Shelf robot

Abstract

Provided is a shelf robot which provides good load storage capacity and good workability in loading / unloading, and which is suitable for load inventory control. A shelf robot (1) comprises a rotary shelf (20) that can rotate about a rotation axis (10), a shelf rotation drive unit (23) that causes the rotary shelf (20) to rotate around the rotation axis (10), and a control unit (50). For the rotary shelf (20), a plurality of storage spaces (21, 22) are set along a virtual circle centered on the rotation axis (10). The control unit (50) comprises a target storage space identification means (63) that identifies a target storage space in which a stored object that a user is about to take out is stored, a loading / unloading position determination means (64) that determines the unloading position of the stored object in accordance with the attribute of the user, and a storage space movement means (71) that moves the target storage space to the unloading position by causing the rotary shelf (20) to rotate around the rotation axis (10) through control of the shelf rotation drive unit (23).

Description

Technical Field

[0001] The present invention relates to shelf equipment, and more particularly to a shelf robot suitable for assisting in the loading and unloading of goods (also referred to as "stored items") or inventory management using artificial intelligence technology.

Background Art

[0002] Conventionally, a rotary type of shelf equipment is known as shelf equipment that has a large storage capacity for goods and good workability for loading and unloading (incoming and outgoing). (See, for example, Patent Document 1). The rotary shelf equipment described in Patent Document 1 includes a box-shaped enclosure (1), an endless chain (5) wound vertically within the enclosure (1), and a bucket (13) swingably supported on the endless chain (5) via a link plate (14). By circulating the endless chain (5), the target bucket (13) is moved to the loading and unloading outlet (18) formed at the lower front of the enclosure (1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, the types of goods stored on the shelf and the users who use the shelf are diverse. For example, if it is possible to assist in the loading and unloading work according to the weight of the goods put in and out of the shelf or the physique of the user, etc., the convenience should be further improved. However, the shelf equipment described in Patent Document 1 above lacks consideration for such problems, for example, the position of the loading and unloading outlet of the goods is fixed.

[0005] Furthermore, the personnel responsible for tasks such as receiving and shipping goods are not identified without paper documentation. Identifying personnel without paper documentation means relying on cumbersome handwritten records to comply with standards (GXP) established by government and other public institutions to ensure the reliability of who did what and when.

[0006] This invention is based on the discovery of new challenges in such shelving systems and aims to provide a shelving robot that is excellent in terms of storage capacity and ease of loading and unloading goods, and is also suitable for assisting in loading and unloading goods or inventory management using, for example, artificial intelligence technology. [Means for solving the problem]

[0007] To solve the above-mentioned problems, the present invention provides a shelf robot comprising a rotating shaft, a rotating shelf rotatable about the rotating shaft, a shelf rotation drive unit for rotating the rotating shelf about the rotating shaft, and a control unit, wherein the rotating shelf has a plurality of storage spaces set along a virtual circle centered on the rotating shaft, and the control unit comprises a target storage space identification means for identifying a storage space (referred to as the target storage space) among the plurality of storage spaces in which an item to be retrieved by the user is currently stored, an item retrieval / in / out position determination means for determining the item retrieval position according to the user's attributes, and a storage space moving means for moving the target storage space to the retrieval position by controlling the shelf rotation drive unit to rotate the rotating shelf about the rotating shaft.

[0008] In the shelf robot, it is preferable that the plurality of storage spaces in the rotating shelf are arranged in a ring along a single virtual circle to form a single layer, and that the layer is set up in multiple concentric circles around the rotation axis.

[0009] Furthermore, it is preferable that the shelf robot further includes a front plate on the loading / unloading side of the rotating shelf, which has a loading / unloading entrance corresponding to the loading position.

[0010] Furthermore, it is preferable that the shelf robot includes, in addition to the control unit, a storage item identification means for identifying items stored in the storage space, and the target storage space identification means for selecting a target storage item that the user intends to retrieve from among the storage items identified by the storage item identification means, and for identifying the storage space in which the selected target storage item is stored as the target storage space.

[0011] Furthermore, it is preferable that the shelf robot includes a control unit which further comprises a user determination means which determines at least one of the user's physical characteristics, posture, or personal identification information as the user's attribute, and the loading / unloading position determination means which determines the loading position based on the attribute determined by the user determination means.

[0012] Furthermore, it is preferable that the shelf robot's storage item identification means uses code reading technology to identify the items stored in the storage space.

[0013] Furthermore, it is preferable that the shelf robot uses image recognition technology to determine the user's attributes using the user determination means.

[0014] Furthermore, the shelf robot preferably includes an image capture device for photographing users handling stored items, and a user determination means for determining the user from the image captured by the image capture device. The control unit generates a location information algorithm based on the result determined by the user determination means, thereby executing operation records required by GXP, a public standard aimed at ensuring the reliability of operations regarding information on who, when, and what was done.

[0015] Furthermore, the shelf robot is preferably a shelf robot comprising a rotating axis, a rotating shelf rotatable about the rotating axis, a shelf rotation drive unit that rotates the rotating shelf about the rotating axis, and a control unit, wherein the rotating shelf has a plurality of storage spaces set along a virtual circle centered on the rotating axis, a storage container is installed in each of the storage spaces, and the lower part of the storage container is provided with a forward and backward moving plate and a bottom plate (pallet), and the control unit transmits information calculated from an image taken by the image capture device, including the forward and backward moving plate and / or the bottom plate (pallet), to a transport vehicle that transports the stored items stored in the storage containers, thereby enabling cooperative operation with the transport vehicle.

[0016] Furthermore, it is preferable that the shelf robot operates using artificial intelligence technology in its control unit. [Effects of the Invention]

[0017] According to the present invention, a shelf robot can be provided that is excellent in terms of cargo storage capacity and ease of loading and unloading, and is also suitable for cargo loading and unloading support or inventory management using artificial intelligence technology, for example. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing the front view of the basic shelf structure of the shelf robot. [Figure 2] This is a conceptual diagram showing the front view of the rotating shelf that makes up the shelf robot. [Figure 3] This is a conceptual diagram showing the side view of the basic shelf component of a shelf robot. [Figure 4] This is a block diagram showing the control and processing means incorporated into a shelf robot. [Figure 5] This flowchart illustrates the process of loading (receiving) goods into a shelving robot. [Figure 6] This flowchart illustrates the process of removing (retrieving) stored items from a shelf robot. [Figure 7] This is a functional block diagram to further explain the configuration of the shelf robot.

Best Mode for Carrying Out the Invention

[0019] Hereinafter, a preferred embodiment of the shelf robot according to the present invention will be described. FIGS. 1 to 3 are conceptual diagrams for explaining the basic shelf structure of the shelf robot 1 according to an embodiment of the present invention. As shown in these figures, the shelf robot 1 has, as a basic shelf structure, a rotating shaft 10 and a rotating shelf 20 that can rotate around the rotating shaft 10. The rotating shelf 20 for storing luggage is rotationally driven around the rotating shaft 10 by a shelf rotation driving unit 23 including, for example, an electric motor. Here, an embodiment in which the rotating shelf 20 rotates in the vertical direction around the horizontal rotating shaft 10 will be described, but the rotating shelf 20 may rotate in the horizontal direction around a vertical rotating shaft.

[0020] In the description of this specification, the "luggage" stored in the shelf robot includes, in addition to the objects handled by the user (including animals and plants such as livestock and biological samples), humans depending on the purpose and use of the embodiment of the shelf robot.

[0021] In the present embodiment, a front plate 30 is provided on the loading / unloading side, which is the front side of the rotating shelf 20. One or more loading / unloading ports 31, which are opening windows for loading and unloading luggage, are formed at one or more locations on the front plate 30 corresponding to the loading / unloading positions of the rotating shelf 20. The front plate 30 may be fixed, or may be rotationally driven around the rotating shaft 10 by a front plate rotation driving unit 33 including, for example, an electric motor.

[0022] Further, a rear plate 40 may be provided on the shelf basic structure on the side opposite to the front plate 30 of the rotating shelf 20. In the present embodiment, the front side of the rotating shelf 20 is the loading / unloading side for taking in and out luggage, but a mode in which luggage can be taken in and out from both sides of the front and back of the rotating shelf 20 may also be adopted. In that case, the rear plate 40 may have the same configuration as the front plate 30, that is, may have a loading / unloading port at an appropriate position.

[0023] In particular, as conceptually shown in Figure 2, the rotating shelf 20 has multiple storage spaces 21, 21, ..., 22, 22, ... arranged along virtual circles L1 and L2 centered on the rotation axis 10. For example, the first layer of storage space is formed by arranging multiple storage spaces 21, 21, ... in a ring shape along the outermost virtual circle L1, and then the second layer of storage space is formed by arranging multiple storage spaces 22, 22, ... in a ring shape along the inner virtual circle L2. In this way, the rotating shelf 20 has multiple concentric storage layers L1, L2, ... centered on the rotation axis 10. However, in carrying out the invention, the number of storage space layers may be one layer or three or more layers. Also, all layers may rotate as a single unit, or each layer may rotate independently.

[0024] The number of storage spaces 21 and 22 in each layer described above is preferably set to a multiple of 4, 5, 6, or 10. Furthermore, the storage spaces 21 and 22 are preferably cylindrical or spherical. The size of the storage space is set, for example, as follows: First, in the outermost first layer L1, the storage space radius is calculated based on the radius of the rotating shelf 20. Next, the radius of the storage space 22 in the second layer L2, which is inside the first layer L1, is set to be the same size as the storage space 21 in the first layer L1. In other words, the radius of the storage space 22 in the second layer L2 is not calculated based on the surplus turning radius obtained by subtracting the storage space radius of the first layer L1 from the radius of the rotating shelf 20.

[0025] Each storage space 21, 22 is provided with storage containers 211, 221 for storing luggage. Preferably, the storage containers 211, 221 are suspended within the storage spaces 21, 22. Alternatively, the storage containers 211, 221 may be supported or placed on a swinging platform or the like that is always kept horizontal within the storage spaces 21, 22. Each storage container may be equipped with a detachable device for exchanging it for other storage containers.

[0026] Storage spaces 21 and 22 are designed to be the largest possible relative to the size of the rotating shelf 20 and the number of storage containers 211 and 221. Furthermore, the storage spaces 21 and 22 and the storage containers 211 and 221 are designed so that collisions do not occur between them when the rotating shelf 20 rotates. To this end, the radii of the storage spaces 21 and 22, as well as the diagonal lengths and side lengths of the storage containers 211 and 221, are designed so that adjacent storage spaces 21 and 22 have a gap of 1% or more relative to their radius (storage space radius).

[0027] A label reader 34, which constitutes a stored item identification means 62 described later, is provided on the back of the front panel 30 (the side facing the rotating shelf 20). The label reader 34 is a device that identifies stored items in the storage spaces 21 and 22, for example, by using code reading technology. Labels such as two-dimensional barcodes, QR codes (registered trademarks), and RFID tags are attached to the stored items, and the label reader 34 can obtain identification code information for each stored item from these labels in a contactless manner.

[0028] Furthermore, an image capture device (camera) 35 for photographing the contents of the rotating shelf 20 may be provided on the back of the front panel 30. The image capture device 35 can be used auxiliaryly by the contents identification means 62, for example, to identify the contents by image recognition using artificial intelligence technology when the label reading device 34 cannot identify what the contents are, depending on the orientation and placement of the contents.

[0029] The label reader 34 and / or image capture device 35 are preferably mounted on the back of the front panel 30 so that they can move linearly from the left end to the right end. With this configuration, the contents of the rotating shelf 20 can be identified throughout without any blind spots.

[0030] Furthermore, the front portion of the front panel 30 is provided with an image capturing device (camera) 36, which constitutes a user determination means 61 (described later) for determining the user's attributes. The user determination means 61 may also include a near-field communication device (NFC reader) 37, such as a card reader, to identify the user.

[0031] The shelf robot 1 according to this embodiment includes a arithmetic processing unit 51 and a computer system (control unit) 50 which includes a storage device (database) 52 connected to the arithmetic processing unit 51. The computer system 50, which includes the arithmetic processing unit 51 and the storage device 52, etc., and the elemental equipment incorporated into the shelf robot 1 work together to realize, for example, the control and processing means shown by the dashed block in Figure 4.

[0032] Specifically, the shelf robot 1 of this embodiment includes, as analytical means, a user determination means 61, a stored item identification means 62, a target storage space identification means 63, and an loading / unloading position determination means 64. The shelf robot 1 also includes, as drive control means, a storage space movement means 71 and a loading / unloading entrance movement means 72. The configuration and processing operations of these functional means will be described in more detail below. Note that, among the functional blocks shown in Figure 4, some of the analytical processing that requires high-speed computation of large amounts of data, such as image recognition processing and deep learning (machine learning) processing, may be processed by an external (central) large computer connected to the computer system 50 of the shelf robot 1 via a network.

[0033] (User determination means) The user determination means 61 comprises, for example, an image capturing device (camera) 36 and / or a near-field communication device (NFC reader) 37 provided on the front of the front panel 30, and a user determination processing unit 561 implemented in the computer system 50. The user determination means 61 determines, for example, at least one of the following as user attribute information from an image captured by the image capturing device (camera) 35 using image recognition with artificial intelligence technology by the user determination processing unit 561: for example, the type of user (human, transport vehicle, transport robot, etc.), physical and structural characteristics (e.g., height, build, gender, presence or absence of handling arms, etc.), posture (standing, crouching, in a wheelchair, etc.), or personal identification information (facial recognition, personal ID, vehicle equipment registration number, etc.). Alternatively, the user determination means 61 may determine or identify a user based on information read by the near-field communication device (NFC reader) 37, together with / or instead of the image capturing device 36 described above.

[0034] (Means for identifying stored items) The storage item identification means 62 includes, for example, a label reader 34 and / or an image capture device (camera) 35 provided on the back of the front panel 30, and a storage item identification processing unit 562 implemented in the computer system 50. The storage item identification means 62 uses the image capture device 35 to photograph the luggage (storage items) stored in the storage spaces 21, 22 or storage containers 211, 221 of the rotating shelf 20. The label reader 34 may read a two-dimensional code attached to the luggage (storage items) to obtain identification code information for the luggage (storage items). Alternatively, based on the image of the captured luggage (storage items), the luggage (storage items) may be identified by image recognition processing using artificial intelligence technology.

[0035] The identification code information for each stored item identified by the stored item identification means 62 is managed in the storage device (database) 52 of the computer system 50 in an inventory management table associated with the individual information of the storage spaces 21 and 22 in which the stored item is stored. In addition, the inventory management table also records the ID information of the user (in this specification, the term "user" includes not only people who load and unload goods, but also transport vehicles such as four-wheeled vehicles and forklifts) and the date and time of use (when the goods were loaded or unloaded) as historical information for each storage space 21 and 22.

[0036] (Means for identifying the target storage space) The target storage space identification processing unit 563 (target storage space identification means 63) is a means for identifying, among the multiple storage spaces 21, ..., 22, ... provided in the rotating shelf 20, the storage space in which the item the user intends to retrieve is currently stored or the storage space in which the user intends to store their belongings (collectively referred to as the "target storage space").

[0037] For example, the storage device 52 manages a position reference table that associates individual information for all storage spaces 21 and 22 with polar coordinate information (layer number, rotation angle from a reference) indicating the relative position of each storage space 21 and 22 on the rotating shelf 20. When the target storage space identification processing unit 563 is given identification code information for a certain stored item, it can search for the storage spaces 21 and 22 in which that item is stored by referring to the inventory management table. Furthermore, by referring to the position reference table based on the current rotation angle of the rotating shelf 20, it can immediately identify the current position of the storage space in which the item is stored.

[0038] Furthermore, when a user brings in luggage, the target storage space identification processing unit 563 can identify, for example, the available storage spaces 21 and 22 closest to the determined loading position (loading / unloading entrance 31) as the target storage spaces. Alternatively, based on the user's personal identification information identified by the user determination means 61, the storage spaces 21 and 22 reserved by or exclusively for that user may be identified as the target storage spaces.

[0039] (Carry-in / out position determining means) The loading / unloading position determination processing unit 564 (loading / unloading position determination means 64) is a processing means that determines the loading / unloading position of stored items according to the user's attributes, for example, determined by the user determination means 61. For example, the loading / unloading position can be determined to an optimized height that makes it easier to load and unload items, depending on the user's physical characteristics and posture.

[0040] (Means of transporting storage space) The storage space movement control unit 571 (storage space movement means 71) is a drive control means that controls the shelf rotation drive unit 23 described above to rotate the rotating shelf 20 around the rotation axis 10, thereby moving the specified target storage space to the determined loading / unloading position (loading / unloading entrance 31).

[0041] (Means of transporting goods at the loading / unloading entrance) The loading / unloading entrance / exit movement control unit 572 (loading / unloading entrance / exit movement means 72) is a drive control means that controls the front plate rotation drive unit 33 described above to rotate the front plate 30 around the rotation axis 10, thereby moving the predetermined loading / unloading entrance / exit 31 to the determined loading / unloading position.

[0042] Next, an example of the operation of the shelf robot 1 having the basic shelf configuration described above will be explained.

[0043] (Explanation of the loading process) Figure 5 is a flowchart showing an example of the actions a user takes when storing items in the shelf robot 1.

[0044] In this embodiment, first, when a user approaches the shelf robot 1, the user determination means 61 is activated. The user determination means 61 takes a picture of the user with the image capture device 36 and determines the user's face and attributes (e.g., the user's face, physical characteristics, posture, etc.) based on the image (step S101). To more accurately identify the user, the user determination means 61 may obtain the user's personal ID or key information from an ID card held over the near-field communication device (NFC reader) 37, or may ask the user to enter an authentication code such as a pre-registered password.

[0045] Next, the loading / unloading position determination means 64 determines the optimal loading position according to the user's attributes determined by the user determination means 61 (step S102). Then, the loading / unloading entrance moving means 72 moves the loading / unloading entrance 31 to the determined loading position by rotating the front plate 30 around the rotation axis 10 (step S103).

[0046] Next, the target storage space identification means 63 identifies one of the multiple storage spaces 21, 22 of the rotating shelf 20 as the target storage space (step S104). Then, the storage space moving means 71 rotates the rotating shelf 20 around the rotation axis 10 to move the identified target storage space 21 (22) to the determined loading position (loading / unloading entrance 31) (step S105). This allows the user to easily store their belongings in the target storage space 21 (22) through the loading / unloading entrance 31 of the front panel 30.

[0047] The luggage (storage items) stored in the storage space 21 (22) have their identification code information automatically acquired by the storage item identification means 62 (label reader 34 and / or image capture device 35). Then, the receiving history information in the inventory management table managed in the storage device (database) 52 of the computer system 50 is updated (step S106).

[0048] (Explanation of the process for removing stored items) Next, referring to the flowchart in Figure 6, we will explain an example of the actions a user takes when retrieving items stored in the shelf robot 1.

[0049] First, when a user approaches the shelf robot 1, the user determination means 61 takes a picture of the user with the image capture device 36 and determines the user's face and attributes (e.g., the user's face, physical characteristics, posture, etc.) based on the image (step S201). The user determination means 61 may obtain the user's personal ID or key information from an ID card held over the short-range wireless communication device 37, or it may authenticate the user using a dedicated authentication application such as a smartphone.

[0050] In the next step S202, the target storage space identification means 63 refers to the inventory management table described above based on the user authentication information (e.g., personal ID or key information) determined by the user determination means 61, and searches for the items stored in the rotating shelf 20 by the user, i.e., the belongings owned by the user. If the user has stored one item, the target storage space identification means 63 selects that item as the target item that the user intends to retrieve. If the user has stored multiple items and they are stored across multiple storage spaces 21 and 22, the user may be asked to perform an additional specification input operation to select the target item. Once the item to be retrieved is specified by the user's input operation, the target storage space identification means 63 selects that specified item as the target item.

[0051] The target storage space identification means 63 identifies the storage space 21 (22) (referred to as the "target storage space") in which the target storage items are stored by referring to the inventory management table based on the identification code information of the target storage items (step S203).

[0052] Next, the loading / unloading position determination means 64 determines the optimal loading position according to the user's attributes determined by the user determination means 61 (step S204). Then, the loading / unloading entrance / exit moving means 72 moves the loading / unloading entrance / exit 31 to the determined loading position by rotating the front plate 30 around the rotation axis 10 (step S205).

[0053] Furthermore, the storage space moving means 71 moves the identified target storage space 21 (22) to the determined loading position (loading / unloading entrance 31) by rotating the rotating shelf 20 around the rotation axis 10 (step S206). This allows the user to easily retrieve the desired luggage (stored items) from the target storage space 21 (22) through the loading / unloading entrance 31 of the front panel 30.

[0054] When the target stored item is successfully retrieved, the computer system 50 updates the retrieval history information in the inventory management table managed by the storage device (database) 52 (step S207).

[0055] The shelf robot 1, having such a basic shelf structure, can achieve good loading and unloading efficiency while maintaining maximum storage capacity for goods. Furthermore, the shelf robot 1 is also suitable for assisting with loading and unloading goods or inventory management using artificial intelligence technology.

[0056] In addition to the above, conventional multi-tiered shelving systems present several specific technical challenges or needs, as follows:

[0057] [1] Lack of height control to adjust the height of stored items according to the user's physique. [2] Storage space is occupied in inconvenient locations, resulting in a low total area of ​​easily accessible storage containers per floor area. [3] Lack of a function to identify information about the stored items (quantitative information, qualitative information such as type and time, and location information within the storage space due to rearrangement). [4] To solve the high burden on users by analyzing the condition of stored items (qualitative information including shape or text, and positional information of the storage space, such as disorganization) using image analysis. [5] It does not have the function to analyze images of stored items located outside the shelves. [6] All sides of the front are fixed as loading / unloading entrances to reduce the time and distance to reach the stored items. [7] The weight of each storage container is measured by placing the storage container on a weighing scale without human intervention, and the weight fluctuations are monitored. [8] Tilt the storage container either to the left or right, or to the front or back. [9] Moving the stored items forward or backward to move their position toward the user and making them visually recognizable to the user.

[10] When using a transport vehicle, two steps are required: inserting the forks to move the vehicle towards the transporter and inserting the forks all the way in. This procedure should be reduced to one step.

[11] To monitor from a 360-degree perspective, for example, by rotating horizontally 180 degrees towards the side from which the stored items or storage containers are loaded or unloaded, or by rotating horizontally in 90-degree increments to capture images of the stored items as stereoscopic images.

[12] By placing an additive port, lighting device, and temperature sensor in one location for each stored item, substance addition, illumination, and temperature control can be completed for all storage containers on the shelf, and the environment (temperature) of the stored items can be set uniformly by a constant change in height within the room.

[13] Perform work on the bottom of the storage container or stored items in a stable manner while the user is standing or sitting.

[14] Loading and unloading stored goods between locations with different levels (such as warehouse entrances and truck entrances, the movement of goods between land and on a cargo ship, or scaffolding and work areas at a construction site).

[15] Monitor user safety by analyzing images of weather conditions (such as rain and wind) around the shelves and analyzing the emotions of people's voices around the shelves to prevent a lack of composure.

[16] To provide a system for integrating and supporting medical care in the same time and space.

[17] Identify the person in charge of the task without using paper documents.

[18] Identifying the persons responsible for the work without paper records would rely on cumbersome handwritten records to comply with standards (GXP) established by government and other public institutions for the purpose of ensuring the reliability of who did what and when. Furthermore, the public standard GXP includes GAP (Good Agricultural Practice), GCP (Good Clinical Practice for Clinical Trials of Pharmaceuticals and Medical Devices), GCLP (Clinical Laboratory Practice for Clinical Trial Specimens), GDP (Good Distribution Practice for Pharmaceuticals), GLP (Good Laboratory Practice for Non-Clinical Trials of Pharmaceuticals and Medical Devices), GMP (Good Manufacturing Practice for Pharmaceuticals and Quasi-drugs), GQP (Quality Control Practice for Pharmaceuticals, Quasi-drugs, Cosmetics and Medical Devices), GVP (Post-Marketing Safety Management Practice for Pharmaceuticals, Quasi-drugs, Cosmetics and Medical Devices), GPSP (Post-Marketing Surveillance and Testing Practice), or GPMSP (Post-Marketing Surveillance Practice for Pharmaceuticals).

[0058] To address these specific challenges, the shelf robot can be equipped with the following five additional functions, depending on the product's intended use.

[0059] The first function is a rotation and stopping function. The rotating shelf 20 that stores the stored items or the storage containers 211 and 221 is equipped with a rotation and stopping device that stops the rotation, and when a rotation and stopping of the rotating shelf 20 that is affected by gravity is selected by the operation of the operating electronic device or by a signal from the user, a stop control algorithm 651 is generated, the rotation stops, and horizontality is maintained. Next, when a rotation and stopping of the rotating shelf 20 that is not affected by gravity is selected by the operation of the operating electronic device or by a signal from the user, the horizontality by the rotation stopping device becomes horizontality that is not affected by gravity, and work at the bottom of the stored items in the storage containers 211 and 221 can be performed in a standing or sitting position.

[0060] The second function is weight measurement. For measuring the weight of the stored items or the storage containers 211 and 221, a weighing scale 673 is provided, which is installed at the bottom of the storage containers 211 and 221 located at the lowest part of the shelf. The weight measurement by the weighing scale 673 at the bottom of the storage container is performed by operating the operating electronic device or by a signal from the user, which generates a weight measurement algorithm 671, which causes the storage containers 211 and 221 to rotate as the rotating shelf 20 rotates, and the containers rotate and stop at the location where the weighing scale 673 is installed. When the storage containers 211 and 221 float by pulling the rope connected to them, which is suspended at the stopping point, the weighing scale 673 is installed at the bottom of the storage containers 211 and 221, and when the rope is released, the weight is recorded in the central computer from images of the shake of the weight scale and the shake of the weighing plate for each storage container 211 and 221.

[0061] The third function is liquid volume adjustment. For adjusting the amount of liquid contained in the storage containers 211 and 221 that contain liquid, the storage containers 211 and 221 are equipped with tilting points, and a liquid volume adjustment algorithm 681 is generated by the operation of the operating electronic device or by a signal from the user, and the liquid volume adjustment when the storage containers 211 and 221 or the storage containers contain liquid is adjusted by pulling a rope on one side connected to a container suspended from the tilting point, thereby tilting the storage containers 211 and 221 or the storage containers either forward or backward relative to the front, and the liquid volume is adjusted from the image of the lighting mismatch that changes.

[0062] The fourth function is horizontal rotation. As a component that causes a change in viewpoint by horizontal rotation of the stored items or the storage containers 211 and 221, a horizontal rotating plate 693 is provided at the bottom of the storage containers 211 and 221 on the shelf, and a horizontal rotation algorithm 691 is generated by the operation of the operating electronic device or by the image of the user's signal, and the orientation of the storage containers 211 and 221 relative to the front is adjusted by the rotation of the horizontal rotating plate 693 by the image, which reverses the front-facing orientation of the storage containers 211 and 221 to the rear-facing orientation, or the storage containers 211 and 221 are rotated horizontally and stopped horizontally in order to create a 360-degree viewpoint in order to capture images of all four faces or four compartments of the cube, or the storage containers 211 and 221

[0063] The fifth function is addition and environmental homogenization. To reflect the addition to all the storage containers 211 and 221 on the shelf by setting an addition port at one location on the shelf and homogenizing the environment, the shelf is equipped with an addition port, a lighting device, and a temperature sensor at any position on the shelf. When addition is selected by operating the operating electronic device or by a signal from the user, an addition algorithm is generated, and the storage containers 211 and 221 are rotated by the rotation of the rotating shelf 20, so that all the containers on the shelf are aligned to the addition port at one location and stopped at the addition port position. When a substance is added to the storage containers 211 and 221, and when it is selected to equalize the environment (temperature) within the shelf to all the storage containers 211 and 221 by operating the operating electronic device or by a signal from the user, an environment equalization algorithm 701 is generated, the required number of rotations of the rotating shelf 20 per hour is determined, and environment (temperature) equalization is performed to all the storage containers 211 and 221 within the shelf by positioning the lighting device and the temperature sensor at any one location and stopping the rotating shelf 20 at the top of the rotating shelf.

[0064] To achieve such functionality, the shelf robot may optionally include the following configuration, as shown in Figure 7.

[0065] As a component for controlling the rotation and stopping of the rotating shelf 20 that stores the stored items or the storage containers 211, 221, depending on whether gravity is influencing it or not, a rotation and stopping device is provided for rotating and stopping the rotating shelf 20. When the rotation and stopping of the rotating shelf 20 is selected to be influenced by gravity by the operation of the operating electronic device or the signal of the user, a stop control algorithm 651 is generated, and the storage containers 211, 221 on the shelf are influenced by gravity and maintain their horizontal position. Next, when the rotation and stopping of the rotating shelf 20 is selected to be unaffected by gravity by the operation of the operating electronic device or the signal of the user, the stop control algorithm 651 is generated, the shelf becomes horizontal and unaffected by gravity, and work at the bottom of the stored items and the storage containers can be performed stably while standing or sitting.

[0066] Furthermore, as a component for the forward / backward movement of the stored items or the storage containers 211, 221, the storage containers 211, 221 or the bottom of the stored items are provided with the forward / backward moving plate 24. The loading and unloading of the stored items or the storage containers 211, 221 is performed by operating the operating electronic device or by a signal from the user, which generates a height control algorithm 661 that includes a function to detect the stored items and a function to move the moving plate 24 forward / backward. The loading and unloading of the stored items or storage containers 211, 221 is performed by the rotation of the rotating shelf 20, and when the rotation stops, the forward / backward moving plate 24 moves the stored items or storage containers 211, 221 forward to a height or position that is easy to access before loading or unloading them, and moves them backward by the forward / backward moving plate 24 after loading or unloading the stored items or storage containers 211, 221.

[0067] Furthermore, a weighing scale 673 is provided as a component for measuring the weight of the stored items or the storage containers 211 and 221, and is installed at the bottom of the storage containers 211 and 221 located at the lowest part of the shelf. The weight measurement by the weighing scale 673 at the bottom of the storage container is performed when a weight measurement algorithm 671 is generated by the operation of the operating electronic device or by a signal from the user set by the user's identification. The storage containers 211 and 221 rotate as the rotating shelf 20 rotates, and they rotate and stop at the location where the weighing scale 673 is installed. When the storage containers 211 and 221 float by pulling the rope connected to them, which is suspended at the stopping point, the weighing scale 673 is installed at the bottom of the storage containers 211 and 221. When the rope is released, the weight of each storage container 211 and 221 is corrected by the deflection of the scale or numerical value on the weighing scale 673 and the image of the deflection of the storage containers 211 and 221, and the weight is recorded in the central computer.

[0068] Furthermore, tilting points 683 are provided on the storage containers 211 and 221 as components for adjusting the amount of liquid contained in the stored items or storage containers 211 and 221 that contain liquid. A liquid volume adjustment algorithm 681 is generated by the operation of the operating electronic device or by a signal from the user set by the user's identification. If the storage containers 211 and 221 or the stored items contain liquid, the liquid volume is adjusted by pulling a rope on one side connected to the containers 211 and 221 suspended from the tilting points 683, thereby tilting the storage containers 211 and 221 or the stored items either forward or backward relative to the front, and the liquid volume is adjusted based on the resulting image.

[0069] Furthermore, a horizontal rotating plate 693 is provided at the bottom of the storage containers 211 and 221 as a component for the horizontal rotation of the stored items or the storage containers 211 and 221. The horizontal rotation algorithm 691 is generated by the operation of the operating electronic device or by a signal from the user, and one horizontal rotation is performed to adjust the orientation of the storage containers 211 and 221 relative to the front by rotating the horizontal rotating plate 693 to reverse the forward-facing orientation to the backward-facing orientation, or the storage containers 211 and 221 are rotated horizontally and stopped horizontally every 90 degrees by 360-degree viewpoint conversion in order to capture images of all four faces or four compartments of the cube.

[0070] Furthermore, to ensure that the addition of a substance to the storage containers 211 and 221 at one location within the shelf and the resulting uniformity of the environment are reflected in all the storage containers 211 and 221 within the shelf, the storage containers 211 and 221 located at the top of the shelf are equipped with an addition port, a lighting device, and a temperature sensor. When addition is selected by operation of the control electronic device or by a signal from the user, an addition algorithm is generated, and the substance is added to the contents of all the storage containers 211, 221 on the shelf, which are linked to the placement of the addition port at one location and stopping at the addition port position. When environmental homogenization is selected by operation of the control electronic device or by a signal from the user, an environmental homogenization algorithm 701 is generated, and the number of rotations of the rotating shelf 20 per hour is determined according to the use of the shelf. As the storage containers are circulated by the rotation of the rotating shelf 20, the environment (temperature) is homogenized within the shelf to all the storage containers 211, 221 on the shelf by the placement of the lighting device and the temperature sensor at one location and the stopping of the rotating shelf 20 at the top of the rotating shelf.

[0071] Furthermore, to shorten the distance and time required to move to the storage containers 211 and 221, the bottom of the shelf is provided with a linear movement base plate and a linear movement device. When multiple shelves are installed, the entry and exit points for loading and unloading stored items from the shelves are located at either the left end, center, or right end. On the other hand, the recognition points for recognizing information about the stored items are also located at either the left end, center, or right end. This means that the entry and exit points and the recognition points are in different locations at the left end, center, and right end due to rotation, resulting in multiple movements from shelf to shelf in the conventional method. If the shelves are close together, it may be impossible to reach the retrieval position. In contrast, with the aforementioned shelves, even if multiple shelves are close together, the retrieval position can be reached in a single movement. By positioning the shelves at an inclined angle (e.g., 45 degrees) with the entrance behind the user and the direction of travel to the entry and exit points, or by positioning them so that the starting point of travel is a straight line movement from left to right on the shelf with the direction of travel behind the user, the entry and exit points for the user or the transport vehicle do not overlap, resulting in the shortest possible travel distance to the storage containers 211, 221 or the stored items, and reducing the space between shelves.

[0072] Furthermore, as components for identifying the user and controlling the height of the stored items, the system is equipped with an external image capture device (camera) that captures an image of the user in order to identify the user's individual characteristics (face, build, and signals), an internal image capture device (camera) that captures an image of the stored items within the shelf, and an image capture device (camera) that captures an image of any space other than the shelf. A full-body image is taken, and the face, physique (height to the shoulders and arm length), and a signal are extracted from the image by instructions via the central computer. When a feature is selected by operation of the control electronic device or by a signal from the user, a feature algorithm is generated to characterize the face, physique, and signal from the full-body image, respectively. After matching the user, the user is identified using the three images. When the user searches for the type of stored item, an elevation control algorithm 661 is generated, which includes searching for the storage space and detecting whether the item has been moved to a different storage container or to the location of the label. The rotating shelf 20 is rotated and moved so that the position from which the stored item is loaded or unloaded is within the user's field of view (for example, within approximately 70 cm to the left, right, up, and down of the object for a distance of 1 m from the object) or within the retrieval range, without any up, down, left, right, or left or right movement of the head and trunk in the user's physique and standing or sitting position, and the stored item is loaded or unloaded.

[0073] Furthermore, the system includes a transport instruction device, coding technology (label reader) for the transport instruction device, an image capture device (camera) for photographing the route to determine the route of the transport vehicle, a transceiver that enables network connection between the central computer and the transport vehicle, a forward and backward moving plate 24 for the storage containers 211 and 221 located at the bottom of the storage containers 211 and 221, a bottom plate (pallet) for determining the position into which the forks of the transport vehicle are inserted, and a pallet bottom plate for recognizing the pallet position. Instructed via the central computer, the transporter's movement is controlled by the operation of the control electronic device or by a signal from the user, and the transporter moves based on the calculation of the distance and position between the transporter and the shelves through triangulation image analysis of the image captured by the camera installed on the stand. For the operation of inserting items into pallets, the operation of the control electronic device or by a signal from the user is controlled by the fork insertion position algorithm, which determines the height position to insert the items into the pallets. Information on the height positions of the storage containers 211 and 221, calculated from the image captured by the image capture device (camera) inside the shelves, is wirelessly transmitted to the transporter, and loading and unloading of items up to a height of 3m where the pallet position is outside the operator's field of view is performed on all connected shelves via the central computer.

[0074] Furthermore, as a component for identifying the operator in operations on the stored items or the storage containers 211 and 221 without the need for paper documents, an off-shelf camera that photographs the user is provided. The identification of the operations on the stored items is performed by generating a location information analysis algorithm from the captured images in accordance with standards (GXP) established by government and other public institutions to ensure the reliability of operations regarding who performed what and when. This allows the operator of the shelf in which the operation was performed to be identified, and thus the identification of the person in charge is performed electronically via a network connection, similar to how the identification of the person in charge was previously done using paper documents.

[0075] Next, we will describe some examples of shelf robots that utilize the basic shelf structure described above.

[0076] (Example 1; Bookshelf Robot) Conventional bookshelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that while it is known that library users do not always return books to the same place they took them, the lack of organization is not detected when users return stored items. The second problem is the high burden it places on users; the larger the scale, the more time and effort it takes for users to find and retrieve books, and the greater the effort and burden required for inventory management or rearrangement. The third problem is that artificial intelligence has not been used to solve the above problems for all shelves. In addition to the above, shelves that can store items of various sizes according to their size are not yet commonplace.

[0077] The bookshelf robot according to an embodiment of the present invention comprises the basic shelf structure, a retrieval position located on the front of the front panel, a storage container (bookcase) suspended in the storage space from the suspension points of the rotating shelf located on the front and rear wheels, a component for identifying the user and controlling the height of the stored items, a component for transporting the stored items or storage container, a component for moving the stored items or storage container forward / backward, a component for shortening the travel distance and travel time of the stored items or storage container, and the water of the stored items or storage container. The system is equipped with components for horizontal rotation, and the means for this include identifying users (book users or library visitors) using a characterization algorithm, identifying stored items using a stored item characterization algorithm, transporting the stored items by a transport vehicle using the aforementioned driving algorithm, loading and unloading by users using the aforementioned height control algorithm, horizontal rotation using the aforementioned horizontal rotation algorithm for 360-degree viewpoint, detection of dynamic objects using the aforementioned position information analysis algorithm, and detection of disorganization using the aforementioned position information analysis algorithm.

[0078] The library robot ensures that all of its storage container areas are easily accessible, allowing users to set the retrieval position of stored items according to their needs. Assuming that each bookshelf has two shelves sufficient to hold A4-sized books, and that the height / width and depth of each storage container are 70cm / 70cm and 35cm respectively, the ratio of easily accessible storage containers to floor space indicates that five storage units can be stored in the space of one flat floor. The minimum ground clearance for shelves with only one layer (shelves 1 and 2), shelves with two layers (shelves 3 and 4), and shelves with three layers are 0m, 70cm, and 1.4m, respectively. Shelf heights range from approximately 1m to 5.08m, and users, including children and wheelchair users, can utilize shelves up to the third layer.

[0079] [Table 1]

[0080] [Table 2]

[0081] [Table 3]

[0082] Disorganization can be detected by recognizing and matching stored items to register and record specific information (quantitative and qualitative). If there is a mismatch, image analysis (location information) can be used to indicate whether the placement of stored items is interfering with the label reader's reading, thereby detecting disorganization. The burden on users can be reduced by identifying and matching users, checking history and inventory management status during daily management, and providing user-friendly receiving and transport services through height control of storage containers. This reduces the burden of registration and updating during inventory or daily management, as well as the burden on users during loading and unloading.

[0083] (Example 2; Prescription pharmacy shelf robot) Conventional prescription pharmacy shelving has three problems in addition to the lack of height control to manage the height of stored items. The first problem is that it is not possible to detect disorganization after staff have moved items in and out. The second problem is the high burden on users, stemming from the burden of managing a large inventory and updating drug information from suppliers. The third problem is that artificial intelligence is not being used to solve the above problems for all shelves. There are three waiting times between hospitals and prescription pharmacies. The first waiting time is the time it takes for the pharmacist at the prescription pharmacy to verify the prescription issued by the hospital doctor, which can be an important step. The second waiting time is the time it takes for the pharmacist to dispense the medication after the patient hands over the prescription. The third waiting time is the time it takes to find the prescribed medication among the many medications stored at the prescription pharmacy. Artificial intelligence is not being used to shorten the above waiting times. In addition to the above, shelving that can store various items according to their size and storage conditions (room temperature, refrigerated, frozen) is not yet commonplace.

[0084] The prescription pharmacy shelf robot according to an embodiment of the present invention comprises the basic shelf structure, the storage item label structure, the user identification and height control of the storage items, the horizontal rotation of the storage items or storage containers, the identification of the worker in the storage items or storage containers without paper media, and storage containers (drug boxes) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels. The means include the identification of the user (pharmacist or prescription pharmacy staff) by the characterization algorithm, the identification of the storage items (drugs) by the storage item characterization algorithm, the loading and unloading of storage items by the user by the height control algorithm, the horizontal rotation of the storage containers by the horizontal rotation algorithm for 360-degree viewpoint, network connection between the hospital and the prescription pharmacy, detection of dynamic objects by the position information analysis algorithm, and detection of disorganization by the position information analysis algorithm.

[0085] The prescription pharmacy shelving robot ensures that all storage container areas are easily accessible, allowing users to set the retrieval position of stored items. Assuming that storage containers are arranged in two tiers using dividers, and assuming storage container heights / widths and depths of 40cm / 40cm and 20cm respectively, the ratio of easily accessible storage containers to floor space indicates that two to six containers can be stored in the space of one flat floor. The minimum ground clearances for the first, second, third, and fourth shelves are 0m, 40cm, 0.8m, and 1.2m, respectively, and the height of the rotating shelves allows for shelves ranging from 0.8m to 5.48m.

[0086] [Table 4]

[0087] [Table 5]

[0088] [Table 6]

[0089] [Table 7]

[0090] The detection of disorganization involves the registration and history of specific (quantitative and qualitative) information, and image analysis (location information) can reveal whether the placement of stored items is obstructing the reading of label readers. The high burden on users lies in checking the history and inventory status during daily management and transportation during inventory counts. This burden can be reduced by mutual verification between hospital doctors and pharmacists at dispensing pharmacies via internet connection, the task of finding prescribed medications among the many medications stored at the dispensing pharmacy, accurate inventory management and supplier drug information, and setting the location of easily accessible places at different heights for users to load and unload items.

[0091] (Example 3: Robot for managing medical products in a hospital) Conventional hospital medical product storage shelves have three problems in addition to the lack of height control to manage the height of stored items (pharmaceuticals, medical devices, medical equipment, and medical consumables). The first problem is the detection of disorganization of stored items, as it is not possible to detect disorganization after users have moved items in and out. The second problem is the high burden on users. Users of hospital medical products (pharmaceuticals, medical devices, medical equipment, and medical consumables) are multiple users within the hospital who are busy with their daily duties and paying attention to medical errors while moving items in and out. Although electronic storage shelves for managing multiple medical products are useful, the use and management of stored items are burdensome because different labels are attached to products from different manufacturers. This information is diverse, such as manufacturer, lot number, drug price, barcode, specifications, and expiration date, and consists of a large amount of information. This information changes rapidly with the release of new products, and solving the burden of managing all of this information is a challenge. The third challenge is that artificial intelligence is not being used to solve the aforementioned problems for all shelves, both within the hospital (each area of ​​warehouses, each patient, each room, each ward) and with external parties outside the hospital (pharmaceutical companies conducting clinical trials, medical supply suppliers, prescription pharmacies). In addition to the above, shelves that can accommodate items of various sizes according to their size are not yet commonplace.

[0092] The hospital medical product management shelf robot according to an embodiment of the present invention comprises the shelf basic structure, a component for the forward / backward movement of the stored items or storage containers, a component for user identification and height control of the stored items, a component for transporting the stored items or storage containers, a component for the forward / backward movement of the stored items or storage containers, the basic structure, a component for horizontal rotation of the stored items or storage containers, a component for identifying the worker in the stored items or storage containers without paper media, a storage container (medical product box) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels, and the storage The system is equipped with a component for identifying an object or worker in the storage container without the use of paper media, and the means include identifying the user (hospital user) by a characterization algorithm, identifying the stored object (hospital medical product) by a stored object characterization algorithm, transporting the stored object by a transport vehicle by a driving algorithm, loading and unloading the stored object by the user by a height control algorithm, horizontal rotation by a horizontal rotation algorithm for 360-degree viewpoint, network connection to the inside and outside of the hospital, detection of dynamic objects by a position information analysis algorithm, and detection of disorganization by a position information analysis algorithm.

[0093] The hospital medical product management shelving robot ensures that all storage container areas are easily accessible, allowing users to set the retrieval position of stored items. Assuming two layers of medical product boxes, and assuming the width / length and depth of the storage containers are 70cm and 35cm respectively, the ratio of easily accessible storage containers to floor space indicates that two to five boxes can be stored in the space of one level floor. The minimum ground clearance for the first layer only (shelf numbers 1 and 2), the shelves up to the second layer (shelf numbers 3 and 4), and up to the third layer is 0m, 70cm, and 1.4m, respectively, and rotating shelves with diameters ranging from approximately 1.4m to 5.04m can be used.

[0094] [Table 8]

[0095] [Table 9]

[0096] [Table 10]

[0097] Detecting disorganization and tidiness involves registering and recording specific (quantitative and qualitative) information, revealing whether the placement of stored items is obstructing the reading of label readers. In an environment where multiple users within a hospital are busy with their daily duties and paying attention to medical errors while handling stored items, the burden of managing information such as manufacturer-specific labels affixed to products, which consist of a lot of information including manufacturer, lot number, drug price, barcode, specifications, and expiration date, can be reduced. The burden of use can be reduced through registration, updating, and inventory management, user-centered receiving, inventory management of consumables, and daily burdens between various departments within the hospital and external parties outside the hospital (pharmaceutical companies conducting clinical trials, medical supply suppliers, prescription pharmacies).

[0098] (Example 4; Diagnostic, therapeutic, and surgical robot) Conventional diagnostic, treatment, and surgical shelving systems have three main drawbacks, in addition to the lack of height control for managing the height of stored items. The first is the difficulty in detecting disorganization of stored items, as this cannot be detected after staff have moved items in and out. The second is the high workload. Surgical procedures and cellular-level diagnosis and treatment require accurate work in a short amount of time. Within this necessity, the selection and retrieval of drugs and surgical instruments must also be accurate and rapid. Furthermore, while human anatomy is depicted in anatomical atlases in textbooks, there are variations in anatomical, physiological, and pathological features among individual patients, and diagnosis, treatment, and surgery must be performed taking these variations into consideration. Performing diagnosis and treatment at the cellular level in real time and in a continuous manner is difficult, and for example, in recent years, the Convection-Enhanced Delivery (CED) method using nanoparticles has been proposed. This is a cell therapy that diagnoses and treats only tumor cells without affecting normal cells, unlike brain tumor treatment where the impact on normal cells directly leads to death. After bone resection of the brain, it becomes possible to perform cellular-level surgical diagnosis and treatment by administering nanoparticle nuclear magnetic resonance (MRI) contrast agents, confirming convection to brain tumor cells with MRI contrast images, and then intervening with nanoparticle-sized anticancer drugs. However, the operation of this surgical diagnosis and treatment is on a micrometer or nanometer scale, making it difficult to perform with the naked eye and human hands. Furthermore, while contrast enhancement by nuclear magnetic resonance produces a nonspecific image of the whole body due to water molecules, intravascular administration of gadolinium contrast agent results in intravascular convection, and there is a phenomenon (EPR effect) where macromolecules convect and accumulate in cancer blood vessels surrounding the cancer. However, cellular-level analysis after dispersive image extraction on a micrometer or nanometer scale using artificial intelligence has not been performed. The third challenge is that it is important to respond to time-series events that may change at the cellular level in diagnosis, treatment, and surgery in emergency medical settings such as surgery, and artificial intelligence is not being used to solve all of the above challenges. In addition to the above, shelves that can store items of various sizes according to their size and can be used for the aforementioned surgical diagnosis and treatment methods are not yet common.

[0099] The diagnostic, therapeutic, and surgical shelf robot according to an embodiment of the present invention comprises: the basic shelf structure; the storage item label structure; the user identification and height control of the storage items; the forward / backward movement of the storage items or storage containers; the identification of the worker in the storage items or storage containers without the use of paper media; storage containers (diagnostic, therapeutic, and surgical tool boxes) suspended within the storage space from suspension points of a rotating shelf located at the front and rear wheels; a three-dimensional image projector (e.g., hologram) for projecting standard anatomical diagrams; a lesion magnification device for displaying magnified images of the affected area of ​​a patient; and shelf accessories. The system includes an image capture device (camera) for capturing images of the patient's affected area, and a magnetic resonance imaging (MRI) device (MRI machine) for contrast enhancement of the patient's affected area. The means include identifying the user (physician or medical professional) using a characterization algorithm, identifying stored items (diagnostic, therapeutic, and surgical instruments) using a stored item characterization algorithm, loading and unloading by the user using the height control algorithm, network connection with the magnified images of the patient's affected area, detection of gadolinium metal in the images by the MRI machine using the dispersible substance extraction algorithm, and detection of disorganization using the position information analysis algorithm.

[0100] The diagnostic, treatment, and surgical shelving robot ensures that all of its storage container areas are easily accessible, allowing users to set the retrieval position of stored items according to their needs. Assuming a medical product box as one shelf, the total easily accessible storage area per floor area, with the width / length and depth of each container being approximately 40cm / 40cm, shows that it is possible to store two to five easily accessible storage containers in the space of one flat floor. The minimum ground clearances for the first, second, and third layers are 0m, 0.4m, 0.8m, and 1.2m, respectively, and the diameter of shelves usable by adults is approximately 2.2m to 2.9m.

[0101] [Table 11]

[0102] [Table 12]

[0103] Table 13

[0104] Table 14

[0105] Detecting disorganization involves registering and recording specific (quantitative and qualitative) information, or using image analysis (location information) to determine if the placement of stored items is obstructing the label reader. The high burden on users can be reduced through registration, updating, and inventory management, user-centered receiving, and confirmation of standard and 3D images of the patient's affected area from the perspectives of two surgeons. Furthermore, while human anatomy has a general form as presented in textbooks, there are variations in anatomical, physiological, and pathological features among individual patients. Considering these variations, surgical procedures performed by two surgeons with different field of view orientations will utilize different orientations for video support. 360-degree treatment is possible by projecting a 3D image representing the standard anatomical diagram of the surgical site and comparing it with magnified surgical images of the patient's affected area during surgery. Most of the products used in diagnostic, therapeutic, and surgical shelves are kept in a sterile environment. Surgical instruments are arranged in storage containers for quick retrieval, and depending on the surgical situation, surgeons can adjust the height of the retrieval door to be easily accessible whether standing or sitting, using a rotating shelf. By having two retrieval doors on the left and right, it is possible to provide standard and patient-specific image support (image support tailored to the field of view) that is suitable for each surgeon's field of view, even when two surgeons are working together. Images outside the shelf are images of gadolinium metal. If the nanoparticles after administration of the diagnostic drug, which is polymer gadolinium metal-bound nanoparticles, are bound and decomposed polymer bounds, then their dispersibility should be on the nanoscale or micrometer scale. The dispersibility of the administered nanoparticles should be different from that after conventional administration of low molecular weight gadolinium metal, and it is expected that the dispersibility will be different after intravascular administration compared to conventional administration of low molecular weight gadolinium metal. On the other hand, intravascular administration of nanoparticles is expected to lead to the accumulation of polymeric substances around cancer cell aggregates. If the nuclear magnetic resonance images of the gadolinium metal nanoparticles and their polymer conjugates are generated using a dispersive extraction algorithm, it would be possible to identify abnormal areas around cancer cell aggregates and demonstrate the phenomenon of polymers accumulating in the cancer blood vessels surrounding the cancer (EPR effect), resulting in detailed images linked to the progression and severity of the cancer.On the other hand, the convection-enhanced delivery (CED) method using nanoparticles allows for cellular-level diagnosis, treatment, and surgery targeting only abnormal cells without affecting normal cells, and subsequent evaluation of treatment effectiveness can be done at the cellular level. Furthermore, it becomes possible to address time-series events that may change at the cellular level in the aforementioned diagnosis, treatment, and surgery, even in emergency medical settings such as surgery.

[0106] (Example 5; Room temperature indoor warehouse shelving robot and refrigerated / frozen indoor warehouse shelving robot) Conventional indoor warehouse shelving and refrigerated / frozen indoor warehouse shelving are mainly used in research laboratories, factories, warehouses, and transportation facilities. They involve both human and transporter handling of loading and unloading, and have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that the storage height is not set to a level that is easy for transporters to load and unload. Although forklifts are stipulated to be able to lift up to a standard lifting height of 3m or 3.3m, the operator can only confirm that the forks are horizontally inserted into the pallet from their seat at a height of about 2m, and the operator has to repeatedly try and fail to precisely insert the forks into the pallet. Furthermore, there are no shelves that can handle transportation between locations with different heights (between transport trucks and warehouse shelving, or between the ground and ships). The second problem is that it is not possible to detect disorganization after the person in charge has loaded or unloaded the items. This disorganization is due to the fact that the position (height and width) of the forks at the bottom of the incoming goods is not remembered, and this position memory is not utilized for the next shipment. The third challenge is the high workload. Warehouse work in research laboratories, factories, and transportation facilities primarily involves the use of forklifts and the repeated loading and unloading of goods onto multi-tiered shelves. This work requires precise visual work and attention to safety. In many cases, multiple workers perform multiple loading and unloading operations, requiring concentration and skill from these workers. When multiple workers perform multiple loading and unloading operations, avoiding collisions between transport vehicles and efficiently executing planned loading and unloading schedules becomes a high workload. Furthermore, the working environment in refrigerated and frozen warehouse shelves, where items requiring strict temperature control (e.g., green and yellow vegetables) are kept under strict temperature conditions, is harsh. Even with cold weather precautions, the loading and unloading operations in these environments are extremely demanding, resulting in a high workload. The third challenge is that artificial intelligence is not being used to solve the above challenges for all shelves. In addition to the above, shelves that can accommodate items of various sizes according to their size are not yet commonplace.

[0107] The room temperature indoor warehouse shelf robot and the refrigerated / frozen indoor warehouse shelf robot according to the present invention include the basic shelf structure, the storage item label structure, the user identification and height control of the storage items, the transport of the storage items or storage containers, the forward / backward movement of the storage items or storage containers, the structure for reducing the travel distance and travel time to the storage items or storage containers, and storage containers (loads or manufacturing raw material boxes) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels, and the means are characterized by an algorithm This includes identifying the user (transporter or person in charge) using SUM, identifying the stored items using a stored item characterization algorithm, transporting the stored items by a transport vehicle using a driving algorithm, rearranging the stored items, loading and unloading by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewpoint, homogenizing the environment between storage containers within the shelves using an environment homogenization algorithm, shortening the transport distance through shelf arrangement, detecting dynamic objects using a position information analysis algorithm, and detecting disorganization using a position information analysis algorithm.

[0108] Furthermore, the components for transporting the stored items or storage containers include a transport vehicle internal packing indicator device, a transceiver that enables network connection between the transport vehicle internal packing indicator device and the operating electronic equipment, a label reader and image capture device using code technology installed on the transport vehicle internal packing indicator device, an image capture device (camera) that photographs the route to determine the transport vehicle's route, a transceiver that enables network connection between the central computer and the operating electronic equipment and the transport vehicle, and the storage container's front and rear moving plates and bottom plate (pallet) located at the bottom of the storage container. The position in which the transport vehicle's forks are inserted into the pellets is determined by reading the code installed on the front and rear moving plates or by image recognition by the camera, and for the transporter's movement, a driving algorithm is generated in which the distance and position between the transport vehicle and the shelf are calculated by triangulation image analysis of the image captured by the camera installed on the stand, based on the operation of the operating electronic equipment or the user's signal, and the transporter moves accordingly. For the operation of inserting items into pallets, a fork insertion position algorithm is generated, and information on the height and depth of the storage containers, calculated from images captured by the image capture device (camera) inside the shelf, is wirelessly transmitted to the transport vehicle via the central computer. A height control algorithm is then generated to determine the height and depth at which the loads are inserted into the pallet, based on instructions from the central computer, at a height that is outside the operator's field of vision. As a result, after the forks are inserted into the pallet, the forward and backward moving plate moves forward, the inserted forks reach their deepest point, and a collaborative operation is achieved in which the lifting operation can be completed in a single step.

[0109] The room temperature indoor warehouse shelving robot or the refrigerated / frozen indoor warehouse shelving robot is designed to store containers in a single layer without partitions. Assuming the height / width and depth of the storage containers are the same as JIS standard pallets (1.1m x 1.1m), and the width / length and depth of the storage containers are 1.1m / 1.1m and 1.1m, respectively, it was shown that the ratio of easily accessible storage containers to floor area allows for the storage of two to five containers in a space equivalent to one level of flat ground. The minimum ground clearance of the shelves for the first, second, and third layers during loading and unloading between ground levels is 0m, 1.1m, and 2.2m, respectively. Since the position of the pallet bottom plate on the third layer is approximately 2.2m, it is possible to unload up to 6-8m (shelf numbers 5-6) at the standard lifting height.

[0110] [Table 15]

[0111] [Table 16]

[0112] [Table 17]

[0113] The detection of disorganization results in the registration and history of specific (quantitative and qualitative) information, making inventory management easier. The high burden of use can be reduced by utilizing artificial intelligence to handle registration, updates, and inventory management, user-centric receiving, reducing the burden of transportation work by requiring only one forklift insertion, the burden of inventory management of consumables on all shelves via network connection, and the risk of collisions between multiple transport vehicles.

[0114] (Example 6; Step-Moving Shelf Robot) Conventional adjustable shelving units are primarily used as platforms for scaffolding construction work, where workers move construction materials between different heights on construction sites. However, they lack height control to manage the height of stored items and have three main drawbacks. The first is the inability to detect the disorganization of stored items after users have loaded and unloaded them. This disorganization stems from the fact that the positions of materials placed on the shelves are not memorized, meaning their location is not utilized in subsequent tasks. The second is the high burden on workers. High-altitude construction work begins with scaffolding construction, followed by the task of workers transporting materials to the scaffolding and work site, as well as work within the work site itself. This involves the risk of falls from the scaffolding and work site, while also making it difficult to set the scaffolding to various heights and lateral positions to accommodate the shape of the building, thus imposing a difficult task on workers. The third is the lack of artificial intelligence to address the above issues for all shelving units. In addition to the above, shelving units capable of storing items of various sizes according to their dimensions are not yet commonplace.

[0115] The step-moving shelf robot according to an embodiment of the present invention comprises the shelf basic structure, the storage item label structure, the user identification and height control of the storage items, the transport of the storage items or storage containers, the forward / backward movement of the storage items or storage containers, the structure for shortening the travel distance and travel time to the storage items or storage containers, and storage containers (loads or manufacturing raw material boxes) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels. The means include identifying the user (person in charge) by a characterization algorithm, identifying the storage items by a storage item characterization algorithm, rearranging the storage items, loading and unloading by the user by a height control algorithm, and detecting disorganization by a position information analysis algorithm.

[0116] Furthermore, the system may be equipped with a camera for capturing images of users inside and outside the shelves, and an audio listener 38 for listening to sounds around the shelves, as components for exploring the safety of users inside and outside the shelves. A standard voice of the user emitted around the shelves is identified in advance from listening to the user's voice, a safety exploration algorithm is generated at the work site, sentiment analysis is performed from the transcription of the voice emitted by the user while working, a hazard analysis is performed from images of the environment around the shelves (weather such as rain and wind), and safety is explored and reported based on the sentiment analysis and the hazard analysis.

[0117] The stepped shelving robot is designed to store items in storage containers on a single level without partitions. The height / width and depth of the storage containers are not necessarily assumed to be forklift-loaded, but assuming they are JIS standard pallets (1.1m x 1.1m), and the width / length and depth of the storage containers are 1.1m / 1.1m and 1.1m respectively, it was shown that the ratio of easily accessible storage containers to floor area allows for the storage of two to five containers in the space of one level floor. The minimum ground clearance of the shelves for the first, second, and third layers during loading and unloading between ground levels is 0m, 1.1m, and 2.2m, respectively. Since the pallet bottom plate of the third layer is at approximately 2.2m, it is possible to unload items up to 6-8m (shelf numbers 5-6).

[0118] [Table 18]

[0119] [Table 19]

[0120] [Table 20]

[0121] Detecting disorganization and tidiness can lead to the registration and history of specific (quantitative and qualitative) information, or reveal whether the placement of stored items is interfering with the reading of label readers. High burden on users can be identified as factors that affect the risk of falls during work on scaffolding and at work sites, thereby reducing the risk of falls.

[0122] (Example 7; Flying object shelf robot) Conventional projectile racks are not widespread. While large-scale operations are often advantageous for maximizing productivity in outdoor agricultural production, the terrain of outdoor farmland can be sloping. Therefore, it is necessary to monitor the type, location, and number of harmful animals to minimize damage to crops, including the application of seeds or chemicals (fertilizers and pesticides) to the entire field, plant maintenance, and culling of harmful animals. Performing these tasks on vast farmlands, including sloping areas, without projectiles is not easy. A rack is needed that allows for the launch and landing of the projectiles and facilitates their maintenance. In addition to lacking height control to manage the height of stored items, the projectile rack has three problems. The first problem is that it is not possible to detect the disorganization of the projectiles and their maintenance equipment and materials after launch and landing. The second problem is that it is burdensome, and the normal launch position of the projectiles may require daily maintenance (oil changes, cleaning the bottom of the projectiles, etc.) to be performed in an upside-down position, making it difficult to facilitate such maintenance. The third challenge is that artificial intelligence is not being used to solve the aforementioned problems for all shelves.

[0123] The flying object shelf robot according to an embodiment of the present invention comprises, as components for transporting the stored object (flying object), the shelf basic component, the stored object label component, the user identification and height control of the stored object, the forward / backward movement of the stored object or the storage container, the components for shortening the distance and time of movement to the storage container, the storage container (flying object takeoff and landing equipment) suspended in the storage space from the suspension points of the rotating shelf located at the front and rear wheels, the flight instruction device, the flight instruction device with a label reader in code technology, the transport instruction device with a label reader in code technology, the transport instruction device with an image capture device (camera) installed to photograph the air path in order to determine the flight path of the flying object, the transceiver enabling network connection between the central computer and the flying object, and the storage container for storing the flying object, with a forward / backward movement plate for the storage container and a bottom plate (p) at the bottom of the storage container for storing the flying object that serves as a guide for determining the fork insertion position at the bottom of the flying object. The system is equipped with a fork insertion algorithm, which includes identifying the user (person in charge) using a characterization algorithm, identifying the stored items using a stored item characterization algorithm, loading and unloading by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewing, shortening the transport distance by the shelf arrangement, detecting dynamic objects using a position information analysis algorithm, and detecting disorganization using a position information analysis algorithm. The system is equipped with a fork insertion algorithm that, upon instruction via the central computer, calculates the distance and position between the flying object and the shelf by triangulation image analysis of the image captured by a camera installed on the stand based on the operation of the control electronic equipment or a signal from the user, and transports the flying object. The system is equipped with a fork insertion algorithm that, upon instruction via the central computer, calculates the height position to insert into the pallet, and loading and unloading operations of the flying object are performed on all net-connected shelves. The storage containers for housing the aforementioned projectiles may be equipped with a detachable device for exchanging each storage container with another.

[0124] The flying object shelving robot is designed to be stored in a single-tier storage container without partitions. Assuming the height / width and depth of the storage container are based on a JIS standard pallet (1.1m x 1.1m), the shelves will be approximately 2.2m to 8m in length. The ratio of easily accessible storage containers to floor space is such that, assuming the width / length and depth of the storage containers are 1.1m and 1.1m respectively, it is possible to store two to five easily accessible storage containers in the space of one level floor. The minimum ground clearance of the first, second, and third layers for loading and unloading between ground levels is 0m, 1.1m, and 2.2m, respectively. Since the pallet bottom plate of the third layer is at approximately 2.2m, it is possible to unload items at a standard lifting height up to 6-8m (shelf numbers 5-6).

[0125] [Table 21]

[0126] [Table 22]

[0127] [Table 23]

[0128] The detection of disorganization results in the registration and history of the identification (quantitative and qualitative information) of the stored items, making it possible to clarify the inventory management of flying objects on all shelves. Furthermore, it makes it easier for flying objects to avoid collisions with natural obstacles, artificial obstacles, and birds after flight. The high burden of use can be reduced by adopting a user-centered receiving system. By making it possible to use it for daily maintenance work, the burden of maintenance management can be reduced.

[0129] (Example 8; Motorcycle parking and car parking shelf robot) Conventional motorcycle and automobile parking facilities have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that they are difficult to use for daily maintenance work (oil changes, cleaning the underside of the vehicle, etc.), as normal ground parking positions require maintenance work to be done in a supine position, making it difficult to perform the aforementioned maintenance work. The second problem is that they cannot detect the disorganization of stored items. This results in a high theft risk because there are insufficient measures to prevent theft of stored items. The third problem is that they are burdensome, and ease and speed of loading and unloading are important. When parking forward upon entry and reversing upon exit, 180-degree rotation to facilitate quick exit is not common. The third problem is that artificial intelligence is not used to solve the above problems for all shelves. In addition to the above, shelves that can store items of various sizes according to their size are not common.

[0130] The parking shelf robot for two-wheeled and four-wheeled vehicles according to an embodiment of the present invention comprises the shelf basic structure, the storage item label structure, the user identification and height control of the storage items, the forward / backward movement of the storage items or storage container, the horizontal rotation of the storage items or storage container, the gravity-independent rotation stopping of the storage items or storage container, and the storage container inside the suspended container (individual parking space) suspended within the storage space from the suspension points of the rotating shelf located at the front and rear wheels, and The means include identifying the user (driver) using a characterization algorithm, identifying the stored items (two-wheeled and four-wheeled vehicles) using a stored item characterization algorithm, loading and unloading by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewpoint, vehicle inspection by the user by stopping the rotation of the stored items or storage containers without gravity using a stop control algorithm, detection of dynamic objects using a position information analysis algorithm, and detection of disorganization using a position information analysis algorithm.

[0131] The motorcycle parking shelf robot ensures that all storage container areas are easily accessible, allowing users to set the retrieval position of stored items. Assuming the height / width and depth of the storage containers are 2.2m / 2.2cm and 2.2m, respectively, the ratio of easily accessible storage containers to floor area indicates that two to four motorcycles can be stored in a space equivalent to one level. The ground clearance of the first, second, and third layers is 0m, 2.2m, and 4.4m, respectively. Therefore, for entry and exit between ground levels, only the first layer allows entry and exit without steps, while the second and third layers require design considerations for steps. On the other hand, for entry and exit between ground level and locations with steps (such as ships or trucks), the second layer and beyond can be used. Layers that allow for smooth entry and exit according to the aforementioned steps are used, enabling entry and exit between ground level and locations with steps.

[0132] [Table 24]

[0133] [Table 25]

[0134] [Table 26]

[0135] The AI-controlled four-wheeled vehicle parking shelf robot demonstrated that all of its storage container areas are easily accessible spaces, allowing users to set the retrieval position of stored items according to their preferences. Assuming the height / width and depth of the storage containers are 4.5m / 4.5cm and 4.5m, respectively, the ratio of easily accessible storage containers to floor area allows for the loading and unloading of two to four vehicles in a space equivalent to one level. The ground clearance of the first, second, and third layers is 0m, 4.5m, and 9m, respectively. Therefore, for loading and unloading between ground levels, only the first layer allows for loading and unloading without steps, while the second and third layers require design considerations for steps. On the other hand, for loading and unloading between ground level and locations with steps (such as ships or trucks), the second layer and beyond can be used. Layers that allow for smooth loading and unloading according to the aforementioned steps are used, enabling loading and unloading between ground level and locations with steps.

[0136] [Table 27]

[0137] [Table 28]

[0138] [Table 29]

[0139] The detection of disorganization results in the registration and history of specific (quantitative and qualitative) information, revealing whether the placement of stored items obstructs the reading of label readers. This reduces the risk of theft by ensuring that vehicles are stored in a concealed state so that their value cannot be visually recognized, and by automating the verification of their loading and unloading using personal authentication. The high burden of use can be reduced by simplifying registration / updates, inventory management, loading and unloading, and supporting daily maintenance tasks.

[0140] (Example 9; Plant cultivation shelf robot) Conventional plant cultivation shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is the inability to detect the disorganization of stored items, which stems from the lack of an evaluation system to detect plant growth in response to environmental factors (temperature, lighting, nutrients), and may stem from the lack of an evaluation system to find and implement cultivation methods that surpass natural cultivation. The second problem is the high burden on the system, one reason being the difficulty in maintaining a uniform environment within the shelf, where even adjusting local temperatures does not prevent environmental fluctuations within the shelf due to differences in height and left-right positioning, and another reason being the need for manual labor for plant replacement and shipping. There is no system to detect indicators of plant growth (shape, color, or arrangement) and determine the shipping time accordingly. The third problem is that artificial intelligence is not being used to solve the above problems for all shelves. In addition to the above, shelves that can store items of various sizes according to their size are not yet commonplace.

[0141] The plant cultivation shelf robot according to an embodiment of the present invention comprises: the basic shelf structure; the storage item label structure; the user identification and height control of the storage items; the transport of the storage items or storage containers; the forward / backward movement of the storage items or storage containers; the adjustment of the liquid volume in the storage items or storage containers; the setting at one location on the shelf for the storage items or storage containers to be applied to all the storage items or storage containers on the shelf; the travel distance and travel time to the storage items or storage containers; the rotation stop of the storage items or storage containers not due to gravity; the horizontal rotation of the storage items or storage containers; and soil cultivation containers on pallets suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels. The system comprises a container or hydroponic growing container, an outer case, a water / fertilizer addition port, and LED lighting equipment. The means include identifying the user (cultivator) using a characterization algorithm, identifying the stored items (plants) using a stored item characterization algorithm, transporting the stored items by a transport vehicle using the aforementioned driving algorithm, loading and unloading by the user using the aforementioned height control algorithm, adding liquid fertilizer using the aforementioned addition algorithm, adjusting the amount of liquid fertilizer using the liquid volume adjustment algorithm, horizontal rotation using the aforementioned horizontal rotation algorithm for 360-degree viewing, homogenizing the environment between storage containers within the shelves using the aforementioned environment homogenization algorithm, shortening the transport distance by arranging the shelves, optimizing cultivation beyond natural cultivation using the aforementioned position information analysis algorithm, detecting dynamic objects using the aforementioned position information analysis algorithm, and detecting disorganization using the aforementioned position information analysis algorithm. The aforementioned soil cultivation containers or hydroponic cultivation containers may be equipped with a device for attaching and detaching them to other storage containers.

[0142] The plant cultivation shelf robot ensures that all of its storage container areas are easily accessible, allowing users to set the retrieval position of stored items according to their preferences. Assuming that each storage container has a width / length and depth of 40cm / 40cm, the total easily accessible storage area per floor area allows for the storage of 2 to 5 containers in the space of one flat plant cultivation shelf. The minimum ground clearance for the first, second, third, and fourth layers is 0m, 0.4m, and 0.8m, respectively, and the shelf diameter usable by adults ranges from 0.8m to 2.9m.

[0143] [Table 30]

[0144] [Table 31]

[0145] [Table 32]

[0146] The detection of disorganization and tidiness results in the registration and history of specific (quantitative and qualitative) information, allowing for the detection of factors influencing plant growth in response to environmental factors (temperature, lighting, nutrients), and potentially revealing cultivation methods that surpass natural farming. The high burden of use can be reduced through cultivation work, maintaining a uniform environment within the shelves, plant registration and updating, inventory management, and shipping. Furthermore, by attaching labels to the pathways to the plant factory, the burden of transportation can be reduced by requiring only a single fork insertion operation through the collaborative work of the shelves and transport vehicles for harvesting. This enables the realization of a plant factory that covers all processes mentioned above: sowing, germination, greening, seedling selection, seedling cultivation, seedling transplanting, harvesting, and shipping.

[0147] (Example 10; Laboratory animal rearing shelf robot) Conventional laboratory animal housing shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that it is not possible to detect the disorganization of stored items, which makes it difficult for users to record chronological symptom observations and difficult for researchers to record the behavior of nocturnal animals, which they rarely have the opportunity to observe. For example, in the case of recording symptom observations after drug administration, the complexity of conducting symptom observations in parallel for each animal from the time of administration to the time of symptom observation tends to result in the administration order being arbitrarily decided by the user on a group basis (control group → low-dose group → medium-dose group → high-dose group). However, the administration order for comparison between administration groups in the study plan, which takes into account pharmacokinetics and physiological diurnal variation for evaluating the effect on animals, should be on an animal basis (control group 1st animal → low-dose group 1st animal → medium-dose group 1st animal → high-dose group 1st animal → control group 2nd animal). The inability to adopt the above administration order stems from the fact that observing symptoms chronologically becomes a confusing task. Analyzing the general condition of each animal over time is important for clarifying the pharmacokinetics after drug administration. For example, investigating the relationships between multiple types of general conditions is important for clarifying the mechanism of action, but it is difficult to clarify this precisely. The second challenge is the high burden, which is as follows: The first high burden is changing cage arrangements, supplying water and feed, changing bedding, and weighing animals as an indicator of health status. All of these are labor-intensive tasks performed by humans, and there is no automation to reduce this labor. The second high burden is maintaining a uniform environment (temperature, humidity). This stems from the conventional fixed cage arrangement, and the impact of the environment (lighting, temperature, humidity) due to lighting and the arrangement of the breeding room on animals is known, but the labor-intensive task of changing cage arrangements is not performed frequently. The third high burden is that compliance with GLP, which uses paper documents, is sometimes unavoidable, and this is a cumbersome task. The third challenge is that artificial intelligence is not being used to solve the above challenges for all shelves. In addition to the above, shelves that can accommodate items of various sizes according to their dimensions are not yet commonplace.

[0148] The experimental animal rearing shelf robot according to an embodiment of the present invention comprises: the basic shelf structure; the storage item label structure; the user identification and height control of the storage items; the transport of the storage items or storage containers; the forward / backward movement of the storage items or storage containers; the weight measurement of the storage items or storage containers; the storage items or storage containers being reflected in all the storage items or storage containers on the shelf by setting at one location on the shelf; the distance and time of travel to the storage items or storage containers; the animal housing space and feed baskets in a cage suspended in the storage space from the suspension points of the rotating shelf located at the front and rear wheels; the feed supply port for supplying feed at the top of the rotating shelf enabling automated feed supply; the water supply port for supplying water; and attached storage items (feces and urine receiving trays for two feces and urine trays). The system is equipped with a transport pallet for transporting plates, waste plates, and labels (barcodes or QR codes®) to be affixed to the transport pallet. The means include identifying the user (person in charge) using the characterization algorithm, identifying the stored items (animals) using the stored item characterization algorithm, transporting the attached stored items by a transport vehicle using the driving algorithm, measuring the weight using the weight measurement algorithm, shortening the travel distance by arranging the shelves, loading and unloading the stored items by the user using the height control algorithm, adding feed using the additive algorithm, homogenizing the environment between storage containers within the shelves using the environment homogenization algorithm, shortening the transport distance by arranging the shelves, observing the stored items using the position information analysis algorithm, detecting dynamic objects using the position information analysis algorithm, and detecting disorganization using the position information analysis algorithm.

[0149] The laboratory animal rearing shelf robot has all its storage container areas designed for easy retrieval, allowing users to set the retrieval position of stored items according to their preference. Assuming that storage is done in a single layer without dividers, the total easily accessible storage area per floor area is approximately 36 cm in width, height, and depth, respectively. The ratio of easily accessible storage containers to floor area is such that two to four containers can be stored in the space of one flat area. The minimum ground clearance for the first, second, and third layers of the AI-controlled laboratory animal rearing shelf is 0 m, 36 cm, and 72 cm, respectively, and the diameter of the shelf usable by adults ranges from 1.64 m to 3.3 m. In this shelf, each rat cage is easily accessible.

[0150] [Table 33]

[0151] [Table 34]

[0152] [Table 35]

[0153] The detection of disorganization involves the registration and history of specific (quantitative and qualitative) information, while the high burden is reduced by minimizing the impact on animals due to environmental factors (lighting, temperature, humidity) caused by changes in cage arrangement due to rotation, maintaining a uniform environment within the shelves, registering and updating individual animals and managing inventory, performing daily animal care tasks (cage arrangement changes, supplying water and feed, changing bedding), detecting health status during periods when workers cannot observe (from lights off to lights on) or over time (observing general condition through medication, observing mating, and measuring weight as an indicator of health), recording the behavior of nocturnal animals that researchers rarely have the opportunity to observe, evaluating reproductive capacity by confirming mating behavior rather than just confirming sperm in the female vagina or dropping a vaginal plug, setting user-friendly locations, and eliminating paper documents, thereby reducing the burden of GLP compliance, transportation, and animal observation including mating confirmation.

[0154] (Example 11; Livestock rearing shelf robot) Conventional livestock shelving systems have three problems in addition to the lack of height control to manage the height of stored items. The first problem is the inability to detect the disorganization of stored items, which makes it difficult to balance growth management in livestock raising, which involves observing the condition of the animals, with lineage management in breeding. This makes it difficult to simultaneously advance two evaluation systems: raising healthy livestock until shipment, and raising them while considering genetic quality control in genetic breeding. Furthermore, harmful animals that affect livestock may be detected, and it may be necessary to eliminate these harmful animals. The second problem is the high burden of use. One aspect of this high burden is that cage arrangement changes, water and feed supply, bedding changes, and weight measurements as indicators of health status are required, all of which are labor-intensive tasks that may not be automated to reduce labor. In particular, while the impact of fixed cage arrangements on animals due to environmental factors (lighting, temperature, humidity) caused by lighting and the arrangement of the rearing room is known, the labor-intensive task of changing cage arrangements is not performed. Maintaining a uniform environment (temperature, humidity) is not easy due to the lack of an automated evaluation system to suppress fluctuations within the shelves. The third challenge is that artificial intelligence is not being used to solve the aforementioned problems for all shelves. In addition to the above, shelves that can accommodate items of various sizes according to their size are not yet commonplace.

[0155] The livestock rearing shelf robot according to an embodiment of the present invention comprises: the basic shelf structure; the storage item label structure; the user identification and height control of the storage items; the transport of the storage items or storage containers; the forward / backward movement of the storage items or storage containers; the weight measurement of the storage items or storage containers; the storage items or storage containers being reflected in all the storage items or storage containers on the shelf by setting at one location on the shelf; the distance and time of movement to the storage items or storage containers; the animal housing space and feed baskets in a cage suspended in the storage space from the suspension points of the rotating shelf located at the front and rear wheels; the feed supply port for supplying feed at the top of the rotating shelf to enable automated feed supply; the water supply port for supplying water; and attached storage items (two manure trays for receiving manure trays). The system is equipped with a transport pallet for transporting manure trays, a label (barcode or QR code®) to be affixed to the transport pallet, and the means include identifying the user (person in charge) using the characterization algorithm, identifying the stored items (animals) using the stored item characterization algorithm, transporting the attached stored items by a transport vehicle using the driving algorithm, measuring the weight using the weight measurement algorithm, shortening the travel distance by arranging the shelves, loading and unloading the stored items by the user using the height control algorithm, adding feed using the additive algorithm, homogenizing the environment between storage containers within the shelves using the environment homogenization algorithm, shortening the transport distance by arranging the shelves, observing the stored items using the position information analysis algorithm, detecting dynamic objects using the position information analysis algorithm, and detecting disorganization using the position information analysis algorithm.

[0156] Assuming that the livestock rearing robot is stored in a single-tiered storage container without partitions, and assuming the height / width and depth of the storage container are 2.5m / 2.5m and 2.5m respectively, it was shown that only the first tier allows for easy entry and exit from the ground level, and the total easily accessible storage area allows for the accommodation of two animals in the space of one animal in a ground-level rearing facility.

[0157] [Table 36]

[0158] The detection of disorganization involves the recognition and matching of stored items, resulting in the registration and history of specific (quantitative and qualitative) information. Furthermore, harmful animals that affect livestock can be detected, and the general condition of animals after lights out, which is rarely observed by the caretaker, can also be recorded. The high burden on users can be reduced by maintaining a uniform environment within the shelves to balance growth in livestock and lineage management in breeding, as well as by managing registration, updates, and inventory, performing daily livestock tasks (cage arrangement changes, water and feed supply, bedding changes), detecting health conditions (general condition observation and weight measurement), setting user-friendly locations, and automating and transporting manure trays.

[0159] (Example 12; High-oxygen, high-pressure environment sleep capsule bed shelf robot) High-oxygen, high-pressure environments are being used as treatments for illnesses. The deterioration of the global environment today has the potential to affect human health, and facilities that routinely provide an environment suitable not only for sick people but also for healthy individuals aiming for longevity during rest and sleep may be necessary in the future. Conventional high-oxygen, high-pressure environment facilities have three problems in addition to the lack of height control to control the height of stored items. The first problem is that they cannot detect the disorganization of stored items, making it impossible to take countermeasures through observation of the general condition of the user in the bed. There is no evaluation system that links the atmospheric environment to longevity. The second problem is the high burden of use. Since it is not a medical procedure aimed at achieving results in conventional hospitals, and is intended for individuals to use at home for sleep without the involvement of medical professionals, it has not become common to use it in a way that is optimal for each individual's health condition. Furthermore, in order to detect the effects in a medical institution, it is necessary to have medical professionals on staff at all times, but on the other hand, when aiming for longevity, it is necessary to monitor important physiological parameters for health during the long hours of individual sleep, and if medical professionals are involved in the monitoring, the personnel costs become a burden. The third challenge is that artificial intelligence is not being used to solve the aforementioned problems for all shelves. In addition to the above, shelves that can accommodate items of various sizes according to their size are not yet commonplace.

[0160] The high-oxygen, high-pressure environment sleep capsule bed shelf robot according to an embodiment of the present invention is designed to accommodate a user (human) and includes the basic structure, the storage item label structure, the user identification and height control of the storage item, the transport of the storage item or storage container, the forward / backward movement of the storage item or storage container, the gravity-independent rotation stop of the storage item or storage container, a capsule for housing a person inside a suspended container suspended within the storage space from suspension points of a rotating shelf located at the front and rear wheels, and a detachable seat consisting of a rotating plate and a plate for moving the rotating plate to facilitate entry and exit of the capsule for a wheelchair user, and an oxygen supply port. The system includes an oxygen sensor and, as an accessory to the shelf, an oxygen supply device including an oxygen cylinder that enables oxygen supply to each capsule outside the shelf. The means include identifying the user (capsule operator or sleeper) using a characterization algorithm, identifying the stored items (sleepers inside the capsule) using a stored item characterization algorithm, transporting the stored items by a transport vehicle using a driving algorithm, allowing the user to enter and exit the stored items using a height control algorithm, homogenizing the environment between storage containers inside the shelf using an environment homogenization algorithm, shortening the transport distance by arranging the shelf, observing the stored items, detecting dynamic objects using a position information analysis algorithm, and detecting disorganization using a position information analysis algorithm.

[0161] Assuming that the high-oxygen, high-pressure environment capsule bed shelf robot is stored in a storage container in a single layer without partitions, and assuming the height / width and depth of the storage container are 0.7m / 0.7m and 2.2m respectively, only the first layer is easily accessible from the ground level. The total area of ​​easily accessible storage containers per floor area is such that two capsule sleeping bed shelves can be stored in the space of one on flat ground.

[0162] [Table 37]

[0163] The detection of disorganization will result in the registration and history of specific (quantitative and qualitative) information, allowing for the monitoring of health-critical physiological parameters during individual long sleep periods, potentially maintaining an environment conducive to health and longevity. Furthermore, the user's general state after lights out may also be recorded. The high burden on users may be reduced through the use of artificial intelligence, which can maintain a uniform environment within the shelves, register and update stored items and manage inventory, detect health status (general state observation and oxygen concentration measurement), and set user-friendly locations and transportation.

[0164] (Example 13; Bathing and resting capsule bed shelf robot) Conventional bathing facilities for the general public, including the elderly, have three main challenges in addition to the lack of height control to manage the height of stored items. The first challenge is the inability to detect the disorganization of stored items, making it impossible to take countermeasures through general observation of the user's condition while they are bathing in bed. The second challenge is the high burden on the elderly. As the aging population increases, bathing for the elderly carries a higher risk of accidents, and using existing bathing facilities requires a significant amount of manpower. It may be difficult for the elderly or wheelchair users to use these facilities safely on their own without assistance. If the goal is for wheelchair users to use these facilities for bathing at home without the involvement of a nurse, it will be burdensome for them to bathe independently or with family assistance in a way that is optimal for their individual health condition. One primary purpose of bathing is to wash the body to remove dirt, but there is also a secondary purpose of recovering from physical fatigue. Providing an opportunity to rest in addition to this purpose is also useful. Facilities that enable bathing that provides the three benefits mentioned above, which cannot be obtained with conventional bathing facilities, are not yet widespread. The third challenge is that artificial intelligence is not being used to solve the aforementioned problems for all shelves. In addition to the above, shelves that can accommodate people of various sizes according to their physical size are not yet commonplace.

[0165] The bathing and resting capsule bed shelf robot according to an embodiment of the present invention is designed to allow a user (human) to enter, and includes the basic structure, the storage item label structure, the user identification and height control of the storage items, the transport of the storage items or storage container, the forward / backward movement of the storage items or storage container, the gravity-independent rotation stop of the storage items or storage container, the storage container (capsule bed) located inside the storage space from the suspension points of the rotating shelf located at the front and rear wheels, and a detachable seat consisting of a rotating plate and a plate for moving the rotating plate to facilitate entry and exit of the capsule bed for a wheelchair user, and the shelf accessories include an image capture device (camera) for taking pictures of any image other than the shelf, and each storage The system is equipped with facilities that enable the supply of hot water and hot air to the containers, and the means include identifying the user (the bather who will operate the capsule bed, a nurse, or someone related to the bather) using a characterization algorithm, identifying the stored items (the bather) using a stored item characterization algorithm, transporting the stored items by a transport vehicle using the aforementioned driving algorithm, entering and exiting the capsule for the bather using the aforementioned height control algorithm when there is no caregiver, entering and exiting the capsule for the bather using the aforementioned height control algorithm when there is a caregiver, homogenizing the environment between the stored containers on the shelves using the aforementioned environment homogenization algorithm, shortening the transport distance by the aforementioned shelf arrangement, detecting dynamic objects using the aforementioned position information analysis algorithm, observing the stored items, and detecting disorganization using the aforementioned position information analysis algorithm.

[0166] The bathing and resting capsule bed shelf robot is designed to be stored in a storage container in a single layer without partitions. Assuming the height / width and depth of the storage container are 0.7m / 0.7m and 2.2m, respectively, it was shown that only the first layer is easily accessible from the ground level, and that the total area of ​​easily accessible storage containers per floor area allows for the storage of two units in the space of one flat area.

[0167] [Table 38]

[0168] Detecting disorganization will result in the registration and history of specific (quantitative and qualitative) information, and image analysis (location information) may facilitate the management of the health status of stored items. The high burden of use can be reduced by utilizing artificial intelligence to maintain a uniform environment within the shelves, register and update stored items and manage inventory, detect health status (general condition observation), and set user-friendly locations for access and transportation. This shelf may have lower maintenance costs compared to the cost incurred by one person, as it can be maintained by four or more people maintaining the same environment.

[0169] (Example 14; Dishware and kitchen utensil shelf robot) Conventional dish and kitchen utensil shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that they cannot detect the disorganization of stored items, making it impossible for kitchen staff to grasp changes in the types, number, and easily accessible arrangement of dishes, which they rarely have the opportunity to observe. The second problem is that they are burdensome, and a large portion of the storage space may not always be in the place where items are needed, resulting in a lot of inconvenient space. The third problem is that artificial intelligence has not been used to solve the above problems for all shelves. In addition to the above, shelves that can store items of various sizes according to their size are not yet commonplace.

[0170] A dish and kitchenware shelf robot according to an embodiment of the present invention comprises a basic shelf structure, a storage item label structure, a structure for identifying the user and controlling the height of the stored items, and storage containers (dishes and kitchenware) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels. The means include identifying the user (the person loading and unloading dishes and pots) using a characterization algorithm, identifying the stored items using a storage item characterization algorithm, loading and unloading by the user using a height control algorithm, detecting dynamic objects using a position information analysis algorithm, and detecting disorganization using a position information analysis algorithm.

[0171] The dish and kitchen utensil shelving robot was designed to store items in storage containers on a single shelf without dividers. Assuming the height / width and depth of the storage containers are 36cm / 36cm and 36cm, respectively, it was shown that the total area of ​​easily accessible storage containers per floor area can accommodate two to five containers in the space of one of the aforementioned dish and kitchen utensil shelving units on a flat surface.

[0172] [Table 39]

[0173] [Table 40]

[0174] [Table 41]

[0175] Detecting disorganization and tidiness involves registering and recording specific (quantitative and qualitative) information about tableware and kitchen utensils, making it possible to reveal this information. The high burden of use can be reduced through registration, updating, inventory management, and user-centric receiving.

[0176] (Example 15; Serving shelf robot) Conventional serving shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that they cannot detect the disorganization of stored items, making it impossible for cooks to grasp the types, number, and changes in the arrangement of dishes after plating, which they rarely have the opportunity to observe. Cooks may not be able to grasp the changes in the arrangement of dishes on the trays. The second problem is that they are burdensome, and cooks and servers may not have the serving shelves in a location that is easy to move in and out of. Serving consists of the work of placing food on trays and the work of transporting them. The work of accurately placing bowls and plates of cooked food onto the appropriate trays requires more space simultaneously as the number of dishes increases, the distance that cooks have to move increases, and the work is not easy to perform in a confined space. The work of accurately transporting multiple trays to the appropriate positions on the dining tables requires many people. The third challenge is that artificial intelligence is not being used to solve the aforementioned transportation challenges for all shelves, such as ensuring that the number of dishes, the numerical arrangement of the presentation, and the qualitative arrangement of the menu are carried out as planned by the chef in each meal, and ensuring that the food is delivered to the customer.

[0177] A serving shelf robot according to an embodiment of the present invention comprises a basic shelf structure, a component for the storage item label, a component for identifying the user and controlling the height of the storage item, a component for transporting the storage item or storage container, and a storage container (meal tray) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels. The means include identifying the user (the person who places food on the meal tray or dishes) using a characterization algorithm, identifying the storage item using a storage item characterization algorithm, transporting the storage item by a transport vehicle using a driving algorithm, loading and unloading by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewpoint, detection of dynamic objects using a position information analysis algorithm, and detection of disorganization using a position information analysis algorithm.

[0178] The serving shelf robot is designed to store items in storage containers on a single shelf without dividers. Assuming the height / width and depth of the storage containers are 45cm / 45cm and 45cm respectively, it was shown that the total area of ​​easily accessible storage containers per floor area can accommodate two to five containers in the space of one serving shelf on a flat surface.

[0179] [Table 42]

[0180] [Table 43]

[0181] [Table 44]

[0182] The detection of disorganization involves the registration and history of specific (quantitative and qualitative) information. If the arrangement of dishes on a tray does not match, image analysis (location information) can reveal information about the placement, number, and type of items in the food arrangement on each bowl and plate. The high burden on users can be reduced through registration, updating, inventory management, and user-centric receiving and transportation.

[0183] (Example 16; Manufacturing and laboratory equipment shelf robot) Conventional manufacturing and laboratory equipment shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that they cannot detect the disorganization of stored items, and researchers cannot keep track of changes in the type, number, and arrangement of manufacturing and laboratory equipment within the shelves. The second problem is that they are burdensome. Manufacturers or researchers cannot keep track of changes in the arrangement of laboratory equipment within the equipment storage containers. While the number and arrangement of laboratory equipment required for a single manufacturing or experiment should be maintained while multiple manufacturers or researchers are using the equipment, allocating time for this is a cumbersome task. The third problem is that artificial intelligence is not being used to solve the above problems for all shelves.

[0184] The manufacturing and laboratory equipment shelf robot according to an embodiment of the present invention comprises the shelf basic structure, the storage item label structure, the user identification and height control of the storage items, the transport of the storage items or storage containers, the forward / backward movement of the storage items or storage containers, the rotation stop of the storage items or storage containers without gravity, the identification of the worker in the storage items or storage containers without paper media, and the suspension points of the rotating shelf located at the front and rear wheels within the storage space. A lowerable storage container (manufacturing / experimental equipment box) is provided, and the means include identifying the user (manufacturer / experimenter) using a characterization algorithm, identifying the stored items using a stored item characterization algorithm, transporting the stored items by a transport vehicle using a driving algorithm, loading and unloading by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewpoint, detection of dynamic objects using a position information analysis algorithm, and detection of disorganization using a position information analysis algorithm.

[0185] The manufacturing and laboratory equipment shelving robot was designed to store equipment in storage containers on a single shelf without dividers. Assuming the height / width and depth of the storage containers (laboratory equipment) are 40cm / 40cm and 40cm respectively, it was shown that the total area of ​​easily accessible storage containers per floor area allows for the storage of two to five containers in a space equivalent to one level of flat ground.

[0186] [Table 45]

[0187] [Table 46]

[0188] [Table 47]

[0189] Detecting disorganization results in the registration and history of specific (quantitative and qualitative) information, revealing how stored items are placed. The high burden on users can be reduced by utilizing artificial intelligence for registration, updating, inventory management, and user-centric receiving.

[0190] (Example 17; Manufacturing / Laboratory Equipment Shelf Robot) Conventional manufacturing and experimental equipment stands (equipment stands) have three problems in addition to the lack of height control to control the height of stored items. The first problem is that they cannot detect the disorganization of stored items, and experimenters cannot grasp changes in the type, number, and arrangement of the equipment on the shelves. In other words, the equipment stand is not being used effectively as space. The second problem is the high burden of use. Recording who used which equipment and when under GXP regulations is a cumbersome task. In relation to the number of users and the number of equipment, two cases can be assumed: number of users > number of equipment used, and number of users < number of equipment used. In the former case, multiple users will use one piece of equipment in turn, and the number of equipment used in proportion to the number of users may not be used effectively. In the latter case, one user can use multiple pieces of equipment simultaneously, but a large area will be occupied by multiple pieces of equipment. The third problem is that artificial intelligence is not being used to solve the above problems for all shelves.

[0191] The manufacturing and experimental equipment shelf robot according to an embodiment of the present invention comprises the basic structure, the storage item label structure, the user identification and height control of the storage items, the transport of the storage items or storage containers, the forward / backward movement of the storage items or storage containers, the gravity-independent rotation stop of the storage items or storage containers, the identification of workers in the storage items or storage containers without paper media, and the storage space from the suspension points of the rotating shelf located at the front and rear wheels. A suspended storage container (experimental equipment box) is provided, and the means include identifying the user (manufacturer / experimenter) using a characterization algorithm, identifying the stored items using a stored item characterization algorithm, transporting the stored items by a transport vehicle using a driving algorithm, loading and unloading by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewpoint, detection of dynamic objects using a position information analysis algorithm, and detection of disorganization using a position information analysis algorithm.

[0192] The manufacturing and experimental equipment shelving robot was designed to store equipment in storage containers on a single shelf without dividers. Assuming the height / width and depth of the storage containers (experimental equipment) are 70cm / 70cm and 70cm respectively, it was shown that the total area of ​​easily accessible storage containers per floor area allows for the storage of two units in the space of one flat area.

[0193] [Table 48]

[0194] [Table 49]

[0195] Detecting disorganization and tidiness may lead to the registration and history of specific (quantitative and qualitative) information, potentially revealing how stored items are placed. The high burden of use may be reduced by streamlining registration, updating, and inventory management, implementing user-centric receiving, complying with GXP regulations without paper documents, and effectively utilizing multiple laboratory benches for multiple experimental operations, as well as the number of experimenters and experimental equipment.

[0196] (Example 18; Manufacturing table or laboratory table (implementation table) shelf robot) Conventional manufacturing or experimental benches (workstations) have three problems in addition to lacking height control to manage the height of stored items. The effective workstation area for the operator is the space within the operator's line of sight and range of motion; the space outside this range is unusable space. As a result, even if the area of ​​currently used workstations is set large, the proportion of unusable space will only increase. Furthermore, current workstations do not allow a single operator to perform many manufacturing or experiments simultaneously in the effective space. For example, it is not easy for multiple operators to work in a relay format or simultaneously. Ideally, manufacturing or experimental equipment (workstation equipment) should be placed near the workstation, but if all workstation equipment is placed next to the workstation, a workstation is needed for each piece of equipment that is not being used, resulting in an increase in unused workstations. This is because the aforementioned workstation houses a single workstation but is not a workstation shelf that houses multiple workstations. The first problem is the inability to detect the disorganization of stored items, and the fact that the number and arrangement of equipment required for a single manufacturing or experiment are not recorded, and that the individual equipment and the person performing the experiment are not identified, as well as the purpose of the experiment performed on the bench. The second problem is the high burden. Under GXP regulations, recording who performed which manufacturing or experiment and when (identifying individual practitioners) is a cumbersome task using paper. In terms of the relationship between the number of practitioners and the number of machines, two cases are conceivable: number of practitioners > number of machines, and number of practitioners < number of machines. In the former case, multiple practitioners will use one machine in turn, and the number of machines may not be used effectively in proportion to the number of practitioners. In the latter case, one practitioner can use multiple machines simultaneously, but a large area will be occupied by multiple pieces of equipment. One practitioner cannot simultaneously use two machines while seated. The third problem is that artificial intelligence is not utilized in all shelves to solve the above problems.

[0197] The manufacturing / laboratory bench shelf robot according to an embodiment of the present invention comprises the basic shelf structure, the storage item label structure, the user identification and height control of the storage items, the forward / backward movement of the storage items or storage containers, the gravity-independent rotation stop of the storage items or storage containers, the identification of the worker in the storage items or storage containers without the use of paper media, storage containers (manufacturing / laboratory benches) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels, a sign indicating the person in charge, and a rotating shelf that stops rotation at regular intervals. The system includes a pallet for transporting equipment that is stable and independent of gravity, and a fume hood for discharging air from the laboratory bench. The means for this include identifying the user (manufacturer / experimenter) using a characterization algorithm, identifying the stored items using a stored item characterization algorithm, transporting the stored items by a transport vehicle using a driving algorithm, loading and unloading by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewpoint, detection of dynamic objects using a position information analysis algorithm, and detection of disorganization using a position information analysis algorithm.

[0198] The manufacturing / laboratory bench shelf robot was designed to store items in storage containers on a single tier without dividers. Assuming the height / width and depth of the storage containers (laboratory equipment) are 80cm / 80cm and 80cm respectively, it was shown that the total area of ​​easily accessible storage containers per floor area allows for the storage of two units in the space of one flat area.

[0199] [Table 50]

[0200] The detection of disorganization involves the registration and history of specific (quantitative and qualitative) information, revealing how stored items are placed. The high burden of use can be reduced by streamlining registration, updating, and inventory management, implementing user-centric receiving, complying with GXP regulations without paper documents, and effectively utilizing multiple laboratory benches for multiple experimental operations, as well as the number of experimenters and experimental equipment.

[0201] (Example 19; Cell culture tank shelf robot) Conventional cell culture tank shelves (culture stands) used during the manufacturing stage have three problems in addition to the lack of height control to manage the height of stored items. This stems from the fact that cell culture stands store a single cell culture tank, not multiple cell culture tanks. The first problem is the inability to detect the disorganization of stored items, and even if there is an evaluation system for each culture tank, there is no system to manage the culture status of all culture tanks. The second problem is the high burden of use, as manual labor is required for changing and shipping heavy culture tanks. Furthermore, maintaining a uniform environment within the shelf is difficult, as even if the temperature is adjusted, it is impossible to prevent environmental fluctuations within the shelf due to differences in height and left / right position. The third problem is that artificial intelligence is not being used to solve the above problems for all shelves. In addition to the above, shelves that can store items of various sizes according to their size are not yet commonplace.

[0202] The cell culture tank shelf robot according to an embodiment of the present invention includes the shelf basic structure, the components of the storage item label, the components for identifying the user and controlling the height of the storage item, the components for transporting the storage item or the storage container, the components for moving the storage item or the storage container forward / backward, the components for identifying the operator for the storage item or the storage container without using a paper medium, the components for horizontally rotating the storage item or the storage container, and a storage container (culture tank) suspended in the storage space from the suspension points of the rotating shelves located at the front wheels and the rear wheels. The means include identification of the user (culture person in charge) by a feature extraction algorithm, identification of the storage item (plant) by a storage item characterization algorithm, transportation of the storage item by a transport vehicle according to the travel algorithm, loading and unloading by the user according to the height control algorithm, horizontal rotation by the horizontal rotation algorithm for 360-degree visualization, equalization of the environment between the storage containers in the shelf by the environment equalization algorithm, shortening of the transport distance by the arrangement of the shelf, optimization of the culture by the position information analysis algorithm, detection of moving objects by the position information analysis algorithm, and detection of non-organization by the position information analysis algorithm.

[0203] Assuming that the cell culture tank shelf robot can accommodate 4 culture tanks in a single tier without partition plates, and assuming that the height / width and depth of the storage container (experimental instrument) are 1.6 m / 1.6 m and 1.6 m respectively, it has been shown that the total area of the storage containers that can be easily taken out per unit floor area can accommodate eight times the storage space of a single flat area.

[0204]

Table 51

[0205] The detection of non-organization becomes a registration / history of specific information (quantitative information, qualitative information) and can clarify the information on how the storage items are placed. The high burden of use can be reduced by maintaining a uniform environment in the shelf, registration / updating and inventory management, user-oriented receipt, reading of the culture status, identification of the individual manufacturer, compliance with GXP regulations without using a paper medium, and transportation.

[0206] (Example 20; Chicken chick rearing shed robot) Conventional chicken chick rearing sheds have three problems in addition to the lack of height control for controlling the height of stored items. The first problem is the inability to detect the disorganization of stored items, and chickens at 7 days after hatching and 15 - 28 days after hatching cannot be set with the indoor environmental variations according to the behavior of chickens, which cannot necessarily be obtained by a thermometer. The second problem is the high burden. For 14 days after hatching, compared with the rearing of chickens 30 days after hatching, in the strict rearing environment (temperature), feeding and watering, sex discrimination by the method of feather discrimination in newly hatched chicks, and observation of pecking habits in newly hatched chicks, careful 24 - hour observation is important. However, it is limited for breeders to observe for 24 hours, and there may be no system to replace the monitoring. Furthermore, even if the temperature of the entire rearing room is adjusted, it may not be possible to prevent environmental variations in the rearing room inside the shed due to differences in height and left - right positions. The third problem is that artificial intelligence is not utilized to solve all the above problems for all the sheds.

[0207] The chicken chick rearing shelf robot according to an embodiment of the present invention comprises: the basic shelf structure; the storage item label structure; the user identification and height control of the storage items; the transport of the storage items or storage containers; the storage items or storage containers being reflected in all the storage items or storage containers on the shelf by setting them at one location on the shelf; the storage items or storage containers being stopped from rotating independently of gravity; the identification of the worker in the storage items or storage containers without the use of paper media; animal housing containers suspended in the storage space from suspension points of the rotating shelf located at the front and rear wheels; environmental (temperature and humidity) detection sensors at the top of the cage; a light intake window; a feed supply port at the top of the rotating shelf enabling automated feed supply; a water supply port; and The lower part of the shelf is equipped with a manure tray for receiving manure and urine, and supports that hold the manure tray in place. The means include identifying the user (breeder) using a characterization algorithm, identifying the stored items (chickens) using a stored item characterization algorithm, transporting the stored items by a transport vehicle using a driving algorithm, loading and unloading by the user using a height control algorithm, adding feed using an additive algorithm, horizontal rotation using a horizontal rotation algorithm for a 360-degree view, homogenizing the environment between storage containers on the shelf using an environmental homogenization algorithm, shortening the transport distance by arranging the shelves, optimizing growth beyond natural growth using a positional information analysis algorithm, detecting dynamic objects using a positional information analysis algorithm, and detecting disorganization using a positional information analysis algorithm.

[0208] The robotic chicken chick rearing system is designed to store chicks in storage containers divided into two levels by a partition plate. Assuming the height / width and depth of the storage containers (rearing rooms) are 1m / 1m and 1m respectively, it was shown that the total area of ​​easily accessible storage containers per floor area allows for the storage of two to four containers in a space equivalent to one level of flat ground.

[0209] [Table 52]

[0210] The detection of disorganization results in the registration and history of specific (quantitative and qualitative) information, and the arrangement of stored items can be revealed through image analysis (location information). The general condition of animals during times when caretakers have little opportunity to observe them is recorded, and it is also possible to detect the behavior of chicken chicks that cannot necessarily be obtained with thermometers. The high burden on users can be reduced by registering and updating individual animals and inventory management, setting user-friendly locations, setting environments according to animal behavior, maintaining a uniform environment within shelves, daily care tasks (cage arrangement changes, water and feed supply, bedding changes), detecting health status during times when workers cannot observe (from lights off to lights on) or over time (general condition observation and weight measurement as an indicator of health), and detecting genetic and breeding traits (sex discrimination by feathers, pecking habits).

[0211] (Example 21; Chicken egg-laying shelf robot) Conventional chicken laying shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that they cannot detect the disorganization of stored items, and may not be able to adjust the environment to respond to changes in the indoor environment in response to chicken behavior, which cannot always be obtained with thermometers. The second problem is the high burden of use. Careful 24-hour observation is important for observing pecking habits, egg-laying habits after maturity (egg-laying habits outside the nest), calculating the egg-laying rate for each individual, identifying the date and time of egg-laying, and obtaining tracking information with the parent hen of the egg. However, there are limits to what a farmer can observe 24 hours a day, and a system to replace monitoring is needed. The third problem is that artificial intelligence has not been used to solve the above problems for all shelves.

[0212] The chicken egg-laying box shelf robot according to an embodiment of the present invention comprises: the basic shelf structure; the storage item label structure; the user identification and height control of the storage items; the transport of the storage items or storage containers; the gravity-independent rotation stop of the storage items or storage containers; the identification of the worker in the storage items or storage containers without the use of paper media; egg-laying box containers (egg-laying space, egg storage space, and egg-laying date and tracking information label attachment space) suspended in the storage space from suspension points of the rotating shelf located at the front and rear wheels; a sign indicating the person in charge; an environmental (temperature and humidity) detection sensor at the top of the cage; and a light-in window. The system is equipped with the following means: identification of the user (breeder) by a characterization algorithm; identification of stored items (chickens) by a stored item characterization algorithm; transport of the stored items by a transport vehicle using the driving algorithm; loading and unloading by the user using the height control algorithm; horizontal rotation using the horizontal rotation algorithm for 360-degree viewpoint; uniformization of the environment between storage containers on the shelves using the environment uniformization algorithm; shortening of transport distance by the arrangement of the shelves; optimization of breeding using the position information analysis algorithm; detection of dynamic objects using the position information analysis algorithm; and detection of disorganization using the position information analysis algorithm.

[0213] The chicken egg-laying box shelf robot ensures that all of its storage container area is easily accessible. Assuming that the storage containers are divided into two levels by a partition plate, and assuming the width / length and depth of the containers are 72cm / 72cm and 36cm respectively, the ratio of easily accessible storage containers to floor area shows that it is possible to store two to ten containers on one level of flat floor space. The minimum ground clearances for the first, second, and third levels of the artificial intelligence-controlled experimental animal rearing shelf are 0m, 72cm, and 144cm, respectively, and the shelf diameter usable by adults ranges from 1.44m to 6.5m.

[0214] [Table 53]

[0215] [Table 54]

[0216] [Table 55]

[0217] The detection of disorganization results in the registration and history of specific (quantitative and qualitative) information, and the location information of stored items can be revealed through image analysis (location information). Animal behavior is recorded during times when caretakers have little opportunity to observe, and it is also possible to detect chickens that lay eggs outside the nest without using nesting boxes in free-range farming. The high burden on users can be reduced by registering and updating individual animals and inventory management, setting user-friendly locations, setting environments according to animal behavior, maintaining a uniform environment within shelves, detecting health status during times when workers cannot observe (from lights off to lights on) (general condition observation and weight measurement as an indicator of health), and detecting genetic breeding traits (pecking habits).

[0218] (Example 22; Mixture preparation shelf robot) Conventional mixture preparation shelves have three problems in addition to the lack of height control to control the height of stored items. The first problem is that it is not possible to detect the disorder (mixing state) of stored items, and it is not easy for manufacturers to record time-series monitoring, nor is there a system for users to record over long periods of time. The second problem is the high burden, which is as follows: The first high burden is that even if weighing and transporting are easy on an experimental scale, the same process is required at the manufacturing stage, and for products with heavy mixture weights per batch, and for products that are not heavy but have a large volume, these are all tasks that require human labor, and it is difficult to reduce labor through automation. The second high burden is that it is difficult to maintain a uniform environment (temperature, humidity) between batches, and there is no algorithm to suppress fluctuations within the shelf. The third high burden is that if GXP compliance is necessary, the cumbersome work using paper as a medium becomes a burden. The third problem is that artificial intelligence is not used to solve the above problems for all shelves. In addition to the above, shelves that can accommodate items of various sizes according to their dimensions are not yet commonplace.

[0219] The mixture production shelf robot according to an embodiment of the present invention includes the shelf basic structure, the components of the storage item label, the components for identifying the user and controlling the height of the storage item, the components for transporting the storage item or the storage container, the components for moving the storage item or the storage container forward / backward, the components for measuring the weight of the storage item or the storage container, the components for reflecting the settings at one location in the shelf to all the storage items or the storage containers in the shelf, the components for non-gravity rotation stop of the storage item or the storage container, the components for identifying the operator of the storage item or the storage container without a paper medium, and a storage container (mixture box or mixer) suspended in the storage space from the suspension points of the rotating shelves located at the front wheels and the rear wheels. The means includes identification of the user (mixture operator) by a characterization algorithm, identification of the storage item (mixture) by a storage item characterization algorithm, transportation of the storage item by a transport vehicle according to the travel algorithm, loading and unloading by the user according to the height control algorithm, horizontal rotation by the horizontal rotation algorithm for 360-degree visualization, addition of substances by the addition algorithm, homogenization of the environment between the storage containers in the shelf by the environment homogenization algorithm, shortening of the transportation distance by the arrangement of the shelf, detection of moving objects by the position information analysis algorithm, and detection of non-organization by the position information analysis algorithm.

[0220] The mixture production shelf robot is assumed to store in a storage container in a single layer without a partition plate. Assuming the height / width and depth of the storage container are 1.1 m / 1.1 m and 1.1 m respectively, it is shown that the total area of the storage containers that can be easily taken out per floor area can store two to five times the amount in a single flat space. In this shelf, the ground heights of the first layer, the second layer, and the third layer are 0 m, 1.1 m, and 2.2 m respectively, and the lowest ground height of all the storage containers is easy for transportation.

[0221]

Table 56

[0222] [Table 57]

[0223] [Table 58]

[0224] Detecting disorganization results in the registration and history of specific (quantitative and qualitative) information, revealing how stored items are placed. The burden on users can be reduced by maintaining a uniform environment within the shelves, registering and updating stored items and managing inventory, setting user-friendly locations, GXP compatibility without paper documents, and transportation by carriers.

[0225] (Example 23; Mushroom cultivation shelf robot) Conventional multi-tiered mushroom cultivation shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is the inability to detect the disorganization of stored items, which may stem from the lack of a system to detect factors affecting mushroom growth. The second problem is the high burden on users. One reason for this is the difficulty in maintaining a uniform environment within the shelves; even if the temperature is adjusted, it is impossible to prevent environmental fluctuations within the shelves due to differences in height and left-right positioning. Another reason is that manual labor is required for changing and shipping the mushrooms. The third problem is that artificial intelligence has not been used to solve the above problems for all shelves. In addition to the above, shelves that can store items of various sizes according to their size are not yet commonplace.

[0226] The mushroom cultivation shelf robot according to an embodiment of the present invention comprises the shelf basic structure, the storage item label structure, the user identification and height control of the storage items, the transport of the storage items or storage containers, the forward / backward movement of the storage items or storage containers, the adjustment of the amount of liquid in the storage items or storage containers, the setting at one location on the shelf to reflect to all the storage items or storage containers on the shelf, the distance and time of travel to the storage items or storage containers, the rotation stop of the storage items or storage containers without gravity, the horizontal rotation of the storage items or storage containers, and the front wheels and rear wheels The rotating shelf is equipped with a pallet containing mushroom cultivation containers suspended from the suspension point within the storage space, and a water / fertilizer addition port. The means include identifying the user (cultivator) using a characterization algorithm, identifying the stored items (plants) using a stored item characterization algorithm, transporting the stored items by a transport vehicle using the aforementioned driving algorithm, loading and unloading by the user using the aforementioned height control algorithm, horizontal rotation using the aforementioned horizontal rotation algorithm for 360-degree viewing, homogenizing the environment between storage containers within the shelf using the aforementioned environment homogenization algorithm, shortening the transport distance by the arrangement of the shelf, optimizing cultivation using the aforementioned position information analysis algorithm, detecting dynamic objects using the aforementioned position information analysis algorithm, and detecting disorganization using the aforementioned position information analysis algorithm.

[0227] The mushroom cultivation shelf robot assumes that storage containers (cargo) without dividers are used as one layer, and assuming the height / width and depth of the storage containers are the same as JIS standard pallets (1.1m x 1.1m), then assuming three layers, the shelf will be 2.2m to 29.7m long. If the width / length and depth of the storage containers are 1.1m / 1.1m and 1.1m respectively, it was shown that the ratio of easily accessible storage containers to floor area allows for the storage of two to five containers in the space of one flat area. In this shelf, the ground clearance of the first, second, and third layers is 0m, 1.1m, and 2.2m, respectively, and the minimum ground clearance of all storage containers is easy to transport.

[0228] [Table 59]

[0229] [Table 60]

[0230] [Table 61]

[0231] The detection of disorganization involves the registration and history of specific (quantitative and qualitative) information, and image analysis (location information) can reveal how stored items are placed. The burden on users can be reduced by maintaining a uniform environment within the shelves, registering and updating individual mushrooms and managing inventory, and setting user-friendly locations and transportation.

[0232] (Example 24; Aquatic organism breeding shelf robot) Conventional multi-tiered shelving systems for aquatic organism rearing have three main problems, in addition to the lack of height control to manage the height of stored items. The first problem is the inability to detect the disorganization of stored items, which may stem from the absence of a system to detect factors affecting the growth of aquatic organisms. The second problem is the high burden on users. One reason for this is the difficulty in maintaining a uniform environment within the shelves; even if the room temperature is adjusted, it is impossible to prevent environmental fluctuations within the shelves due to differences in height and left-right positioning. Another reason is the need for manual labor for changing or shipping aquatic organisms. The third problem is that artificial intelligence has not been utilized to solve the above problems for all shelves. In addition to the above, shelves that can accommodate items of various sizes according to their size are not yet commonplace. For example, in eel farming, the amount of glass eels caught is only one-twentieth of what it was 50 years ago. Although experimental complete aquaculture has been achieved through recent research, the survival rate is still low, ranging from 0.01% to 1.6%, compared to the 90% survival rate in the production of other fish. Furthermore, the period from hatching to metamorphosis from pre-leptocephalus or leptocephalus to glass eel has become longer, and the use of eels as feed is limited due to the use of shark eggs. There are many problems in determining the optimal rearing environment for mass production of eel seedlings, and practically speaking, artificial intelligence has not been utilized to achieve the development of inexpensive and effective feed, improve survival rates, and shorten the metamorphosis period.

[0233] An aquatic organism rearing shelf robot according to an embodiment of the present invention comprises: a basic shelf structure; a storage item label structure; a structure for identifying the user and controlling the height of the storage items; a structure for transporting the storage items or storage containers; a structure for moving the storage items or storage containers forward / backward; a structure for reflecting settings made at one location within the shelf to all the storage items or storage containers on the shelf; a structure for shortening the distance and time of movement to the storage items or storage containers; a structure for stopping the rotation of the storage items or storage containers without gravity; a structure for horizontal rotation of the storage items or storage containers; and a rotating shelf suspended in the storage space from suspension points located at the front and rear wheels. The system is equipped with aquatic organism breeding containers on a pallet and water / fertilizer addition ports, and the means include identifying the user (breeder) using a characterization algorithm, identifying the stored items (aquatic organisms) using a stored item characterization algorithm, transporting the stored items by a transport vehicle using the aforementioned driving algorithm, loading and unloading by the user using the aforementioned height control algorithm, horizontal rotation using the aforementioned horizontal rotation algorithm for 360-degree viewpoint, homogenization of the environment between storage containers on the shelves using the aforementioned environment homogenization algorithm, shortening of transport distance by the arrangement of the shelves, optimization of aquatic organism breeding using the aforementioned position information analysis algorithm, detection of dynamic objects using the aforementioned position information analysis algorithm, and detection of disorganization using the aforementioned position information analysis algorithm.

[0234] The aquatic organism breeding shelf robot assumes that storage containers (cargo) without dividers are arranged in one tier. Assuming the height / width and depth of the storage containers are the same as a JIS standard pallet (1.1m x 1.1m), and the width / length and depth of the storage containers are 0.7m / 0.7m and 0.7m, the shelf height will range from 1.4m to 4.9m. The ratio of easily accessible storage containers to floor area shows that three containers can be stored in the space of one flat area. In this shelf, the ground clearance of the first, second, and third layers is 0m, 0.7m, and 1.4m, respectively, and the minimum ground clearance of all storage containers is easy to transport.

[0235] [Table 62]

[0236] [Table 63]

[0237] [Table 64]

[0238] The detection of disorganization allows for the identification of factors affecting development, and can reveal the factors necessary to achieve the development of inexpensive and effective feed, increased survival rates, and a shortened metamorphosis period from pre-leptocephalus or leptocephalus to glass eel. The high burden on users can be reduced by maintaining a uniform environment within the shelves, registering, updating, and managing the inventory of aquatic organisms, and setting user-friendly locations and transportation.

[0239] (Example 25; Freezer or refrigerated shelf robot) Conventional multi-tiered freezer or refrigerator shelves have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that it is not possible to detect the disorganization of stored items, and this disorganization cannot be detected after users have moved items in and out. This disorganization is due to the fact that the memory of the stored items' positions is not utilized. The second problem is that it is highly burdensome, and even if the temperature is adjusted, it is not possible to prevent environmental fluctuations within the shelf due to differences in height and left / right positioning. The third problem is that artificial intelligence is not used to solve the above problems for all shelves. In addition to the above, shelves that can store items of various sizes according to the size of the stored items are not yet commonplace. For example, in a typical freezer or refrigerator shelf, users rely only on visual information for the stored items, so when opening and closing the contents, the entire space must be visible from the front, and the opening and closing is greatly affected by the outside temperature. In order to make the opening and closing doors only for the space that the user needs, information only for the location that the user needs is required.

[0240] A refrigerated shelf robot or refrigerator shelf robot according to an embodiment of the present invention comprises a basic shelf structure, a component for labeling the stored items, a component for identifying the user and controlling the height of the stored items, a component for refrigerating and freezing the inside of the shelf, a small opening / closing door and a conventional door that opens and closes the entire shelf, a component for moving the stored items or storage containers forward / backward, and storage containers suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels. The means include identifying the user by a characterization algorithm, identifying the stored items by a stored item characterization algorithm, rearranging the stored items, loading and unloading by the user by a height control algorithm, homogenizing the environment between storage containers inside the shelf by an environment homogenization algorithm, and detecting disorganization by a position information analysis algorithm.

[0241] The AI-controlled freezer or refrigerator robot is designed with two shelves, one above the other, and is intended to store containers in a single shelf without dividers. Assuming the height / width and depth of the storage containers are 0.4m / 0.4m and 0.2m respectively, it was shown that the ratio of easily accessible storage containers to floor area allows for the storage of two to five containers in the space of one. The minimum ground clearance of the shelves for the first, second, and third layers during loading and unloading between ground levels is 0m, 0.4m, and 0.8m, respectively. In the combination of upper and lower shelves, two combinations of lower shelves (shelf numbers 3-4) and two combinations of upper shelves (shelf numbers 1-2) allow for retrieval, while in the case of a single shelf, five combinations (shelf numbers 1-5) allow for retrieval.

[0242] [Table 65]

[0243] [Table 66]

[0244] [Table 67]

[0245] The detection of disorganization involves the registration and history of specific (quantitative and qualitative) information, allowing users to avoid relying solely on visual information for stored items. This also requires wider doors to allow the entire space to be visible from the front when opening and closing, and minimizes the impact of outside temperature during opening and closing. The high burden on users can be reduced through user-centric receiving, registration / update, and inventory management.

[0246] (Example 26; Electronic Document Shelf Robot) Conventional multi-tiered shelving systems for electronic documents have three problems in addition to the lack of height control to manage the height of stored items. The first problem is that, although it is known that users of electronic documents do not always return stored items to the same location from which they were retrieved, the lack of organization is not detected when users return stored items (including supplementary materials that serve as guides to the electronic document, or specimens accompanying the document, if there are original materials corresponding to the electronic document). The second problem is the high burden it places on users; the larger the scale, the more time and effort it takes for users to find and retrieve stored items, and the greater the effort and burden required for inventory management or rearrangement. The third problem is that artificial intelligence has not been used to solve the above problems for all shelving systems. In addition to the above, shelving systems that can store items of various sizes according to the size of the stored items are not yet commonplace. Electronic document storage systems may only involve the creation and storage of electronic documents as an operational challenge in the review and selection process for government-backed loan and subsidy programs, or they may involve the application, approval, storage, and auditing of materials for GXP (Government Expansion Program). Structurally, they may or may not include raw data, and none of these systems are operated using artificial intelligence.

[0247] An electronic document shelf robot according to an embodiment of the present invention comprises the shelf basic structure, a storage container (storage box) suspended in the storage space from suspension points of a rotating shelf located at the front and rear wheels, a component for identifying the user and controlling the height of the stored items, a component for transporting the stored items or storage container, a component for the forward / backward movement of the stored items or storage container, a component for shortening the travel distance and travel time of the stored items or storage container, and a component for horizontal rotation of the stored items or storage container. The means include identifying the user (electronic document user) by a characterization algorithm, identifying the stored items by a stored item characterization algorithm, transporting the stored items by a transport vehicle using a travel algorithm, retrieval and return by the user using a height control algorithm, horizontal rotation using a horizontal rotation algorithm for 360-degree viewpoint, detection of dynamic objects using a position information analysis algorithm, and detection of disorganization using a position information analysis algorithm.

[0248] The electronic document shelving robot ensures that all storage container areas are easily accessible, allowing users to set the retrieval position of stored items according to their needs. Assuming that one bookshelf has two shelves sufficient to store A4-sized books, and that the height / width and depth of the storage containers are 70cm / 70cm and 35cm respectively, the ratio of easily accessible storage containers to floor space indicates that two to five storage units can be stored in the space of one flat floor. The minimum ground clearance for shelves with only one layer (shelves 1 and 2), shelves with up to two layers (shelves 3 and 4), and shelves with up to three layers are 0m, 70cm, and 1.4m, respectively, limiting access to shelves up to the third layer for children and wheelchair users. The height of the AI-controlled electronic document shelving for all users ranges from approximately 1m to 5.08m, but children and wheelchair users can utilize shelves up to the third layer.

[0249] [Table 68]

[0250] [Table 69]

[0251] [Table 70]

[0252] Detecting disorganization involves registering and recording specific (quantitative and qualitative) information, and image analysis (location information) can reveal how stored items are placed. The high burden on users lies in checking history and inventory status during daily management and transportation during inventory counts. This burden can be reduced by utilizing artificial intelligence for registration and updates, user-centered receiving, user-returns, daily management, and transportation by designated carriers. [Explanation of symbols]

[0253] 1 Shelf Robot 10 Rotation axis 20 Rotating Shelves 21 Storage space 22 Storage Spaces 23 Shelf rotation drive unit 24 Front and rear moving plate 30 Front panel 31 Loading / unloading entrance 33 Front plate rotation drive unit 34 Label reader 35 Image acquisition device (camera) 36. Image acquisition device (camera) 37. Near-field communication device (NFC reader) 38. Audio Listener 40 Rear plate 50 Computer Systems 51 Arithmetic Processing Unit 52. Storage Devices (Databases) 61 User determination means 62. Means for identifying stored items 63. Means for identifying the target storage space 64 Carrying in / out position determining means 71. Means of transporting storage space 72 Means of moving the loading / unloading entrance 211, 221 Storage containers 351 Storage container image data 651 Stop control algorithm 661 High / Low Control Algorithm 662 High / Low Control 671 Weight measurement algorithm 672 Weight measurement 673 Weight scale 681 Liquid volume adjustment algorithm 682 Inclination control 683 Tilt device 691 Horizontal rotation algorithm 692 Horizontal rotation control 693 Horizontal Rotating Plate 701 Environmental homogenization algorithm 702 Environmental homogenization control

Claims

1. The axis of rotation and A rotating shelf that can rotate around the aforementioned rotation axis, A shelf rotation drive unit that rotates the aforementioned rotating shelf around the rotation axis, Control unit and A shelf robot equipped with, The aforementioned rotating shelf has multiple storage spaces arranged along a virtual circle centered on the rotation axis. The control unit, A target storage space identification means for identifying the storage space in which the item the user intends to retrieve is currently stored (referred to as the target storage space) among the aforementioned multiple storage spaces, A means for determining the loading / unloading position of the stored items according to the attributes of the user, A storage space moving means that moves the target storage space to the discharge position by controlling the shelf rotation drive unit to rotate the rotating shelf around the rotation axis, and A shelf robot equipped with this feature.

2. The shelf robot according to claim 1, wherein in the rotating shelf, the plurality of storage spaces are arranged in a ring along a single virtual circle to form a single layer, and the layer is set up in multiple concentric circles around the rotation axis.

3. The shelf robot according to claim 1, further comprising a front plate on the loading / unloading side of the rotating shelf, with a loading / unloading opening corresponding to the loading / unloading position formed therein.

4. The control unit further comprises storage item identification means for identifying items stored in the storage space, The shelf robot according to claim 3, wherein the target storage space identification means selects a target storage item that the user intends to retrieve from among the storage items identified by the storage item identification means, and identifies the storage space in which the selected target storage item is stored as the target storage space.

5. The control unit further comprises user determination means for determining at least one of the user's physical characteristics, posture, or personal identification information as the user's attributes, The shelf robot according to claim 3, wherein the loading / unloading position determination means determines the loading position based on the attributes determined by the user determination means.

6. The shelf robot according to claim 4, wherein the storage item identification means identifies the storage items stored in the storage space using code reading technology.

7. The shelf robot according to claim 5, wherein the user determination means determines the user's attributes using image recognition technology.

8. The system further comprises an image capture device for photographing users handling stored items, and a user determination means for determining the user from the image captured by the image capture device. The shelf robot according to claim 1, wherein the control unit generates a location information algorithm based on the result determined by the user determination means, thereby executing an operation record required by GXP, which is a public standard for ensuring the reliability of operations regarding information on who did what and when.

Images