Mobile robot for inventory management of warehouse, inventory management system including same, and inventory management method of warehouse using same

Abstract

Provided are a mobile robot for inventory management of a warehouse, an inventory management system including the same, and an inventory management method of a warehouse using the same. A mobile robot for inventory management of a warehouse according to an embodiment disclosed herein is disposed in a warehouse, and comprises: a crane module which has a multi-stage structure and can be adjusted in height by sliding in a vertical direction; a sensor module which collects sensor data by scanning a predetermined space in the warehouse; and a control module which obtains logistics information by analyzing the sensor data collected from the sensor module, wherein the sensor module includes a plurality of first sensors installed in at least a portion of the crane module and installed in the left and right directions of the mobile robot for inventory management, and a plurality of second sensors installed in at least a portion of the mobile robot for inventory management and installed in the front and rear directions of the mobile robot for inventory management.

Description

Mobile inventory verification robot for inventory management in a logistics warehouse, an inventory management system including the same, and a method for managing inventory in a logistics warehouse using the same

[0001] The present disclosure relates to a mobile inventory verification robot for inventory management in a logistics warehouse, an inventory management system including the same, and a method for managing inventory in a logistics warehouse using the same.

[0002] Inventory management in logistics warehouses is a critical factor for improving productivity and efficiency in the logistics industry. However, due to various problems with current inventory management methods, the need for digital transformation (DX) is emerging.

[0003] First, problems caused by human error are arising. Warehouse inventory management tends to rely heavily on manpower, leading to reduced work efficiency and frequent picking errors. For example, if inventory is missing or mishandled during logistics inspection, it not only results in inventory loss but also delays the flow of the entire logistics process, potentially causing financial losses. Furthermore, lead times are increasing due to the use of forklifts and manual movement by workers, and errors by personnel can cause mismatches between logistics and shelves.

[0004] Second, there are significant limitations on data accessibility. Current logistics management software, such as Warehouse Management Systems (WMS), is manager-centric, preventing field workers from accessing the systems or data. Furthermore, the majority of warehouse management systems are composed of and managed solely through handwritten documents and text-based information. This can lead to communication barriers due to the increasing number of foreign workers, and the reliance on phone calls and emails hinders the smooth sharing of real-time information. Additionally, the absence of a unified IoT monitoring platform makes it difficult to manage all data in an integrated manner.

[0005] Third, there is a problem regarding limitations on data collection within the logistics warehouse. Because it is difficult to effectively collect real-time location and inventory information, workers currently collect this data manually using devices such as handwritten notebooks or PDAs. This process of readjusting logistics location data related to inbound and outbound operations consumes time and costs. In particular, within diverse warehouse environments utilizing high racks, flat racks, and carts, accurately determining the location and quantity of inventory in real time by relying solely on worker proficiency inevitably entails significant human resources and human error. Furthermore, if the system fails to immediately verify inventory quantities, there is a limitation in effectively monitoring the on-site utilization rate of shelf-stacking items.

[0006] Finally, high initial implementation costs act as another constraint. The initial facility setup costs for introducing new logistics solutions, including existing systems, equipment, sensors, and robots, are substantial, leading to issues regarding ROI (cost efficiency). Difficulties in integrating new and existing systems may result in additional personnel and costs, and retraining issues arise due to changes in warehouse processes.

[0007] To solve these problems, there is a need for a method to perform efficient and accurate inventory management within the warehouse.

[0008] The aforementioned background technology is one that the inventor possessed or acquired in the process of deriving the content of the present disclosure, and it cannot be considered as prior art disclosed to the general public prior to the filing of this application.

[0009] The problem that the present disclosure aims to solve is to provide a mobile inventory verification robot for inventory management in a logistics warehouse, an inventory management system including the same, and a method for managing inventory in a logistics warehouse using the same, which can reduce the significant human resources and various errors (e.g., human error) inevitably occurring during inventory management and enable more accurate and convenient inventory management by deploying an AI-based mobile inventory verification robot within a logistics warehouse and automatically performing inventory management by collecting, analyzing, and recognizing logistics information based on sensor data collected during the autonomous control of the mobile inventory verification robot.

[0010] The problems that this disclosure aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by a person skilled in the art from the description below.

[0011] A mobile inventory verification robot for inventory management in a logistics warehouse according to one embodiment of the present disclosure for solving the above-mentioned problem may be deployed within the logistics warehouse. In various embodiments, the mobile inventory verification robot includes a sensor module that collects sensor data by scanning a predetermined space within the logistics warehouse and a control module that obtains logistics information by analyzing the sensor data collected from the sensor module. The sensor module may include a plurality of first sensors installed in at least a part of the crane module and installed in the left-right direction of the mobile inventory verification robot, and a plurality of second sensors installed in at least a part of the mobile inventory verification robot and installed in the front-rear direction of the mobile inventory verification robot.

[0012] In various embodiments, the plurality of first sensors are installed on the left and right sides of the crane module, respectively, based on the driving direction of the mobile inventory inspection robot, so that sensor data corresponding to the left direction of the mobile inventory inspection robot and sensor data corresponding to the right direction of the mobile inventory inspection robot can be collected.

[0013] In various embodiments, the crane module includes a plurality of sliding units, and each of the plurality of sliding units includes a pair of frames extending parallel to each other spaced apart, and can be installed overlapping each other so as to be slidable in the vertical direction.

[0014] In various embodiments, the plurality of first sensors may be installed in each of the plurality of sliding units.

[0015] In various embodiments, the control module identifies a rack placed near the mobile inventory inspection robot based on sensor data collected from the plurality of second sensors, and moves the plurality of sliding units in an up-and-down direction so that the height of the crane module matches the height of the identified rack, while adjusting the position of the plurality of sliding units so that the spacing between the plurality of first sensors becomes equal.

[0016] In various embodiments, the control module can acquire logistics information using a plurality of sensor data collected from the plurality of first sensors when the interval between the plurality of first sensors is greater than or equal to the reference interval, and can acquire logistics information using only at least one sensor data collected from at least one of the plurality of first sensors when the interval between the plurality of first sensors is less than the reference interval.

[0017] In various embodiments, the sensor data collected from the plurality of first sensors includes first sensor data corresponding to the left direction of the mobile inventory inspection robot located at a specific point and second sensor data corresponding to the right direction of the mobile inventory inspection robot located at the specific point, and the control module identifies a first rack placed to the left of the mobile inventory inspection robot based on the first sensor data and identifies a second rack placed to the right of the mobile inventory inspection robot based on the second sensor data, wherein if the heights of the identified first rack and the identified second rack are different, the height of the crane module can be adjusted based on the rack with the higher height among the identified first rack and the identified second rack.

[0018] In various embodiments, the control module identifies a rack placed near the mobile inventory inspection robot based on sensor data collected from the plurality of second sensors, determines the number of sliding units to be moved in the vertical direction based on the height of the identified rack, and selects a sliding unit corresponding to the determined number among the plurality of sliding units to be moved in the vertical direction.

[0019] In various embodiments, when a rack placed near the mobile inventory inspection robot is identified based on sensor data collected from the plurality of second sensors, the control module moves the plurality of sliding units in an up-and-down direction so that the height of the crane module matches the height of the identified rack; and when the identified rack includes a plurality of shelves, determines the position of each of the plurality of sliding units so that the position of the plurality of second sensors matches the position of each of the plurality of shelves, and moves each of the plurality of sliding units to the determined position.

[0020] In various embodiments, each of the plurality of first sensors may include a high-resolution camera that collects image data as it scans the left and right areas of the mobile inventory inspection robot, and each of the plurality of second sensors may include a LiDAR sensor that collects point cloud data as it scans the front and rear areas of the mobile inventory inspection robot.

[0021] In various embodiments, the control module determines the height of the crane module at a specific point as the second height when the similarity between sensor data collected from the plurality of second sensors when the height of the crane module at a specific point is the first height and sensor data collected from the plurality of second sensors when the height of the crane module at a specific point is the second height is less than a threshold similarity, and determines the height of the crane module at the specific point as the first height when the similarity between sensor data collected from the plurality of second sensors when the height of the crane module at a specific point is the first height and sensor data collected from the plurality of second sensors when the height of the crane module at a specific point is the second height is greater than or equal to the threshold similarity.

[0022] In various embodiments, when the mobile inventory inspection robot is located at a specific point, the control module calculates the height of a rack placed near the specific point based on sensor data collected from the plurality of second sensors at the specific point, and can adjust the height of the crane module in the up and down direction so that the height of the crane module matches the calculated height.

[0023] An inventory management system for a logistics warehouse using a mobile inventory verification robot according to another embodiment of the present disclosure for solving the above-mentioned problem comprises a mobile inventory verification robot placed in a logistics warehouse, comprising a sensor module that collects sensor data by scanning a predetermined space within the logistics warehouse and a control module that obtains logistics information by analyzing the sensor data collected from the sensor module, and a logistics management server that generates logistics data using the logistics information obtained from the control module and performs inventory management for the logistics warehouse using the generated logistics data, wherein the sensor module may include a plurality of first sensors installed on a crane module that has a multi-stage structure and can be height-adjustable by sliding in the up-and-down direction, and a plurality of second sensors installed on the front and rear sides of the mobile inventory verification robot.

[0024] A method for managing inventory in a logistics warehouse using a mobile inventory verification robot according to another embodiment of the present disclosure for solving the above-described problem is a method performed through an inventory management system including a mobile inventory verification robot and a logistics management server, comprising: a step of collecting sensor data by scanning a predetermined space within the logistics warehouse through a sensor module included in the mobile inventory verification robot; a step of obtaining logistics information by analyzing the collected sensor data through a control module included in the mobile inventory verification robot; and a step of generating logistics data using the obtained logistics information through the logistics management server and performing inventory management for the logistics warehouse using the generated logistics data, wherein the step of collecting sensor data may include a step of adjusting the height of a crane module on which the sensor module is installed according to the height of a rack placed near the mobile inventory verification robot.

[0025] Other specific details of the present disclosure are included in the detailed description and drawings.

[0026] According to various embodiments of the present disclosure, by deploying an AI-based mobile inventory verification robot within a logistics warehouse and automatically performing inventory management by collecting, analyzing, and recognizing logistics information based on sensor data collected during the autonomous driving control of the mobile inventory verification robot, there is an advantage of reducing the significant human resources and various errors (e.g., human error) that inevitably occur during the inventory management process, and enabling more accurate and convenient inventory management.

[0027] The effects of the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art from the description below.

[0028] The following drawings attached to this specification illustrate preferred embodiments of the present disclosure and serve to further enhance understanding of the technical concept of the present disclosure together with the detailed description of the invention; therefore, the present disclosure should not be interpreted as being limited only to the matters described in such drawings.

[0029] FIG. 1 is a drawing illustrating a logistics management system of a logistics warehouse according to one embodiment of the present disclosure.

[0030] FIG. 2 is a diagram illustrating the data flow in the process of a logistics management system performing inventory management using a mobile inventory verification robot in various embodiments.

[0031] FIGS. 3 to 9 are drawings illustrating a mobile inventory inspection robot according to various embodiments of the present disclosure.

[0032] FIGS. 10 and 11 are drawings illustrating the process of collecting sensor data by adjusting the height of the structure of a mobile inventory inspection robot according to the height of the rack in various embodiments.

[0033] FIGS. 12 to 18 are drawings illustrating sensor data and the results of analyzing the sensor data in various embodiments.

[0034] FIGS. 19 to 24 are drawings illustrating, in various embodiments, an exemplary user interface (UI) of a logistics management platform operated in a logistics management system.

[0035] FIG. 25 is a flowchart of an inventory management method for a logistics warehouse using a mobile inventory verification robot according to another embodiment of the present disclosure.

[0036] FIG. 26 is a flowchart of a method for performing logistics management using logistics information extracted through a two-step analysis of sensor data in various embodiments.

[0037] FIG. 27 is a diagram illustrating the process of a logistics management system performing inventory management using a mobile inventory verification robot in various embodiments.

[0038] FIG. 28 is a diagram illustrating the hardware configuration of a control module included in a mobile inventory inspection robot according to another embodiment of the present disclosure.

[0039] The advantages and features of the present disclosure and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure is complete and to fully inform those skilled in the art of the scope of the present disclosure, and the present disclosure is defined only by the scope of the claims.

[0040] The terms used herein are for describing the embodiments and are not intended to limit the disclosure. In this specification, the singular form includes the plural form unless specifically stated otherwise in the text. As used herein, "comprises" and / or "comprising" do not exclude the presence or addition of one or more other components in addition to the components mentioned.

[0041] Throughout this specification, the same reference numerals refer to the same components, and "and / or" includes each of the mentioned components and all combinations of one or more thereof. Although terms such as "first," "second," etc., are used to describe various components, they are not limited by these terms. These terms are used merely to distinguish one component from another. Accordingly, the first component mentioned below may be the second component within the technical scope of this disclosure.

[0042] As used herein, the terms “part” or “module” refer to hardware components such as software, FPGAs, or ASICs, and the “part” or “module” performs certain roles. However, the “part” or “module” is not limited to software or hardware. The “part” or “module” may be configured to reside in an addressable storage medium or configured to run on one or more processors. Thus, by example, the “part” or “module” includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and “parts” or “modules” may be combined into a smaller number of components and “parts” or “modules,” or further separated into additional components and “parts” or “modules.”

[0043] Spatially relative terms such as "below," "beneath," "lower," "above," and "upper" may be used to facilitate the description of the relationship between one component and other components as illustrated in the drawings. Spatially relative terms should be understood as encompassing different orientations of components during use or operation, in addition to the orientations depicted in the drawings. For example, if a component depicted in a drawing is inverted, a component described as "below" or "beneath" of another component may be placed "above" of that component. Therefore, the exemplary term "below" may encompass both the lower and upper directions. Components may also be oriented in other directions, and accordingly, spatially relative terms may be interpreted according to the orientation.

[0044] Expressions such as "first," "second," or "first," "second" as used in this specification are used to distinguish one object from another when referring to a plurality of objects of the same kind, unless otherwise indicated by the context, and do not limit the order or importance of said objects.

[0045] Expressions used herein such as “A, B, and C,” “A, B, or C,” “A, B, and / or C,” or “at least one of A, B, and C,” “at least one of A, B, or C,” “at least one of A, B, and / or C,” “at least one selected from A, B, and C,” “at least one selected from A, B, or C,” “at least one selected from A, B, and / or C,” etc., may mean each of the listed items or all possible combinations of the listed items. For example, “at least one selected from A and B” may refer to (1) A, (2) at least one of A, (3) B, (4) at least one of B, (5) at least one of A and at least one of B, (6) at least one of A and B, (7) at least one of B and A, and (8) all of A and B.

[0046] As used herein, the expression “based on” is used to describe one or more factors affecting an act or action of a decision or judgment described in the phrase or sentence containing such expression, and such expression does not exclude additional factors affecting said act or action of a decision or judgment.

[0047] As used in this specification, the expression that a certain component (e.g., a first component) is "connected" or "connected" to another component (e.g., a second component) may mean that the said certain component is not only directly connected or connected to the said other component, but is also connected or connected through a new other component (e.g., a third component).

[0048] As used herein, the expression "configured to" may have meanings such as "set to," "capable of," "modified to," "made to," or "capable of." Such expression is not limited to the meaning of "specifically designed in hardware," and, for example, a processor configured to perform a specific operation may mean a generic-purpose processor capable of performing that specific operation by executing software.

[0049] Unless otherwise defined, all terms used herein (including technical and scientific terms) may be used in a meaning commonly understood by those skilled in the art to which this disclosure pertains. Additionally, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise.

[0050] In this specification, the term "computer" refers to any type of hardware device comprising at least one processor, and may be understood to include software configurations operating on said hardware device according to the embodiments. For example, the term "computer" may be understood to include smartphones, tablet PCs, desktops, laptops, and user clients and applications running on each of these devices, but is not limited thereto.

[0051] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0052] Each step described in this specification is described as being performed by a computer, but the subject of each step is not limited thereto, and depending on the embodiment, at least some of each step may be performed on different devices.

[0053]

[0054] FIG. 1 is a drawing illustrating a logistics management system of a logistics warehouse according to one embodiment of the present disclosure, and FIG. 2 is a drawing illustrating a data flow in the process of a logistics management system performing inventory management using a mobile inventory verification robot in various embodiments.

[0055] Additionally, FIGS. 3 to 9 are drawings illustrating a mobile inventory inspection robot according to various embodiments of the present disclosure, and FIGS. 10 and 11 are drawings illustrating a process of collecting sensor data by adjusting the height of the structure of the mobile inventory inspection robot according to the height of the rack in various embodiments.

[0056] Referring to FIGS. 1 to 11, the logistics management system of a logistics warehouse may include a mobile inventory inspection robot (100), a user terminal (200), a logistics management server (300), and a network (400).

[0057] Here, the inventory management system of a logistics warehouse illustrated in FIGS. 1 to 11 is according to one embodiment, and its components are not limited to the embodiment illustrated in FIGS. 1 to 11 and may be added, changed, or deleted as needed.

[0058] For example, the inventory management system of a logistics warehouse may further include an external server (e.g., an external storage server) that stores and manages logistics information obtained from a mobile inventory verification robot (100) and logistics data generated from a logistics management server (300), but is not limited thereto.

[0059] In one embodiment, the mobile inventory inspection robot (100) may be placed within a logistics warehouse and may autonomously drive within the logistics warehouse according to control commands obtained from the outside (e.g., control commands obtained from a logistics management server (300) and / or a user terminal (200)), and may perform various operations for inventory inspection while autonomously driving within the logistics warehouse. To this end, the mobile inventory inspection robot (100) may include a sensor module (110), a crane module (120), and a control module (130).

[0060] In various embodiments, the sensor module (110) can collect sensor data as it scans a predetermined space within a logistics warehouse.

[0061] In various embodiments, the sensor module (110) may include a first sensor (111) and a second sensor (112).

[0062] First, the first sensor (111) is installed on the left and right sides of the mobile inventory inspection robot (100), and can collect sensor data for the left and right sides as it scans the left and right sides of the mobile inventory inspection robot (100).

[0063] Here, the first sensor (111) may be a vision sensor, i.e., a high-resolution camera, and the sensor data collected from the first sensor may be a high-resolution image (e.g., FIG. 12 to FIG. 15), but is not limited thereto.

[0064] At this time, the sensor module (110) may further include an image capturing light (113) so as to be able to acquire high-resolution images even in an environment with low illumination (e.g., at night or when the lights are off). This light (113) may be installed in a location adjacent to the first sensor (111), but is not limited thereto.

[0065] Here, it can be implemented so that one logistics pallet is photographed per high-resolution camera to generate a high-resolution image for each logistics pallet, but is not limited thereto.

[0066] Here, when shape information of the logistics is extracted from a high-resolution image collected through the first sensor (111), the position information of the mobile inventory inspection robot (100) collected through the position sensor included in the sensor module (110) can be utilized to match and store the position (row, column) of the shelf corresponding to the shape information of the logistics and the high-resolution image.

[0067] Next, the second sensor (112) can be installed on the front and rear sides of the mobile inventory inspection robot (100), and can collect sensor data for the front and rear areas by scanning the front and rear areas of the mobile inventory inspection robot (100).

[0068] Here, the second sensor (112) may be a LiDAR sensor, and the data collected through the second sensor (112) may be point cloud data corresponding to the front and rear areas (e.g., FIGS. 16 to 18), but is not limited thereto.

[0069] At this time, the second sensor (112) is installed on the front and rear sides of the mobile inventory inspection robot (100) so that it can collect point cloud data corresponding to the front and rear areas of the mobile inventory inspection robot (100), but is not limited thereto and may be point cloud data corresponding to the surrounding 360-degree directions of the mobile inventory inspection robot (100).

[0070] For example, the mobile inventory inspection robot (100) may have a structure that can rotate 360 ​​degrees, and the point cloud data collected through the second sensor (112) may be point cloud data collected while the mobile inventory inspection robot (100) is rotating 360 degrees, that is, point cloud data corresponding to a 360-degree range in the horizontal direction with respect to the ground.

[0071] As another example, since the second sensor (112) itself is implemented in a form that can rotate 360 ​​degrees, the point cloud data collected through the second sensor (112) may be point cloud data corresponding to a 360-degree range in a direction vertical to the ground.

[0072] Here, when shape information of logistics is extracted from point cloud data collected through the second sensor (112), the position information of the mobile inventory inspection robot (100) collected through the position sensor included in the sensor module (110) can be utilized to match and store the position (row, column) of the shelf corresponding to the shape information of logistics and the point cloud data.

[0073] In various embodiments, the sensor module (110) may include a plurality of first sensors (111), and the plurality of first sensors (111) may be installed on the crane module (120). For example, the plurality of first sensors (111) may be installed on each of the left and right sides of the crane module (120).

[0074] Here, the crane module (120) has a multi-stage structure and may have a shape that allows for height adjustment as it slides in the up and down direction. For example, the crane module (120) may each include a pair of frames that extend side by side and are spaced apart from each other, and may include a plurality of sliding units (121) that are installed overlapping each other so as to be slidable in the up and down direction, and the height of the crane module (120) can be adjusted as the plurality of sliding units (121) slide in the up and down direction.

[0075] In various embodiments, a plurality of first sensors (111) may be installed to correspond one-to-one with each of a plurality of sliding units (121), but are not limited thereto.

[0076] Additionally, a plurality of first sensors (111) may be installed on a plurality of sliding units (121), and when the height of the crane module (120) is at its minimum (e.g., when the crane module (120) is inserted into the mobile inventory inspection robot (100), the plurality of first sensors (111) may be installed so as to be arranged on the same line, but are not limited thereto.

[0077] In one embodiment, the control module (130) can control the operation of the mobile inventory inspection robot (100) so that the mobile inventory inspection robot (100) performs various functions.

[0078] Here, the functions provided by the mobile inventory inspection robot (100) are as follows.

[0079] (1) Basic control functions: crane reduction, charging standby mode (a function to charge while the crane module (120) is reduced), self-diagnosis mode (a function to check for system abnormalities in the sensor module (110) and the drive unit of the mobile inventory inspection robot (100)), edge PC platform synchronization (a function to synchronize by transmitting driving information of the mobile inventory inspection robot (100) and information of the sensor module (110) to the platform), logistics information extraction and update function (a function to extract logistics ID and volume information using images and LiDAR using deep learning, update in real time, and perform secondary detection only on missing data)

[0080] (2) Crane Control Functions: Maximum Height Extension (a function that allows the crane to rise to the maximum height of the logistics shelves to scan the goods), Automatic Rack Height Adjustment (a function that automatically adjusts the height by utilizing information obtained from measuring the height of the entire high rack and flat shelves using LiDAR that scans the surrounding environment), Obstacle Avoidance During Movement (Shelf Obstacles) (a function that allows the inventory verification AMR to detect shelf obstacles using LiDAR and drive while avoiding them), 3D Logistics Loading Space Map Generation (a function that automatically generates a map while driving through the logistics loading space initially)

[0081] (3) Vision Control Function: Shelf and Object Detection Function (LiDAR Module) (A function that allows a 3D LiDAR installed on a crane to collect PCDs and detect shelves and objects), Logistics Information Collection and Analysis (QR, Barcode, OCR, Object) (A function that extracts logistics IDs by analyzing images captured by high-resolution cameras installed in both directions), Optimal Logistics Information Collection Settings (Lighting + Camera) (A function that allows changing the necessary settings for the camera and lighting during collection depending on the logistics site), Real-time Logistics Information Extraction and Re-analysis of Missing Information (A function that extracts information in real time and re-extracts logistics information through secondary analysis if the information is missing), Support for Vertical Movement of Vision Module According to Shelf Configuration (A function that allows adjusting the vertical position of the camera and lighting to accommodate various logistics sites with different shelf heights)

[0082] (4) LiDAR control function: Front and rear spatial / logistics information analysis (function to detect objects in the front and rear and collect and analyze logistics volume using 2D / 3D LiDAR), 360-degree rotation radius (all-around comprehensive collection using 360-degree LiDAR)

[0083] (5) Driving control functions: navigation function (equipped with AMR autonomous driving navigation for field scanning), obstacle avoidance while driving (a function that recognizes and avoids obstacles on the ground in front, behind, left, and right while driving), movement function for data re-collection (a function that can accurately move to the location for re-collection in case of failure to update logistics or extract logistics information), 360-degree rotation function while driving (a function that can rotate 360 ​​degrees in narrow places while driving, allowing for a 360-degree change in direction), sensor parallelism maintenance while driving, and vibration prevention function (a function that enables stable driving even on uneven ground and prevents shaking of the sensor due to vibration, thereby enabling stable data collection)

[0084] Below, a configuration in which various functions are provided through the mobile inventory verification robot (100) as the control module (130) controls the operation of the mobile inventory verification robot (100) will be described in more detail.

[0085] In one embodiment, the control module (130) can control the operation of the sensor module (110). For example, the control module (130) can generate a control command that directs the operation of the sensor module (130), and by controlling the operation of the sensor module (110) according to the control command, the sensor data can be collected through the sensor module (110).

[0086] In various embodiments, the control module (130) can acquire the exact size of a logistics loading structure, such as a rack / shelf, during the process of collecting initial warehouse / logistics data and generating a logistics warehouse map corresponding to the logistics warehouse, and can set the recognition range of the sensor module (110) based on this, and can control the operation of the sensor module (110) to scan the set recognition range.

[0087] In one embodiment, the control module (130) can control the operation of the crane module (120).

[0088] In various embodiments, the control module (130) can adjust the height of the crane module (120).

[0089] In various embodiments, the control module (130) can identify a rack placed near the mobile inventory inspection robot (100) based on sensor data collected from a plurality of second sensors (112), and can adjust the height of the crane module (120) by moving a plurality of sliding units (121) in an up-and-down direction so that the height of the crane module (120) matches the height of the rack.

[0090] For example, the control module (130) can move a plurality of sliding units (121) in the up and down direction so that the height of the crane module (120) and the height of the rack match, and can adjust the position of the plurality of sliding units (121) so that the spacing between the plurality of first sensors (111) is equal.

[0091] As another example, the control module (130) moves a plurality of sliding units (121) in an up-and-down direction so that the height of the crane module (120) and the height of the rack match, and determines the number of sliding units to be moved in an up-and-down direction based on the height of the rack, and selects a sliding unit (121) corresponding to the determined number among the plurality of sliding units (121) to move in an up-and-down direction.

[0092] In addition, as another example, the control module (130) moves a plurality of sliding units (121) in an up-and-down direction so that the height of the crane module (120) and the height of the rack match, and when the rack includes a plurality of shelves, determines the position of each of the plurality of sliding units (121) such that the position of each of the plurality of first sensors (111) and the position of each of the plurality of shelves can match so that each of the plurality of first sensors (111) can photograph each of the plurality of shelves, and moves each of the plurality of sliding units (121) to the corresponding position.

[0093] As another example, the control module (130) can calculate the height of racks placed within a predetermined range centered on the mobile inventory inspection robot (100) based on sensor data obtained by scanning the area around the mobile inventory inspection robot (100), and can automatically adjust the height of the crane module (120) to match the height of each rack when the mobile inventory inspection robot (100) passes through each rack based on the calculated height of the racks.

[0094] As another example, the control module (130) can scan the logistics and adjust the height of the crane module (120) so that the height of the crane module (120) matches the height of the maximum loaded logistics, when the logistics warehouse where the mobile inventory inspection robot (100) is deployed is a flat warehouse or the location of the mobile inventory inspection robot (100) is a space for storing logistics on a flat surface (e.g., a space where racks are not identified).

[0095] In various embodiments, the control module (130) can compare sensor data collected during the process of adjusting the height of the crane module (120) in stages to predetermine the height of the crane module (120) for each location within the logistics warehouse, and can use this to adjust the height of the crane module (120).

[0096] More specifically, first, the control module (130) can collect sensor data from a plurality of second sensors (112) and adjust the height of the crane module (120) stepwise when the mobile inventory inspection robot (100) is located at each of the plurality of points, and can determine the height at each of the plurality of points by comparing the similarity between the sensor data collected from the plurality of second sensors (112).

[0097] For example, the control module (130) can determine the height of the crane module (120) at a specific point as the second height if the similarity between the sensor data collected from a plurality of second sensors (112) when the height of the crane module (120) at a specific point is the first height and the sensor data collected from a plurality of second sensors (112) when the height of the crane module (120) at a specific point is the second height is less than the threshold similarity.

[0098] Meanwhile, the control module (130) can determine the height of the crane module (120) at a specific point as the first height if the similarity between the sensor data collected from a plurality of second sensors (112) when the height of the crane module (120) is the first height and the sensor data collected from a plurality of second sensors (112) when the height of the crane module (120) is the second height is greater than or equal to a threshold similarity.

[0099] Afterward, the control module (130) can adjust the height of the crane module (120) of the mobile inventory inspection robot (100) to a pre-set height (first height or second height) at a specific point when the mobile inventory inspection robot (100) is located at a specific point after the height of the crane module (120) at a specific point has been determined to be a first height or a second height.

[0100] In various embodiments, the control module (130) can adjust the height of the crane module (120) of the mobile inventory inspection robot (100) based on sensor data previously collected from a plurality of second sensors (112) included in the mobile inventory inspection robot (100). For example, when the mobile inventory inspection robot (100) is located at a specific point, the control module (130) can calculate the height of a rack placed near the specific point based on sensor data previously collected through a plurality of second sensors (112) at the specific point, and can adjust the height of the crane module (120) in the up and down direction so that the height of the crane module (120) matches the height of the rack calculated from the previously collected sensor data.

[0101] In one embodiment, the control module (130) can control the driving of the mobile inventory inspection robot (100). For example, the control module (130) can identify an object corresponding to an avoidance target, such as an obstacle, by analyzing point cloud data corresponding to the front and rear areas of the mobile inventory inspection robot (100), and can control the avoidance driving so that a collision with the identified object does not occur.

[0102] In one embodiment, logistics information can be extracted by analyzing sensor data collected from the sensor module (110).

[0103] First, the control module (130) can acquire a high-resolution image through the first sensor (111) (e.g., a high-resolution camera) among the sensor modules (110), and can extract a barcode, QR code, and text as logistics information from the high-resolution image (e.g., FIGS. 12 to 15). For example, the control module (130) can analyze the high-resolution image to identify a region of interest, and can extract logistics information from the identified region of interest.

[0104] Here, the region of interest may be a logistics area, a pallet area, a development box area, a barcode area, a QR area, or a logistics text area, and the logistics information extracted from the region of interest may be a barcode ID, QR code, or text, or may include a pallet logistics ID and other information (product name, quantity, arrival date, number of items, etc.) detected from the barcode ID, QR code, or text, but is not limited thereto.

[0105] In addition, the control module (130) can analyze a high-resolution image to extract the size (width * height) of the logistics shape.

[0106] Here, the method for recognizing various regions from high-resolution images may utilize a deep learning-based image analysis model (e.g., a model trained using images with information labeled in various regions as training data), but is not limited thereto.

[0107] In addition, the method for extracting barcode IDs, QR codes, and characters from high-resolution images may utilize a deep learning-based character extraction model (e.g., OCR), but is not limited thereto.

[0108] In addition, the method for extracting the size of a logistics shape from a high-resolution image may utilize image processing (e.g., an image analysis algorithm that performs the processes of image preprocessing, shape detection, feature extraction, measurement, and analysis), but is not limited thereto.

[0109] At this time, the high-resolution image and the information extracted from the high-resolution image can be stored by matching them with the position (row, column) of the shelf corresponding to the high-resolution image. Here, the position of the shelf corresponding to the high-resolution image may be determined based on the position of the mobile inventory inspection robot (100) when the high-resolution image is taken, but is not limited thereto.

[0110] Next, the control module (130) can obtain point cloud data generated by scanning an area corresponding to the left and right directions of the mobile inventory inspection robot (100) through the second sensor (112) (e.g., LiDAR sensor) among the sensor modules (110), and can obtain the size (width*length*height) of the logistics as logistics information from the point cloud data.

[0111] For example, the control module (130) can extract logistics shape size information from point cloud data using a PCD logistics volume extraction algorithm, but is not limited thereto.

[0112] At this time, the point cloud data and the information extracted from the point cloud data can be stored by matching them with the shelf positions (rows, columns) corresponding to the point cloud data. Here, the shelf positions corresponding to the point cloud data may be determined based on the position of the mobile inventory inspection robot (100) when scanning the point cloud data, but are not limited thereto.

[0113] In various embodiments, the control module (130) can individually acquire logistics information for the left and right directions of the mobile inventory inspection robot (100). For example, the control module (130) can acquire first logistics information corresponding to a rack placed on the left side of the mobile inventory inspection robot (100) at a specific point by analyzing first sensor data corresponding to the left direction of the mobile inventory inspection robot (100) located at a specific point, and acquire second logistics information corresponding to the right direction of the mobile inventory inspection robot (100) by analyzing second sensor data corresponding to a rack placed on the right side of the mobile inventory inspection robot (100) at a specific point.

[0114] At this time, if the heights of the racks placed on the left and right sides of the mobile inventory inspection robot (100) are different, the control module (130) can adjust the height of the crane module (120) based on the rack with the higher height. For example, the control module (130) identifies a first rack placed on the left side of the mobile inventory inspection robot (100) based on first sensor data and identifies a second rack placed on the right side of the mobile inventory inspection robot (100) based on second sensor data, and if the heights of the first rack and the second rack are different, the height of the crane module (120) can be adjusted based on the rack with the higher height between the first rack and the second rack.

[0115] In various embodiments, the control module (130) obtains logistics information using multiple sensor data collected using multiple first sensors (111), and when the interval between the multiple first sensors (111) is greater than or equal to a reference interval, it can generate logistics data using multiple sensor data collected from the multiple first sensors (111). Meanwhile, when the interval between the multiple first sensors (111) is less than a reference interval, the control module (130) can generate logistics inventory data using only at least one sensor data collected from at least one sensor (111) among the multiple first sensors (111).

[0116] When the spacing between sensors is narrow, there is a lot of mutually overlapping information between sensor data, which may result in unnecessary computation work. When the spacing between sensors is less than a standard spacing, that is, when the spacing is narrow, computation can be performed more quickly and efficiently by utilizing only some sensors (e.g., utilizing only the even-numbered or odd-numbered sensors) instead of utilizing all sensors.

[0117] On the other hand, if the spacing between sensors is wide and only a few sensors are selectively utilized, gaps in information collection occur, making accurate inventory management impossible. Therefore, when the spacing between sensors exceeds a standard interval—that is, when the spacing is wide—all sensors are utilized to prevent the omission of information.

[0118] In various embodiments, the control module (130) obtains logistics information using multiple sensor data collected using multiple first sensors (111), and when at least a portion of the multiple sensor data collected from multiple first sensors (111) overlaps, the overlapping information can be automatically filtered based on shelf position information.

[0119] In various embodiments, the control module (130) acquires logistics information based on a plurality of sensor data collected from the sensor module (110), and may acquire logistics information by selecting only high-quality sensor data among the plurality of sensor data. For example, when capturing high-resolution images, differences in image quality and shooting area occur depending on the environment. Considering this, for the purpose of extracting more accurate information from high-resolution images, logistics information may be extracted by utilizing only high-resolution images with a quality level above a certain standard.

[0120] In various embodiments, when the control module (130) intends to conduct an inventory count only at the location where logistics operations were performed based on the logistics inflow and outflow history of a specific date, it can automatically adjust the height of the crane module (120) to match the loading location of the logistics to collect only sensor data corresponding to that location and use this to extract only logistics information corresponding to that location.

[0121] In various embodiments, the control module (130) can perform inventory management by controlling the operation of the mobile inventory inspection robot (100) based on a pre-set schedule (e.g., setting a collection start time, setting a collection end time, setting an immediate scan, setting a scan by zone and priority, etc.). For example, when an inventory inspection of a specific zone of a logistics warehouse is scheduled for a specific date and time, the control module (130) controls the mobile inventory inspection robot (100) to drive through the specific zone of the logistics warehouse at the specific date and time and collect sensor data, and can obtain logistics information corresponding to the specific zone based on the collected sensor data.

[0122] In various embodiments, the control module (130) may perform inventory verification tasks only for locations within the logistics warehouse where logistics operations have occurred. For example, when the control module (130) collects an event from the logistics management server (300) indicating that a logistics update operation has occurred at a specific location, it may control the mobile inventory verification robot (100) to collect sensor data for the specific location and obtain logistics information corresponding to the specific location based on the sensor data.

[0123] In various embodiments, the control module (130) can transmit sensor data obtained through the sensor module (110) of the mobile inventory inspection robot (100) and logistics information obtained from the sensor data to the logistics management server (300).

[0124] The operation of the control module (130) as described above can be performed through a computer program implemented in the form of an application as follows.

[0125] First, through the sensor module edge application, a real-time logistics ID extraction algorithm (high-resolution image → segmentation deep learning model → barcode, text, pallet, logistics area image → OCR deep learning detection model and logistics size algorithm → barcode ID, QR, character, size detection), a real-time size extraction algorithm (LiDAR PCD → logistics size extraction algorithm → logistics size (width, height) shape extraction), and an operation to request re-detection from the mobile inventory inspection robot (100) when there is a sensor data scanning error in the sensor module (110) can be performed.

[0126] In addition, through a server vision application, operations to store cropped logistics image information by location, operations to extract logistics IDs using a high-accuracy deep learning model for missing information extracted in real time, and high-precision barcode, text, and vision deep learning algorithms (precisely detecting missing barcodes and sizes using a real-time algorithm) can be performed.

[0127] In one embodiment, the logistics management server (300) can perform logistics management for the logistics warehouse.

[0128] In various embodiments, the logistics management server (300) can generate logistics data using logistics information obtained through the control module (130) of the mobile inventory inspection robot (100), and can perform inventory management for the logistics warehouse using the logistics data.

[0129] In various embodiments, the logistics management server (300) can generate a map corresponding to the logistics warehouse (e.g., a real-time digital map using 3D LiDAR SLAM) based on sensor data collected from a mobile inventory inspection robot (100) placed in the logistics warehouse, and can record information about objects included in the logistics data (e.g., type and quantity) on coordinates corresponding to the object locations on the map.

[0130] In addition, the logistics management server (300) can simultaneously collect and classify 3D point cloud data and 2D logistics images by space / object, map them with location information, and automatically generate 3D assets to realize an extended reality identical to the actual logistics site.

[0131] In various embodiments, the logistics management server (300) may be connected to a user terminal (200) through a network (400) and may provide a user interface (UI) (e.g., FIG. 19 to FIG. 24) that provides logistics management services to the user terminal (200).

[0132] More specifically, first, referring to FIG. 19, the UI provided by the logistics management server (300) can provide an inventory inspection control function.

[0133] Here, the inventory count control function can provide inventory count status control information (e.g., location control of the mobile inventory count robot (100), verification of processing information (OCR-BARDOCE-PCD), inquiry of inventory count processing results, inquiry of split picking status and result aggregation, etc.), and can display information so that inventory count monitoring can be performed according to the plan only on adjustment shelves that occurred individually on each day, but is not limited thereto.

[0134] Next, referring to FIGS. 20 and 21, the UI provided by the logistics management server (300) can provide an inventory audit work schedule generation function.

[0135] Here, the inventory verification work schedule generation function creates a work plan by setting the operating time of the mobile inventory verification robot (100) and indicating only the location of the manual adjustment shelf that occurred on each day in the inspection area selection, but is not limited thereto.

[0136] Next, referring to FIG. 22, the UI provided by the logistics management server (300) can provide a work list management function.

[0137] Here, the task list management function may provide functions to view the created task list, view the execution status of each task, and modify the task history, but is not limited thereto.

[0138] Next, referring to FIG. 23, the UI provided by the logistics management server (300) can provide device management functions for the mobile inventory inspection robot (100).

[0139] Here, the device management function may provide device status information inquiry, operation status information inquiry, and battery status information inquiry functions, but is not limited thereto.

[0140] Next, referring to FIG. 24, the UI provided by the logistics management server (300) can provide an inventory count result inquiry function.

[0141] Here, the inventory count result inquiry function may provide statistical aggregation of inventory count results by performed task (e.g., inventory count processing results, inventory information consistency rate, types and ratios of error statuses (information mismatch, information not collected, location information mismatch, manual verification required)), but is not limited thereto.

[0142] Here, the user terminal (200) may refer to any form of entity(s) in a system having a mechanism for communication with the control module (130). For example, such a user terminal (200) may include a PC (personal computer), a notebook, a mobile terminal, a smartphone, a tablet PC, and a wearable device, and may include any type of terminal capable of connecting to a wired or wireless network. Additionally, the user terminal (200) may include any computing device implemented by at least one of an agent, an API (Application Programming Interface), and a plug-in. Additionally, the user terminal (200) may include an application source and / or a client application.

[0143] Additionally, the network (400) may refer to a connection structure capable of exchanging information between each node, such as multiple terminals and servers. For example, the network (400) may include a Local Area Network (LAN), a Wide Area Network (WAN), the World Wide Web (WWW), a wired / wireless data network, a telephone network, a wired / wireless television network, a Controller Area Network (CAN), and Ethernet.

[0144] Wireless data communication networks may include, but are not limited to, 3G, 4G, 5G, 3GPP (3rd Generation Partnership Project), 5GPP (5th Generation Partnership Project), LTE (Long Term Evolution), WIMAX (World Interoperability for Microwave Access), Wi-Fi, Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), RF (Radio Frequency), Bluetooth network, NFC (Near-Field Communication) network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, etc. Hereinafter, with reference to FIG. 25, an inventory management method performed through an inventory management system will be described.

[0145]

[0146] FIG. 25 is a flowchart of an inventory management method for a logistics warehouse using a mobile inventory verification robot according to another embodiment of the present disclosure.

[0147] Referring to FIG. 12, in step S110, sensor data for a predetermined space within a logistics warehouse is collected through a sensor module (110) included in a mobile inventory inspection robot (100).

[0148] Here, sensor data is data generated by scanning a predetermined space through the sensor module (110) of the mobile inventory inspection robot (100), and may include, for example, high-resolution images collected from the first sensor (111) and point cloud data collected from the second sensor (112), but is not limited thereto.

[0149] In various embodiments, the control module (130) identifies a rack placed near the mobile inventory inspection robot (100) based on sensor data collected from the sensor module (110), and if the height of the crane module (120) and the height of the rack are different, it can move a plurality of sliding units (121) in the up and down direction so that the height of the crane module (120) and the height of the rack match, and if the height of the crane module (120) is adjusted, it can re-collect sensor data from the sensor module (110).

[0150] In step S120, logistics information is obtained by analyzing sensor data collected from the sensor module (110) through the control module (130) included in the mobile inventory inspection robot (100).

[0151] Here, logistics information may include, but is not limited to, barcodes, QR codes, and text extracted by analyzing high-resolution images, and logistics shape size information (width*height*depth) extracted by analyzing point cloud data.

[0152] In step S130, logistics / inventory management is performed based on logistics information obtained from sensor data through the logistics management server (300).

[0153] In various embodiments, a control module (130) included in a mobile inventory inspection robot (100) can transmit logistics information extracted from sensor data to a logistics management server (300), and the logistics management server (300) can collect logistics information generated through the control module (130) of the mobile inventory inspection robot (100), generate logistics data using the collected logistics information, and perform inventory management using the generated logistics data. For example, the logistics management server (300) can generate logistics data including information regarding the types and quantities of items stored on a plurality of racks and shelves included in each of the plurality of racks based on the logistics data, and can store the generated logistics data.

[0154] In various embodiments, the logistics management server (300) can generate a map corresponding to the logistics warehouse (e.g., a real-time digital map using 3D LiDAR SLAM) based on sensor data collected from a mobile inventory inspection robot (100) placed in the logistics warehouse, and can record information regarding logistics included in the logistics information (e.g., type and quantity) on coordinates corresponding to the object location on the map.

[0155]

[0156] FIG. 26 is a flowchart of a method for performing logistics management using logistics information extracted through a two-stage analysis of sensor data in various embodiments, and FIG. 27 is a diagram illustrating the process of a logistics management system performing inventory management using a mobile inventory verification robot in various embodiments.

[0157] Referring to FIGS. 26 and 27, in step S210, sensor data for a predetermined space within a logistics warehouse is collected through a sensor module (110) included in a mobile inventory inspection robot (100).

[0158] Here, the operation of collecting sensor data and the type of sensor data collected thereby may be implemented in the same or similar form as step S110 of FIG. 25, but are not limited thereto.

[0159] In step S220, a primary analysis of sensor data is performed through a control module (130) included in the mobile inventory inspection robot (100), and the result of the primary analysis is stored through a logistics management server (300).

[0160] In various embodiments, the mobile inventory inspection robot (100) can obtain primary logistics information by performing primary analysis of sensor data using a deep learning-based model (e.g., a deep learning-based image analysis model, a deep learning-based string extraction model, etc.) through the control module (130), and can store the primary logistics information obtained through the primary analysis.

[0161] Here, the primary logistics information obtained through the primary analysis of sensor data may include the same information as the logistics information obtained through step S120 of FIG. 25, but is not limited thereto.

[0162] In step S230, the mobile inventory inspection robot (100) transmits the sensor data to a separate analysis server if there is missing information based on the results of the primary analysis of the sensor data performed through the control module (130).

[0163] In various embodiments, the mobile inventory inspection robot (100) may, based on the results of a primary analysis through the control module (130), designate the specific sensor data as error data if logistics information is not obtained from the specific sensor data, and transmit the specific sensor data designated as error data to a separate analysis server.

[0164] That is, when the accuracy of the logistics information extracted from specific sensor data is low, the mobile inventory inspection robot (100) can transmit the specific sensor data to an analysis server to increase the detection accuracy, and allow a separate analysis server to obtain the logistics information from the specific sensor data.

[0165] Here, the separate analysis server may be a logistics management server (300), but is not limited thereto.

[0166] In step S240, a secondary analysis of specific sensor data transmitted to a separate analysis server is performed through a separate analysis server, and the results of the secondary analysis are stored and updated through a logistics management server (300).

[0167] More specifically, first, a separate analysis server can extract logistics information by analyzing sensor data received from the mobile inventory inspection robot (100).

[0168] At this time, if logistics information is not extracted from the sensor data, a separate analysis server may request the re-collection of sensor data from the mobile inventory verification robot (100), and may extract logistics information by analyzing the sensor data re-collected from the mobile inventory verification robot (100).

[0169] In various embodiments, the mobile inventory verification robot (100) can set the location where specific sensor data was collected as a re-collection location through the control module (130) when specific sensor data is designated as error data. Subsequently, when the mobile inventory verification robot (100) receives a request to re-collect sensor data from a separate analysis server, it can move to the location set as the re-collection location to re-collect the sensor data and transmit the re-collected sensor data to the separate analysis server.

[0170] In various embodiments, when sensor data collected at a specific point is designated as error data n or more times, a separate analysis server sends a notification to the user terminal (200) of a manager managing a logistics warehouse to guide verification of the sensor data collected at the specific point and the specific point, thereby guiding the manager to visually check the sensor data and the racks placed at the specific point to determine whether the environment is one where logistics information cannot be obtained (e.g., whether physical damage has occurred).

[0171] Afterwards, a separate analysis server can transmit the logistics information extracted as a result of performing a secondary analysis to a logistics management server (300), and the logistics management server (300) can store and update the logistics information received from the separate analysis server (e.g., logistics information extracted through the secondary analysis).

[0172] That is, if an unrecognized barcode occurs on multiple labels attached to a box, the sensor data itself can be transmitted to a separate analysis server so that the sensor data can be analyzed by the separate analysis server. For example, if the sensor data includes multiple image frames, only the high-quality image frames among the multiple image frames can be transmitted to a separate analysis server, and the separate analysis server can generate logistics data by performing separate operations (e.g., OCR and barcode re-decoding processes, etc.) on the high-quality image frames received from the control module (130). Through this, misreading can be minimized and the accuracy of logistics inventory can be improved.

[0173]

[0174] The method for managing inventory in a logistics warehouse using the aforementioned mobile inventory verification robot has been explained with reference to the flowchart illustrated in the drawings. For the sake of simplicity, the method for managing inventory in a logistics warehouse using the mobile inventory verification robot has been illustrated and described using a series of blocks; however, the present disclosure is not limited to the order of the blocks, and some blocks may be performed in a different order from that illustrated and described in this specification or simultaneously. Additionally, new blocks not described in this specification and drawings may be added, or some blocks may be deleted or modified. Hereinafter, with reference to FIG. 28, the hardware configuration of the control module (130) of the mobile inventory verification robot (100) will be described.

[0175]

[0176] FIG. 28 is a diagram illustrating the hardware configuration of a control module included in a mobile inventory inspection robot according to another embodiment of the present disclosure.

[0177] Referring to FIG. 28, in various embodiments, a control module (130) may include one or more processors (131), a memory (132) for loading a computer program (135A) executed by the processor (131), a bus (133), a communication interface (144), and a storage (135) for storing the computer program (135A). Here, FIG. 28 illustrates only the components relevant to the embodiments of the present disclosure. Therefore, a person skilled in the art to which the present disclosure pertains will understand that other general-purpose components may be included in addition to the components illustrated in FIG. 28.

[0178] The processor (131) controls the overall operation of each component of the control module (130). The processor (131) may be configured to include a CPU (Central Processing Unit), an MPU (Micro Processor Unit), an MCU (Micro Controller Unit), a GPU (Graphic Processing Unit), or any type of processor well known in the art of the present disclosure.

[0179] Additionally, the processor (131) may perform operations for at least one application or program for executing the method according to the embodiments of the present disclosure, and the control module (130) may have one or more processors.

[0180] In various embodiments, the processor (131) may further include Random Access Memory (RAM) (not shown) and Read-Only Memory (ROM) (not shown) for temporarily and / or permanently storing signals (or data) processed within the processor (131). Additionally, the processor (131) may be implemented in the form of a System on Chip (SoC) comprising at least one of a graphics processing unit, RAM, and ROM.

[0181] Memory (132) stores various data, instructions and / or information. Memory (132) may load a computer program (135A) from storage (135) to execute a method / operation according to various embodiments of the present disclosure. When the computer program (135A) is loaded into memory (132), the processor (131) may perform the method / operation by executing one or more instructions constituting the computer program (135A). Memory (132) may be implemented as volatile memory such as RAM, but the technical scope of the present disclosure is not limited thereto.

[0182] The bus (133) provides communication functions between components of the control module (130). The bus (133) can be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

[0183] The communication interface (144) supports wired and wireless internet communication of the control module (130). Additionally, the communication interface (144) may support various communication methods other than internet communication. To this end, the communication interface (144) may be configured to include a communication module well known in the art of the present disclosure. In some embodiments, the communication interface (144) may be omitted.

[0184] Storage (135) can store a computer program (135A) non-temporarily. When performing an inventory management process of a logistics warehouse using a mobile inventory verification robot through a control module (130), storage (135) can store various information necessary to provide an inventory management process of a logistics warehouse using a mobile inventory verification robot.

[0185] Storage (135) may be configured to include non-volatile memory such as ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), flash memory, a hard disk, a removable disk, or any form of computer-readable recording medium well known in the art to which this disclosure belongs.

[0186] A computer program (135A) may include one or more instructions that cause a processor (131) to perform a method / operation according to various embodiments of the present disclosure when loaded into memory (132). That is, the processor (131) may perform the method / operation according to various embodiments of the present disclosure by executing the one or more instructions.

[0187] In one embodiment, a computer program (135A) may include one or more instructions for performing a method of managing inventory of a logistics warehouse using a mobile inventory verification robot, comprising the steps of: collecting sensor data by scanning a predetermined space within a logistics warehouse through a sensor module included in a mobile inventory verification robot; generating logistics data by analyzing the collected sensor data through a control module included in a mobile inventory verification robot; and generating inventory data using the generated logistics data through a logistics management server and performing inventory management for the logistics warehouse using the generated inventory data.

[0188] The steps of the method or algorithm described in connection with the embodiments of the present disclosure may be implemented directly in hardware, implemented as a software module executed by hardware, or implemented by a combination thereof. The software module may reside in RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), Flash Memory, a hard disk, a removable disk, a CD-ROM, or any form of computer-readable recording medium well known in the art to which the present disclosure belongs.

[0189] The components of the present disclosure may be implemented as a program (or application) and stored on a medium to be executed in combination with a computer, which is hardware. The components of the present disclosure may be implemented as software programming or software elements, and similarly, embodiments may be implemented in programming or scripting languages ​​such as C, C++, Java, assembler, etc., including various algorithms implemented as combinations of data structures, processes, routines, or other programming configurations. Functional aspects may be implemented as algorithms executed on one or more processors.

[0190]

[0191] Although embodiments of the present disclosure have been described above with reference to the attached drawings, those skilled in the art will understand that the present disclosure may be implemented in other specific forms without altering its technical concept or essential features. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive.

Claims

1. In a mobile inventory verification robot deployed in a logistics warehouse, The above-mentioned mobile inventory verification robot is, A crane module having a multi-stage structure and adjustable height as it slides in the up and down direction; A sensor module that collects sensor data by scanning a predetermined space within the above-mentioned logistics warehouse; and It includes a control module that obtains logistics information by analyzing sensor data collected from the sensor module above, The above sensor module is, A plurality of first sensors installed on at least a portion of the crane module, installed in the left and right directions of the mobile inventory inspection robot; and Characterized by including a plurality of second sensors installed in at least a part of the mobile inventory verification robot, and installed in the forward and rear directions of the mobile inventory verification robot. Mobile inventory verification robot for inventory management in logistics warehouses.

2. In Paragraph 1, The above plurality of first sensors are, Characterized by collecting sensor data corresponding to the left direction of the mobile inventory inspection robot and sensor data corresponding to the right direction of the mobile inventory inspection robot, as they are respectively installed on the left and right sides of the crane module based on the driving direction of the mobile inventory inspection robot. Mobile inventory verification robot for inventory management in logistics warehouses.

3. In Paragraph 1, The above crane module is, It includes multiple sliding units, The above plurality of sliding units are, Each comprising a pair of frames that extend parallel to each other at a distance from one another, and characterized by being installed in an overlapping manner so as to be slidable in the vertical direction, Mobile inventory verification robot for inventory management in logistics warehouses.

4. In Paragraph 3, The above plurality of first sensors are, Characterized by being installed in each of a plurality of sliding units, Mobile inventory verification robot for inventory management in logistics warehouses.

5. In Paragraph 4, The above control module is, Identifying racks placed near the mobile inventory inspection robot based on sensor data collected from the plurality of second sensors, and The plurality of sliding units are moved in the vertical direction so that the height of the crane module matches the height of the identified rack, Characterized by adjusting the positions of the plurality of sliding units so that the spacing between the plurality of first sensors becomes equal. Mobile inventory verification robot for inventory management in logistics warehouses.

6. In Paragraph 5, The above control module is, When the spacing between the plurality of first sensors is greater than or equal to a reference spacing, logistics information is obtained using the plurality of sensor data collected from the plurality of first sensors, and When the interval between the plurality of first sensors is less than the reference interval, the logistics information is obtained using only at least one sensor data collected from at least one of the plurality of first sensors. Mobile inventory verification robot for inventory management in logistics warehouses.

7. In Paragraph 4, The sensor data collected from the plurality of first sensors is It includes first sensor data corresponding to the left direction of the mobile inventory verification robot located at a specific point and second sensor data corresponding to the right direction of the mobile inventory verification robot located at the specific point, The above control module is, Identifying a first rack positioned to the left of the mobile inventory verification robot based on the first sensor data, and identifying a second rack positioned to the right of the mobile inventory verification robot based on the second sensor data, Characterized by adjusting the height of the crane module based on the rack with the higher height among the identified first rack and the identified second rack when the heights of the identified first rack and the identified second rack are different. Mobile inventory verification robot for inventory management in logistics warehouses.

8. In Paragraph 4, The above control module is, Identifying racks placed near the mobile inventory inspection robot based on sensor data collected from the plurality of second sensors, and Based on the height of the rack identified above, the number of sliding units to be moved in the vertical direction is determined, and Characterized by selecting a sliding unit corresponding to the determined number among the plurality of sliding units and moving it in the up and down direction. Mobile inventory verification robot for inventory management in logistics warehouses.

9. In Paragraph 4 The above control module is, When a rack placed near the mobile inventory inspection robot is identified based on sensor data collected from the plurality of second sensors, the plurality of sliding units are moved in the vertical direction so that the height of the crane module matches the height of the identified rack, When the identified rack includes a plurality of shelves, the position of each of the plurality of sliding units is determined such that the position of each of the plurality of second sensors matches the position of each of the plurality of shelves, and each of the plurality of sliding units is moved to the determined position. Mobile inventory verification robot for inventory management in logistics warehouses.

10. In Paragraph 1, Each of the above plurality of first sensors is, It includes a high-resolution camera that collects image data as it scans the left and right areas of the above-mentioned mobile inventory inspection robot, and Each of the above plurality of second sensors is, Each comprising a LiDAR sensor that collects point cloud data as it scans the front and rear areas of the above-mentioned mobile inventory inspection robot, Mobile inventory verification robot for inventory management in logistics warehouses.

11. In Paragraph 1, The above control module is, If the similarity between sensor data collected from the plurality of second sensors when the height of the crane module at a specific point is a first height and sensor data collected from the plurality of second sensors when the height of the crane module is a second height is less than a threshold similarity, the height of the crane module at the specific point is determined as the second height. Characterized by determining the height of the crane module at a specific point as the first height when the similarity between the sensor data collected from the plurality of second sensors when the height of the crane module is a first height and the sensor data collected from the plurality of second sensors when the height of the crane module is a second height is greater than or equal to the threshold similarity. Mobile inventory verification robot for inventory management in logistics warehouses.

12. In Paragraph 1, The above control module is, When the above mobile inventory verification robot is located at a specific point, the height of a rack placed near the specific point is calculated based on sensor data previously collected from the plurality of second sensors at the specific point, and Characterized by adjusting the height of the crane module in the vertical direction so that the height of the crane module and the calculated height match. Mobile inventory verification robot for inventory management in logistics warehouses.

13. A mobile inventory verification robot deployed in a logistics warehouse comprising a sensor module that collects sensor data by scanning a predetermined space within the logistics warehouse and a control module that obtains logistics information by analyzing the sensor data collected from the sensor module; and It includes a logistics management server that generates logistics data using logistics information obtained from the control module and performs inventory management for the logistics warehouse using the generated logistics data. The above sensor module is, Characterized by including a plurality of first sensors installed on a crane module having a multi-stage structure and capable of height adjustment as it slides in the vertical direction, and a plurality of second sensors installed on the front and rear sides of the mobile inventory inspection robot. Inventory management system for a logistics warehouse using a mobile inventory verification robot.

14. A method performed through an inventory management system comprising a mobile inventory verification robot and a logistics management server deployed within a logistics warehouse, A step of collecting sensor data by scanning a predetermined space within the logistics warehouse through a sensor module included in the above-mentioned mobile inventory inspection robot; A step of obtaining logistics information by analyzing the collected sensor data through a control module included in the mobile inventory verification robot; and The method includes the step of generating logistics data using the acquired logistics information through the logistics management server, and performing inventory management for the logistics warehouse using the generated logistics data. The step of collecting the above sensor data is, A step comprising adjusting the height of the crane module on which the sensor module is installed according to the height of the rack placed near the mobile inventory inspection robot. A method for managing inventory in a logistics warehouse using a mobile inventory verification robot.

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