrated and described, it will be apparent to those skilled in the art that the invention can be modified and altered in various ways without departing from the technical spirit of the invention as provided in the appended claims.

[0121] The present invention described above can be implemented as computer-readable code on a medium on which a program is recorded. A computer-readable medium can include all types of recording devices storing data that can be read by a computer system. Examples of computer-readable media include hard disk drives (HDDs), solid-state drives (SSDs), silicon disk drives (SDDs), ROMs, RAMs, CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, etc. Therefore, the detailed description above should not be construed as limiting in any way, but should be considered exemplary. The scope of the invention should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the invention are included within the scope of the invention.

[0122] Explanation of reference numerals in the attached figures: 100: Smart Factory 110: Intelligent Logistics Vehicles 120: Production unit 130: Monitoring device 140: Control device

Claims

1. A method of controlling an intelligent logistics vehicle, the method comprising: controlling at least one intelligent logistics vehicle to move to a destination confirmation location corresponding to a plurality of candidate destinations related to a currently assigned task; while the at least one intelligent logistics vehicle is moving, determining whether at least one of the plurality of candidate destinations is accessible in response to entering the destination confirmation location; setting an accessible candidate destination of the plurality of candidate destinations as a final destination.

2. The method of claim 1, wherein, controlling comprises: collecting information about a current location of the at least one intelligent logistics vehicle; generating a movement path from a departure point corresponding to the current location to the destination confirmation location based on the collected information; controlling the at least one intelligent logistics vehicle to move to the destination confirmation location based on the generated movement path.

3. The method of claim 1, wherein, the destination confirmation location is predetermined to correspond to at least one of a node, a zone, and a lane existing on a path of movement of the at least one intelligent logistics vehicle.

4. The method of claim 1, wherein, determining comprises: while the at least one intelligent logistics vehicle is moving, determining whether the destination confirmation location is accessible; in response to the destination confirmation location being accessible, causing the at least one intelligent logistics vehicle to enter the destination confirmation location, thereby determining whether at least one of the plurality of candidate destinations is accessible.

5. The method of claim 4, wherein, determining whether at least one of the candidate destinations is accessible comprises: in response to the destination confirmation location being inaccessible, controlling the at least one intelligent logistics vehicle to perform a detour task; while the at least one intelligent logistics vehicle is performing the detour task, in response to the destination confirmation location becoming accessible, causing the at least one intelligent logistics vehicle to stop the detour task and enter the destination confirmation location, thereby determining whether at least one of the plurality of candidate destinations is accessible.

6. The method of claim 1, wherein, determining comprises: in response to entering the destination confirmation location, collecting information about the plurality of candidate destinations; determining whether at least one of the plurality of candidate destinations is accessible based on the collected information.

7. The method of claim 6, wherein, collecting comprises: in response to entering the destination confirmation location, collecting information about the plurality of candidate destinations through a sensor provided in each of the plurality of candidate destinations.

8. The method of claim 1, wherein, determining comprises: in response to another intelligent logistics vehicle being located in at least one of the plurality of candidate destinations, or in response to at least one of the plurality of candidate destinations becoming in an inactivated state, determining that the corresponding candidate destination is inaccessible.

9. The method of claim 1, wherein, setting comprises: in response to a plurality of accessible candidate destinations existing, setting one of the plurality of accessible candidate destinations as the final destination. 10.The method of claim 1, further comprising: after the setting, generating a movement path from a current location of the at least one intelligent logistics vehicle to the final destination; controlling the at least one intelligent logistics vehicle to move along the generated movement path. 11.A control apparatus, the apparatus comprising: a communication unit configured to communicate with at least one intelligent logistics vehicle; and a processor configured to: control the at least one intelligent logistics vehicle to move to a destination confirmation location corresponding to a plurality of candidate destinations related to a currently assigned task; while the at least one intelligent logistics vehicle is moving, determine whether at least one of the plurality of candidate destinations is accessible in response to entering the destination confirmation location; set an accessible candidate destination of the plurality of candidate destinations as a final destination. The path selection unit is configured to: control at least one intelligent logistics vehicle to move to a destination confirmation location corresponding to a plurality of candidate destinations related to the currently assigned task; determine whether at least one candidate destination in the plurality of candidate destinations is accessible in response to entering the destination confirmation location while the at least one intelligent logistics vehicle is moving; and set an accessible candidate destination in the plurality of candidate destinations as a final destination.

12. The apparatus of claim 11, wherein, The path selection unit is further configured to: collect information about a current position of the at least one intelligent logistics vehicle; generate a movement path from a departure point corresponding to the current position to the destination confirmation location based on the collected information; control the at least one intelligent logistics vehicle to move to the destination confirmation location based on the generated movement path.

13. The apparatus of claim 11, wherein, The path selection unit is further configured to: determine whether the destination confirmation location is accessible while the at least one intelligent logistics vehicle is moving; in response to the destination confirmation location being accessible, cause the at least one intelligent logistics vehicle to enter the destination confirmation location, thereby determining whether at least one candidate destination in the plurality of candidate destinations is accessible.

14. The apparatus of claim 13, wherein, The path selection unit is further configured to: in response to the destination confirmation location being inaccessible, control the at least one intelligent logistics vehicle to perform a detour task; in response to the destination confirmation location becoming accessible while the at least one intelligent logistics vehicle is performing the detour task, cause the at least one intelligent logistics vehicle to stop the detour task and enter the destination confirmation location, thereby determining whether at least one candidate destination in the plurality of candidate destinations is accessible.

15. The apparatus of claim 11, wherein, The path selection unit is further configured to: collect information about the plurality of candidate destinations in response to the at least one intelligent logistics vehicle entering the destination confirmation location; determine whether at least one candidate destination in the plurality of candidate destinations is accessible based on the collected information.

16. The apparatus of claim 15, wherein, The path selection unit is further configured to: collect information about the plurality of candidate destinations through sensors arranged at each of the plurality of candidate destinations in response to the at least one intelligent logistics vehicle entering the destination confirmation location.

17. The apparatus of claim 11, wherein, The path selection unit is further configured to determine that a corresponding candidate destination is inaccessible in response to another intelligent logistics vehicle being located at at least one candidate destination in the plurality of candidate destinations, or in response to at least one candidate destination in the plurality of candidate destinations becoming a disabled state.

18. The apparatus of claim 11, wherein, The path selection unit is further configured to set one accessible candidate destination in the plurality of accessible candidate destinations as the final destination in response to there being a plurality of accessible candidate destinations.

19. The apparatus of claim 11, wherein, The path selection unit is further configured to: generate a movement path from a current position of the at least one intelligent logistics vehicle to the final destination in response to the final destination being set; control the at least one intelligent logistics vehicle to move along the generated movement path.

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