FORM 2
THE PATENTS ACT, 1970 (39 of 1970) THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(See section 10; rule 13)
TITLE OF THE INVENTION
SYSTEM AND METHOD FOR MANAGING AND CONTROLLING AUTONOMOUS MOBILE
ROBOTS
APPLICANT
JIO PLATFORMS LIMITED
of Office-101, Saffron, Nr. Centre Point, Panchwati 5 Rasta, Ambawadi, Ahmedabad -
380006, Gujarat, India; Nationality : India
The following specification particularly describes
the invention and the manner in which
it is to be performed

RESERVATION OF RIGHTS
[0001] A portion of the disclosure of this patent document contains material,
which is subject to intellectual property rights such as but are not limited to, copyright, design, trademark, integrated circuit (IC) layout design, and/or trade 5 dress protection, belonging to Jio Platforms Limited (JPL) or its affiliates (hereinafter referred as owner). The owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all rights whatsoever. All rights to such intellectual property are fully 10 reserved by the owner.
TECHNICAL FIELD OF DISCLOSURE
[0002] The present disclosure generally relates to a field of robotics,
automation, and telecommunication. More precisely, the present disclosure pertains to a system and a method for centrally managing and controlling Autonomous 15 Mobile Robots (AMRs).
BACKGROUND OF DISCLOSURE
[0003] The following description of related art is intended to provide
background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the 20 present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.
[0004] The use of forklifts in warehouses may present certain dangers and
risks if not managed properly. Forklift operators may be at risk of accidents and 25 injuries if they are not adequately trained, lack experience, or fail to follow safety protocols. The operator may be at risk of collisions, falls, being struck by falling objects, or tipping over the forklift. Warehouse workers and other employees
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working in the vicinity of forklift operations may be at risk of accidents if they are not aware of the forklift's movements or fail to follow designated pedestrian walkways. Inadequate separation of pedestrian and forklift traffic may lead to collisions and serious injuries. There is, therefore, a need to come up with 5 automated solutions to manage the processes in the warehouse.
[0005] Edge computing technology is a distributed computing paradigm that
brings data processing and storage closer to the source of data generation, enabling faster response times, reduced latency, and improved efficiency. Unlike traditional cloud computing, where data is sent to a central data center for processing, edge
10 computing processes data at or near the edge of the network, where the data is being generated. In edge computing, small-scale data centers, or edge nodes, are deployed at the edge of the network infrastructure, such as in proximity to IoT devices, mobile base stations, or local networks. These edge nodes may perform computational tasks, store data, and provide real-time analytics, eliminating the need to send all
15 data to a centralized cloud environment for processing.
[0006] Fleet management systems are software platforms or solutions used
by organizations to efficiently manage and monitor their vehicle fleets. These systems provide a range of features and functionalities that help optimize fleet operations, improve safety, reduce costs, and enhance overall productivity. Instead
20 of relying on foreign suppliers or manufacturers, indigenous 5G radios are designed and produced domestically, often with the aim of promoting local technology development, fostering economic growth, and ensuring national security. Private 5G refers to a local and dedicated 5G network that is deployed and operated by a specific organization or enterprise for its own private use. Unlike public 5G
25 networks that are provided by telecommunication companies and available to the public, private 5G networks are designed to serve the connectivity needs of a specific entity in a closed environment.
[0007] Existing systems for warehouse robots vary depending on the
specific requirements and applications. Automated Guided Vehicles (AGVs) are
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mobile robots that follow predefined paths or markers on the floor to transport goods within a warehouse. Drawbacks of the AGVs include limited flexibility, as the AGVs typically operate on fixed routes and may require infrastructure modifications to accommodate their navigation. AGVs may also have slower 5 speeds compared to other robotic systems. Autonomous Mobile Robots (AMRs) are more flexible than AGVs as they can navigate autonomously using built-in sensors, cameras, and mapping capabilities. However, none of the industrial warehouse AMRs have been developed to operate wirelessly over a private 5G network. The main drawbacks of the existing systems are that implementing robots
10 in the warehouse may involve high initial costs for equipment, integration, and infrastructure modifications. The return on investment needs to be carefully evaluated. Robotic systems require regular maintenance and may experience downtime due to mechanical failures or software issues. Maintenance tasks and downtime may impact operational efficiency and productivity. Warehouse layouts,
15 inventory, and processes may evolve over time. Ensuring that warehouse robots adapt to these changes and integrate with new technologies or workflows can be a challenge.
[0008] There is, therefore, a need to overcome the above drawbacks and
limitations in the current practices to provide an adaptable and low-cost robotic 20 system to be used in various applications. The system in the present disclosure offers high speed at a low cost and has a dynamic capability to adapt to the various needs of the user.
SUMMARY
[0009] Within the scope of this application, it is expressly envisaged that the
25 various aspects, embodiments, examples, and alternatives set out in the preceding paragraphs, in the claims and/or in the following description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. Features described in connection with one embodiment are applicable to all embodiments unless such features are incompatible.
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[0010] The present disclosure discloses a system for centrally managing and
controlling a plurality of Autonomous Mobile Robots (AMRs). The system includes a network module configured to provide a private network coverage for each of the plurality of AMRs. The system includes a Fleet Management System (FMS) 5 deployed over an edge of network, configured to provide one or more real-time instructions to the plurality of AMRs. The system includes a computing module installed within each of the plurality of AMRs to enable seamless communication among the plurality of AMRs and the FMS over the private network based on the one or more real-time instructions. The one or more real-time instructions are 10 provided to manage and control operations of the plurality of AMRs.
[0011] In an embodiment, to provide the private network coverage, the
network module includes a distributed antenna system powered by an Outdoor Small Cell (ODSC).
[0012] In an embodiment, deployment of the FMS over the edge of network
15 provides Ultra Reliable Low Latency Communication (URLLC).
[0013] In an embodiment, the plurality of AMRs is equipped with an
artificial intelligence for navigating each of the plurality of AMRs along dynamic routes and detecting obstacles in real-time.
[0014] In an embodiment, the network module provides a wider signal
20 propagation, support for high device density, and secure connectivity over a licensed spectrum.
[0015] The present disclosure discloses a method for centrally managing
and controlling a plurality of Autonomous Mobile Robots (AMRs). The method includes establishing, by a network module, a private network coverage for each of 25 the plurality of AMRs. The method includes providing, by a Fleet Management System (FMS), one or more real-time instructions to the plurality of AMRs. The method includes upgrading, by a computing module, the plurality of AMRs to enable seamless communication among the plurality of AMRs and the FMS over
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the private network based on the one or more real-time instructions. The one or more real-time instructions is provided to manage and control operations of the plurality of AMRs.
[0016] In an embodiment, the method includes achieving Ultra Reliable
5 Low Latency Communication (URLLC) between the FMS and the plurality of AMRs.
[0017] In an embodiment, the method includes enabling navigation for the
plurality of AMRs using an artificial intelligence for dynamic routing and obstacle detection in real-time.
10 [0018] The present disclosure discloses user equipment (UE) configured to
manage and control a plurality of Autonomous Mobile Robots (AMRs). The UE includes a processor and a computer readable storage medium storing programming for execution by the processor. The programming including instructions to establish a private network coverage through a network module for each of the plurality of
15 AMRs, provide one or more real-time instructions to the plurality of AMRs through a Fleet Management System (FMS) and via the UE, and upgrade, via the computing module, the plurality of AMRs to enable seamless communication among the plurality of AMRs and the FMS over the private network based on the one or more real-time instructions. The one or more real-time instructions are provided to
20 manage and control operations of the plurality of AMRs.
[0019] Various objects, features, aspects, and advantages of the inventive
subject matter will become apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.
25 OBJECTS OF THE PRESENT DISCLOSURE
[0020] Some of the objects of the present disclosure, that at least one
embodiment herein satisfy are as listed herein below.
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[0021] An object of the present disclosure is to overcome the drawbacks and
limitations of the existing systems and to provide a system and a method for centrally managing and controlling a plurality of AMRs.
[0022] An object of the present disclosure is to provide a robust and reliable
5 network infrastructure that provides high-speed, and low-latency connectivity.
[0023] An object of the present disclosure is to use AMRs to perform tasks
like picking, sorting, packing, and transporting goods, for example, within a warehouse, manufacturing facilities, distribution centers, retail spaces, hospitals, and other industrial or commercial settings.
10 [0024] An object of the present disclosure is to provide crucial information
about inventory levels, environmental conditions, and equipment performance to a warehouse management.
[0025] An object of the present disclosure is to handle real-time data
processing, analytics, and decision-making, reducing latency and enabling faster 15 response times for warehouse operations.
[0026] An object of the present disclosure is to include task scheduling and
optimization algorithms, fleet management software, inventory management systems, and interfaces for human operators to monitor and control robotic operations.
20 [0027] An object of the present disclosure is to automate operations,
wherein users may remain involved in overseeing and managing the overall system to monitor the operations, handle exceptions, provide maintenance and troubleshooting, and ensure the system operates smoothly.
[0028] An object of the present disclosure is to operate in a coordinated
25 manner, leverage connectivity (for example, 5G, 6G, or any higher generation connectivity), incorporate data analytics and robotic automation to enable efficient and streamlined operations.
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BRIEF DESCRIPTION OF DRAWINGS
[0029] The accompanying drawings, which are incorporated herein, and
constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same 5 parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that disclosure of such 10 drawings includes the disclosure of electrical components, electronic components or circuitry commonly used to implement such components.
[0030] FIG. 1A illustrates an exemplary network architecture of a system for centrally managing and controlling a plurality of AMRs, in accordance with an embodiment of the present disclosure.
15 [0031] FIG. 1B illustrates a system diagram of an Outdoor Small Cell (ODSC) powered Distributed Antenna System (DAS), in accordance with an embodiment of the present disclosure.
[0032] FIG. 1C illustrates an architecture of a system for centrally managing and controlling a plurality of AMRs, in accordance with an embodiment of the 20 present disclosure.
[0033] FIG. 2 illustrates an exemplary block diagram of various modules within the system configured to centrally manage and control a plurality of AMRs, in accordance with an embodiment of the present disclosure.
[0034] FIG. 3A illustrates an exemplary scenario for an AMR transporting
25 empty bags from inbound to one or more staging locations within a warehouse, in accordance with an embodiment of the present disclosure.
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[0035] FIG. 3B illustrates an exemplary scenario for an AMR transporting of loaded pallets from a bagging line to one or more storage locations, in accordance with an embodiment of the present disclosure.
[0036] FIG. 4 illustrates a flow diagram of a method for centrally managing 5 and controlling a plurality of AMRs, in accordance with an embodiment of the present disclosure.
[0037] FIG. 5 illustrates an exemplary computer system in which or with which embodiments of the present disclosure may be implemented, in accordance with an embodiment of present disclosure.
10 [0038] FIG. 6 illustrates another exemplary computer system in which or with which the embodiments of the present disclosure may be implemented, in accordance with an embodiment of present disclosure.
LIST OF REFERENCE NUMERALS
100A – Network Architecture 15 102-1, 102-2…102-N - Users
104-1, 104-2…104-N - User Equipment (UE)
106 – Network
108 – System
110 – Entity 20 112 – Centralized Server
114 – Processing engine(s)
100B – Example System Diagram of the Outdoor Small Cell (ODSC)
116 – ODSC powered Distributed Antenna System (DAS)
118 – Warehouse 25 100C – Architecture Diagram of the system
120 – Cloud
122 – Network core
124 – gNB
126 – Conveyor to Storage
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128 – Remote Access
130 – Inbound to Staging
200 – Example block diagram of the system
202 – Processor(s) 5 204 – Memory
206 – Interface(s)
208 – Processing engine(s)
210 – Network Module
212 – Fleet Management System (FMS) 10 214 – Control module
216 – Edge computing module
218 – Computing module
220 – Human Machine Interaction (HMI) module
222 – Database 15 300 - Example scenarios of various AMRs used in the system
302 – AMR
304 - Trolley with empty bags
306 - AMR for pallet transfer
308 – Loaded Pallet 20 500 - Example computer system in which embodiments may be implemented
502 - Input devices
504 - Central Processing Unit (CPU)
506 - Data flow and control flow
508 - Output devices 25 510 - Secondary storage devices
512 - Control unit
514 - Arithmetic and Logical Unit (ALU)
516 - Memory unit
600 – Example computer system 30 610 – External storage device
620 – Bus
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630 – Main memory 640 – Read-only memory 650 – Mass storage device 660 – Communication port(s) 5 670 – Processor
DETAILED DESCRIPTION
[0039] In the following description, for explanation, various specific details
are outlined in order to provide a thorough understanding of embodiments of the
10 present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed
15 above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0040] The ensuing description provides exemplary embodiments only and
is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those 20 skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.
[0041] Specific details are given in the following description to provide a
25 thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known
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circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.
[0042] Also, it is noted that individual embodiments may be described as a
process that is depicted as a flowchart, a flow diagram, a data flow diagram, a 5 structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to a method, a function, a 10 procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0043] The word “exemplary” and/or “demonstrative” is used herein to
mean serving as an example, instance, or illustration. For the avoidance of doubt,
15 the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms
20 “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive like the term “comprising” as an open transition word without precluding any additional or other elements.
[0044] Reference throughout this specification to “one embodiment” or “an
25 embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment.
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Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0045] The terminology used herein is to describe particular embodiments
only and is not intended to be limiting the disclosure. As used herein, the singular 5 forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other 10 features, integers, steps, operations, elements, components, and/or groups thereof. As used herein, the term “and/or” includes any combinations of one or more of the associated listed items.
[0046] The present disclosure generally relates to a robotics system that
leverages high speed network (for example, 5G network, 6G network, or any other
15 higher generation network) and edge computing technologies to revolutionize warehouse logistics and supply chain management. More precisely, the present disclosure relates to a system and a method for centrally managing and controlling a plurality of Autonomous Mobile Robots (AMRs). The disclosed system is configured to perform tasks or actions involving warehouse robotic automation
20 which focuses on using robots (i.e., AMRs) to automate various processes within the warehouse environment, such as picking, sorting, packing, and transporting goods. The disclosed system introduces a comprehensive solution for 24x7 material movement using the plurality of AMRs, eliminating a need for forklifts, and enhancing safety and efficiency.
25 [0047] As will be appreciated, while the various embodiments of the present
disclosure have been described with respect to a warehouse environment, it should be understood that the disclosure is not limited to such specific application. The principles and features of the present disclosure for centrally managing and controlling the plurality of AMRs may be equally applicable to other environments
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where centralized management and control of AMRs may be required. This includes, but is not limited to, manufacturing facilities, distribution centers, retail spaces, hospitals, and other industrial or commercial settings. Accordingly, the present disclosure should not be restricted to the disclosed embodiments but should 5 be interpreted broadly within the scope of the claims.
[0048] As will be described in greater detail in conjunction with FIGS. 1-6,
the disclosed system deploys a Fleet Management System (FMS) over an edge of a high speed network (for example, a 5G network, or a 6G network) to manage and control operations of the plurality of AMRs, ensuring ultra-reliable low latency
10 communications (URLLC), for example, less than 25ms. Further, a private network is provided for indoor coverage for the plurality of AMRs. Further, the plurality of AMRs may be upgraded through an integrated computing module (e.g., Mini-PCs and network modules) for seamless communication among the plurality of AMRs and the FMS over the private network. Additionally, each of the AMRs may be
15 equipped with artificial intelligence to navigate along dynamic routes and avoid obstacles in real-time during operation.
[0049] The disclosed system improves upon existing solutions by offering
high data rates, low latency, and scalability, addressing the limitations of legacy Wi-Fi networks. It enhances efficiency, safety, and operational flexibility, 20 providing a robust, scalable solution for modern warehouse automation.
[0050] The various embodiments throughout the disclosure will be
explained in more detail with reference to FIGS. 1-6.
[0051] FIG. 1A illustrates an exemplary network architecture (100A) of a
system (108) for centrally managing and controlling a plurality of AMRs, in 25 accordance with embodiments of the present disclosure.
[0052] Referring to FIG. 1A, the network architecture (100) includes one or
more computing devices or user equipment (UE) (104-1, 104-2…104-N) associated with one or more users (102-1, 102-2…102-N) in an environment. A person of
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ordinary skill in the art will understand that one or more users (102-1, 102-2…102-N) may be individually referred to as the user (102) and collectively referred to as the users (102). Similarly, a person of ordinary skill in the art will understand that one or more user equipment (104-1, 104-2…104-N) may be individually referred 5 to as the user equipment (104) and collectively referred to as the user equipment (104). A person of ordinary skill in the art will appreciate that the terms “computing device(s)” and “user equipment” may be used interchangeably throughout the disclosure. Although three user equipment (104) are depicted in FIG. 1, however any number of the user equipment (104) may be included without departing from 10 the scope of the ongoing description.
[0053] In an embodiment, the user equipment (104) includes smart devices
operating in a smart environment, for example, an Internet of Things (IoT) system. In such an embodiment, the user equipment (104) may include, but may not be limited to, smartphones, smart watches, smart sensors (e.g., mechanical, thermal,
15 electrical, magnetic, etc.), networked appliances, networked peripheral devices, networked lighting system, communication devices, networked vehicle accessories, networked vehicular devices, smart accessories, tablets, smart television (TV), computers, smart security system, smart home system, other devices for monitoring or interacting with or for the users (102) and/or entities, or any combination thereof.
20 A person of ordinary skill in the art will appreciate that the user equipment (104) may include, but may not be limited to, intelligent, multi-sensing, network-connected devices, that may integrate seamlessly with each other and/or with a central server or a cloud-computing system or any other device that is network-connected.
25 [0054] In an embodiment, the user equipment (104) includes, but is not
limited to, a handheld wireless communication device (e.g., a mobile phone, a smartphone, a phablet device, and so on), a wearable computer device (e.g., a head-mounted display computer device, a head-mounted camera device, a wristwatch computer device, and so on), a Global Positioning System (GPS) device, a laptop
30 computer, a tablet computer, or another type of portable computer, a media playing
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device, a portable gaming system, and/or any other type of computer device with wireless communication capabilities, and the like. In an embodiment, the user equipment (104) includes, but is not limited to, any electrical, electronic, electro-mechanical, or an equipment, or a combination of one or more of the above devices 5 such as virtual reality (VR) devices, augmented reality (AR) devices, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, mainframe computer, or any other computing device, wherein the user equipment (104) may include one or more in-built or externally coupled accessories including, but not limited to, a visual aid device such as a camera, an audio aid, a microphone, 10 a keyboard, and input devices for receiving input from the user (102), or the entity (110) such as touch pad, touch enabled screen, electronic pen, and the like. A person of ordinary skill in the art will appreciate that the user equipment (104) may not be restricted to the mentioned devices and various other devices may be used.
[0055] Referring to FIG. 1A, the user equipment (104) communicates with
15 a system (108), through a network (106). In an embodiment, the network (106) may
include, but may not be limited to, a Fifth Generation (5G) network, Sixth
Generation (6G) network, or any high generation network that may be capable of
providing seamless communication to manage and control the plurality of AMRs.
In particular, the network (106) enables the user equipment (104) to communicate
20 with other devices in the network architecture (100) and/or with the system (108)
to manage and control a plurality of AMRs. The network (106) includes a wireless
card or some other transceiver connection to facilitate this communication. In
another embodiment, the network (106) is implemented as, or include any of a
variety of different communication technologies such as a wide area network
25 (WAN), a local area network (LAN), a wireless network, a mobile network, a
Virtual Private Network (VPN), the Internet, the Public Switched Telephone
Network (PSTN), or the like.
[0056] In another exemplary embodiment, the centralized server (112)
includes by way of example but not limitation, one or more of: a stand-alone server,
30 a server blade, a server rack, a bank of servers, a server farm, hardware supporting
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a part of a cloud service or system, a home server, hardware running a virtualized server, one or more processors executing code to function as a server, one or more machines performing server-side functionality as described herein, at least a portion of any of the above, some combination thereof.
5 [0057] The system (108) includes a processing engine (114). The processing
engine (114) of the system (108) may further include various modules to centrally manage and control the plurality of AMRs. These modules are explained in detail in conjunction to FIG. 2.
[0058] Referring to FIG. 1B, a system diagram (100B) of an Outdoor Small
10 Cell (ODSC) (116) powered Distributed Antenna System (DAS) is illustrated. It should be noted that the ODSC (116) is placed in an Information Technology (IT) room near a warehouse (118). The ODSC (116) is used for the network core (for example, a 5G core). The ODSC (116) is a product in a network ecosystem (for example, 5G ecosystem) that delivers the required capacity at the hotspots under 15 the umbrella of the 5G network. It is a compact, single-box, zero-footprint solution which may be deployed on a 10-15 metre pole, to provide the intended coverage and capacity. The DAS powered by the ODSC (116) provides a private network (for example, a private 5G network, a private 6G network, or any other high generation network) that may be accessed by the AMRs within the warehouse 20 (118). It should be noted that in some embodiments, instead of the warehouse (118), the private network may also be provided for other environments where centralized management and control of the plurality of AMR may be required. This may include, but not limited to, manufacturing facilities, distribution centers, retail spaces, hospitals, and other industrial or commercial settings.
25 [0059] The ODSC (116) may use a fiber to connect to a core network. In
some embodiments, the ODSC (116) may be connected to the core network via wireless connections, such as, but not limited to, Wi-Fi, microwave links, or millimeter-wave links, or the like. The ODSC (116) is a four-transmit four-receive (4T4R) all-in-one self-contained unit that houses entire gNodeB (gNB)
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functionality including baseband, radio transceivers, and RF front end. Further, the ODSC (116) is designed to operate in, for example, 3.5 GHz spectrum with a bandwidth of 100 MHz and radiated power of 25 Watts. The ODSC (116) delivers, for example, 1.5 Gbps data throughput in downlink and 75 Mbps in uplink. The 5 private network used by the disclosed system 108 enables a seamless integration of the plurality of AMRs into the network and may also provide low-latency connectivity, enabling real-time communication and supporting applications that demand quick response times, such as industrial automation and robotics. By deploying the private network, the disclosed system 108 may have dedicated and 10 scalable network resources to support a large number of connected devices (such as the AMRs) and applications within the warehouse (118).
[0060] Referring to FIG. 1C, an architecture (100C) of a system (108) for
centrally managing and controlling the plurality of AMRs is illustrated, in accordance with an embodiment of the present disclosure. As depicted in the
15 present FIG. 1C, a main network core (122) is connected to a cloud server 120 to connect to one or more FMS servers (e.g., FMS server 1 and FMS server 2). The private network is enabled by a gNB (124) and is used to connect to the plurality of AMRs performing various tasks in the warehouse (118). The FMS may be operated remotely through remote access (128) using a Virtual Private Connection (VPN)
20 and an IPv6 protocol. Each of the AMRs is integrated with a computing module (e.g., Mini-PC and a network module). This enables one AMR to communicate seamlessly over private network with other AMRs and the FMS.
[0061] In an exemplary embodiment, warehouse automation working over
5G network enabled by the private 5G network may be achieved with ultra-reliable
25 low latency communications (URLLC) i.e., less than ~25ms latency in the operation and with this achievement, each of the AMRs may communicate with the FMS flawlessly. Further, with this automation, a 24x7 material movement in warehouse with scalable operation may be achieved. Additionally, the forklift operation inside the warehouse may be eliminated, thus improving safety and efficiency of
30 operations. The main purpose of the 5G-enabled AMRs is to transport goods from
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a conveyor to storage (126) and from an inbound location to a staging location (130). It should be noted that each of the AMRs transporting the loaded pallets may have a predefined loading capacity (e.g., 1 ton). For example, the AMR, having a 1-ton loading capacity, is configured to transport loaded pallets from the conveyor 5 to the storage (126).
[0062] In an embodiment, the architecture 100C of the system 108 (also
referred to as a 5G-enabled warehouse robotic automation system) included multiple layers. The robotic layer consists of the physical robotic devices employed in warehouse operations, i.e., the AMRs. These AMRs perform tasks such as
10 picking, sorting, packing, and transporting goods within the warehouse. A sensor and perception Layer includes various sensors and perception systems that enable the plurality of AMRs to perceive and understand their environment. The communication layer is where the 5G technology plays a significant role. It involves the 5G network infrastructure that provides high-speed, low-latency
15 communication between the robots, sensors, and other devices within the warehouse. This layer ensures reliable and real-time connectivity for seamless data exchange and control.
[0063] In an edge computing layer, edge computing nodes or edge servers
are deployed within the warehouse environment. These nodes handle real-time data
20 processing, analytics, and decision-making in close proximity to the robots and sensors. Edge computing reduces latency, enables faster response times, and relieves the burden on centralized cloud resources. The control and management layer consists of software systems and algorithms responsible for controlling and coordinating the warehouse robotic operations. It includes fleet management
25 software, task scheduling algorithms, motion planning algorithms, and Human-Machine Interfaces (HMIs) that allow operators to monitor and control the system. The cloud infrastructure provides centralized storage, advanced analytics, and long-term data management capabilities.
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[0064] In an embodiment, the plurality of AMRs has a modular structure
consisting of several key components that work together to enable autonomous navigation and operation. The mobile base serves as a foundation of the AMR and provides the physical structure and mobility. It typically consists of a chassis or 5 platform that supports the other components and contains the necessary mechanisms for movement, such as wheels or tracks. The AMRs are also equipped with various sensors that enable perception and mapping of the environment. These sensors can include laser scanners, cameras, depth sensors, LiDAR (Light Detection and Ranging) sensors, and ultrasonic sensors. The sensors gather data about the 10 surrounding environment, detect obstacles, and enable localization and mapping.
[0065] FIG. 2 illustrates an exemplary block diagram of all the modules in
the processing engine of the system, in accordance with an embodiment of the present disclosure.
[0066] Referring to FIG. 2, an exemplary block diagram (200) of various
15 modules in the processing engine (114) of the system (108) is illustrated, in accordance with an embodiment of the present disclosure. The system (108) may include one or more processor(s) (202), a memory (204), one or more interface(s) (206), and a processing engine (208) (analogous to the processing engine (114)). The one or more processor(s) (202), amongst other capabilities, may be configured
20 to fetch and execute computer-readable instructions stored in the memory (204). The one or more processor(s) (202) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. The functions of the various
25 elements shown in the figure, including any functional blocks labeled as “processor(s)”, may be provided through the use of dedicated hardware as well as hardware capable of executing software in association with the appropriate software. The memory (204) may be coupled to the one or more processor(s) (202) and may, among other capabilities, provide data and instructions for generating
30 different requests.
20

[0067] Further, the interface(s) (206) may include a variety of interfaces, for
example, interfaces for data input and output devices, referred to as Input/Output devices, storage devices, and the like. The interface(s) (206) may facilitate communication to/from the system (108). The interface(s) (206) may also provide 5 a communication pathway for one or more components of the system (108). Examples of such components include, but are not limited to, the processing engine (114) and a local database (222).
[0068] The processing engine (208) includes various modules that work
together to enable seamless communication, efficient operation, and real-time data 10 exchange for centrally managing and controlling the plurality of AMRs. These various modules may include a network module (210), a Fleet Management system (212) including a control module (214) and an edge computing module (216), a computing module (218), and the Human Machine Interaction (HMI) module (220).
[0069] In order to manage and control the plurality of AMRs, initially the
15 network module (210) may be configured to provide a private network coverage for
each of the plurality of AMRs. To provide the private network coverage, the
network module (210) may include a Distributed Antenna System (DAS) powered
by the ODSC (116). In an embodiment, the network module (210) may be a private
network module that may provide a private network coverage (for example, a 5G
20 private network coverage, a 6G network private network coverage, or any other
higher generation network coverage) for each of the plurality of AMRs. In an
alternate embodiment, the network module (210) may be a public network module
that may provide a private network coverage for each of the plurality of AMRs. The
network module (210) provides wider signal propagation, support for high device
25 density, and secure connectivity over a licensed spectrum.
[0070] Once the network coverage is provided, the FMS (212) may be
deployed over an edge of the network. The FMS (212) may be configured to provide one or more real-time instructions to the plurality of AMRs to manage and control operations of the plurality of AMRs.
21

[0071] More particularly, the FMS (212) may provide one or more real-time
instructions to the plurality of AMRs for transporting of empty bags and loaded pallets at different locations, for example, within the warehouse (118). This is further explained in conjunction with FIG. 3. The FMS (212) may include the 5 control module (214) and the edge computing module (216).
[0072] In an embodiment, the control module (214) may be responsible for
handling task allocation, motion planning, obstacle avoidance and management for the plurality of AMRs operating in the warehouse. It receives task requests from a warehouse management system (WMS) or other sources and assigns them to an
10 appropriate AMR based on factors such as availability, proximity, and task priority. The control module (214) may incorporate one or more artificial intelligence algorithms for motion planning, allowing the AMRs to determine optimal paths and trajectories to reach their designated destinations. These algorithms consider factors such as obstacles, traffic conditions, and efficiency considerations to ensure safe
15 and efficient navigation. The control module (214) also includes mechanisms for obstacle detection and avoidance. It utilizes data from sensors, such as LiDAR or cameras, to identify potential obstacles or hazards in the AMRs path. Based on this information, the control module (214) adjusts the AMRs trajectory or triggers appropriate actions to avoid collisions. The control module (214) incorporates
20 localization and mapping algorithms to enable the AMRs to determine their own position within the warehouse. This information is crucial for accurate navigation, task execution, and coordination with other AMRs.
[0073] In an embodiment, the edge computing module (214) may be
responsible for low-latency and high-bandwidth communication with the plurality
25 of AMRs operating in the warehouse (118). This proximity reduces the time taken for data transmission and enables faster response times for critical control and decision-making tasks. Further, the edge computing module (216) performs real¬time data processing tasks, such as sensor data analysis, object recognition, and localization. By processing data at the edge, near the source of generation, it reduces
30 the need for transmitting large volumes of raw data to a centralized cloud,
22

minimizing latency and bandwidth requirements. Further, the edge computing module (216) may incorporate machine learning algorithms or other analytical techniques to extract valuable information, detect patterns, or identify anomalies in real-time. This information may be used for optimizing AMRs behavior and 5 improving operational efficiency. Further, the edge computing module (216) enables localized decision-making and control for the each of the AMRs. By utilizing real-time data and analytics at the edge, it may take intelligent decisions based on predefined rules, algorithms, or machine learning models. This allows for quick responses to changing conditions, dynamic task assignments, or adaptive 10 behavior of the plurality of ARMs.
[0074] Further, the computing module (218) may be installed within each
of the plurality of AMRs. The computing module (218) may include a Mini-PC and a network module that is configured to enable seamless communication among the plurality of AMRs and the FMS (212) over the private network based on the one or 15 more real-time instructions provided by the FMS (212).
[0075] In particular, the Mini-PC and network module refers to specific
components and infrastructure that enable high-speed, low-latency connectivity within an environment (for example, a warehouse environment). The Mini-PC and network module is responsible for establishing and maintaining the network (e.g.,
20 5G network) connectivity required for seamless communication between the plurality of AMRs, sensors, and other components within the system. The Mini-PC and network module enables the inclusion of 5G base stations strategically deployed within the warehouse or in close proximity to ensure reliable coverage. These base stations transmit and receive 5G signals, allowing the plurality of AMRs
25 and other components to connect to the network. The Mini-PC and network module also consists of a module for controlling of antennas that receive and transmit the 5G signals between the base stations and the plurality of AMRs. These antennas may be installed on the mobile AMRs themselves or placed at different locations within the warehouse to ensure adequate coverage and signal strength. The module
30 for controlling the antennas that are responsible for transmitting and receiving data
23

over the private network. These antennas convert the data into the appropriate format for wireless transmission and reception, enabling communication between the plurality of AMRs and other components.
[0076] In an embodiment, the HMI module (220) controls interfaces that
5 allow users to visualize and monitor the status and activities of the plurality of AMRs in real-time via the UE (104). This may involve graphical representations of the warehouse layout, robot locations, task progress, and other relevant information. The HMI module (220) provides controls and commands that enable operators to manually intervene in the AMR operation if needed. Operators can initiate actions
10 such as starting or stopping robots, adjusting robot speeds, or overriding certain behaviors. It may also include features that allow operators to assign tasks to specific robots or groups of robots. Operators may prioritize tasks based on urgency, importance, or other criteria, ensuring efficient task execution by the plurality of AMRs. The HMI module (220) enables operators to configure and
15 customize various aspects of the system (108). This includes setting up communication parameters, adjusting system parameters, defining AMR behaviors, or modifying task schedules. In the system (108), the HMI module (220) may facilitate remote management capabilities as the users may monitor and control the system from remote locations using web-based interfaces or dedicated applications,
20 enabling remote supervision and intervention.
[0077] FIGs. 3A and 3B, illustrate exemplary scenarios (300) of the various
AMRs used in the system (108) for transporting goods from one location to another location within the warehouse (118), in accordance with an embodiment of the present disclosure.
25 [0078] As illustrated in FIG. 3A, the FMS (212) may provide instruction to
at least one AMR (302) for transporting empty bags from inbound to one or more staging locations within a warehouse by docking with the trolley (304) loaded with empty bags, carries it and keeps it at the staging location. Upon requirement, the same AMR may also carry the empty trolley from the staging location and bring it
24

to a bag unloading location. The AMR (304) is designed for material handling and towing tasks in warehouse and industrial environments. While specifics of the AMR (304) may vary based on manufacturer or model version, here are some general features and capabilities typically associated with the AMR (304). The 5 AMR (304) is designed to handle material transportation and towing tasks within the warehouse or industrial setting. It can autonomously move and transport heavy loads, carts, or containers, reducing the need for manual labor and increasing operational efficiency. The AMR (304) utilizes advanced navigation and localization technologies to autonomously navigate through the warehouse 10 environment.
[0079] As illustrated in FIG. 3B, for transporting a loaded pallet (308) from
the bagging line to the storage area is implemented with the help of at least one AMR (306), in which the at least one AMR (306) may have a predefined loading capacity (e.g., 1 ton). The loaded pallet (308) is transported from the backend of a
15 palletizer conveyor and drops at a roller conveyor at the storage location. In this entire process, the at least one AMR (306) travels along dynamic routes, detects obstacles as it is powered with artificial intelligence for location and navigation on a real-time basis. The at least one AMR (306) may also be incorporated into the fleet management software that optimizes the movement and task allocation of
20 multiple robots. The software assigns tasks, optimizes routes, and monitors the performance of the fleet to ensure efficient and coordinated operations. The at least one AMR (306) may be controlled and monitored through user interfaces such as touchscreens or web-based dashboards. The user can use these interfaces to assign tasks, monitor robot status, and intervene if needed. The at least one AMR (306)
25 used in the system for product transfer provide numerous benefits, including increased efficiency, reduced labor costs, improved accuracy, and enhanced safety in material handling operations. They offer flexibility and scalability, allowing for easy integration into existing workflows and the ability to adapt to changing operational needs.
25

[0080] In an embodiment, the user may operate the plurality of AMRs from
the controls provided by the interface by adjusting its speed, direction, and load easily through the UE (104). In an embodiment, the FMS may include a Warehouse Management System (WMS) that generates tasks based on the warehouse's 5 operational requirements, including task details such as task type, priority, and location, which are sent to the system (108). The control module (214) receives the task assignments and plans the optimal allocation of tasks to the available AMRs. The control module (214) also considers factors such as AMRs availability, proximity to task location, and task priorities to optimize task allocation. Further,
10 the control module (214) dispatches the selected AMRs to their assigned tasks and navigates through the warehouse environment, avoiding obstacles, and following predefined paths or dynamically. The network module (210) ensures continuous, high-speed communication between the robots, edge computing module (216), and other components of the system. Real-time data, including AMRs status, sensor
15 readings, and environment updates, is transmitted and received through the network. Based on the analyzed data and insights from the edge computing module (216), localized decisions are made for each AMRs. The decision-making includes adapting robot behaviors, adjusting trajectories, prioritizing tasks, or triggering responses to dynamic changes in the environment.
20 [0081] In an embodiment, the user may validate the working of an Industry
4.0 use case of warehouse automation working over 5G enabled by Private 5G network. The system (108) aims to achieve ultra-reliable low latency communications (URLLC) i.e., less than ~25ms latency in the operation and the AMRs are able to communicate with the FMS flawlessly. With this automation, the
25 system enables targeting to achieve a 24x7 material movement in the warehouse with scalable operation and eliminate the forklifts operation inside the warehouse, thus improving safety and efficiency of operations. The AMRs execute their assigned tasks, such as picking up or moving objects, inventory management, or transportation within the warehouse. The HMI module (220) provides real-time
26

monitoring interfaces for human operators to oversee task progress, robot status, and intervene if necessary.
[0082] Referring to FIG. 4, a flow diagram of a method (400) for centrally
managing and controlling the plurality of AMRs, in accordance with an 5 embodiment of the present disclosure. The method (400), at step 402 includes establishing, a network module (210), a private network coverage for each of the plurality of AMRs. The method (400), at step 404 further includes providing, by a Fleet Management System (FMS) (212), one or more real-time instructions to the plurality of AMRs. The method (400), at step 406 further includes upgrading, by 10 computing module (218), the plurality of AMRs (212) to enable seamless communication among the plurality of AMRs (212) and the FMS (206) over the private network based on the one or more real-time instructions. The one or more real-time instructions are provided to manage and control operations of the plurality of AMRs.
15 [0083] In some embodiments, the method (500) further includes achieving
Ultra Reliable Low Latency Communication (URLLC) (for example, less than 25ms between the FMS (212) and the plurality of AMRs). In some embodiments, the method (500) further includes enabling navigation for the plurality of AMRs (212) using artificial intelligence for dynamic routing and obstacle detection in real-20 time.
[0084] Referring to FIG. 5, an exemplary computer system (500) in which
or with which embodiments of the present disclosure may be implemented, in accordance with an embodiment of present disclosure. The computer system includes input devices (502) connected through I/O peripherals. The system also 25 includes a Central Processing Unit (CPU) (504), and Output Devices (508), connected through the I/O peripherals. The CPU (504) is also attached to a memory unit (516) along with an Arithmetic and Logical Unit (ALU) (514), a control unit, (512), along with secondary storage devices (510) such as Hard Disks and a Secure Digital Card (SD). The data flow and control flow (506) are indicated by a straight
27

and dashed arrow respectively. The CPU (504) consists of data registers that hold the data bits, pointers, cache, Random Access Memory (RAM), and a main processing unit containing the processing engine (114). The system also consists of communication buses that are used to transport the data internally in the system 5 (108).
[0085] In an embodiment, the CPU (504) of the system (108) is used to
process all the data that is required for identification of a higher ranked neighbor cell. A person skilled in the art will appreciate that the system may include more than one CPU (504) and communication ports for ease of function. Examples of
10 CPU (504) include, but are not limited to, an Intel® Itanium® or Itanium 2 processor (s), or AMD® Opteron® or Athlon MP® processor (s), Motorola® lines of processors, FortiSOC™ system on a chip processor or other future processors. The CPU (504) may include various modules associated with embodiments of the present invention. The input component can also include communication ports,
15 ethernet ports, gigabit ports, parallel port, or another Universal Serial Bus (USB). The communication port can also be chosen depending on a specific network such as a Wide Area Server (WAN), Local Area Network LAN), or a Personal Area Network (PAN). The communication port can be a RS-232 port that can be used with the remote dialling and internet connection options of the system. A Gigabit
20 port can be used to connect the system to the internet at all times and the Gigabit port can use copper or fibre for connection.
[0086] FIG. 6 illustrates another exemplary computer system (600) in which
or with which the embodiments of the present disclosure may be implemented.
[0087] As shown in FIG. 6, the computer system (600) may include an
25 external storage device (610), a bus (620), a main memory (630), a read-only memory (640), a mass storage device (650), a communication port(s) (660), and a processor (670). A person skilled in the art will appreciate that the computer system (600) may include more than one processor and communication ports. The processor (670) may include various modules associated with embodiments of the
28

present disclosure. The communication port(s) (660) may be any of an RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. The communication ports(s) (660) may be chosen 5 depending on a network, such as a Local Area Network (LAN), Wide Area Network (WAN), or any network to which the computer system (600) connects.
[0088] In an embodiment, the main memory (630) may be Random Access
Memory (RAM), or any other dynamic storage device commonly known in the art. The read-only memory (640) may be any static storage device(s) e.g., but not
10 limited to, a Programmable Read Only Memory (PROM) chip for storing static information e.g., start-up or basic input/output system (BIOS) instructions for the processor (670). The mass storage device (650) may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced
15 Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces).
[0089] In an embodiment, the bus (620) may communicatively couple the
processor(s) (670) with the other memory, storage, and communication blocks. The 20 bus (620) may be, e.g. a Peripheral Component Interconnect PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), Universal Serial Bus (USB), or the like, for connecting expansion cards, drives, and other subsystems as well as other buses, such a front side bus (FSB), which connects the processor (670) to the computer system (600).
25 [0090] In another embodiment, operator, and administrative interfaces, e.g.,
a display, keyboard, and cursor control device may also be coupled to the bus (620) to support direct operator interaction with the computer system (600). Other operator and administrative interfaces can be provided through network connections connected through the communication port(s) (660). Components
29

described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system (600) limit the scope of the present disclosure.
[0091] It is to be appreciated by a person skilled in the art that while various
5 embodiments of the present disclosure have been elaborated for centrally managing and controlling a plurality of AMRs system. However, the teachings of the present disclosure are also applicable for other types of applications as well, and all such embodiments are well within the scope of the present disclosure. However, the system and method for sign language conversion is also equally implementable in 10 other industries as well, and all such embodiments are well within the scope of the present disclosure without any limitation.
[0092] Moreover, in interpreting the specification, all terms should be
interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as
15 referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refer to at least one of something selected from the group consisting of A, B, C….and N, the text should be
20 interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[0093] While considerable emphasis has been placed herein on the preferred
embodiments it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from 25 the principles of the disclosure. These and other changes in the preferred embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be implemented merely as illustrative of the disclosure and not as a limitation.
30

ADVANTAGES OF THE PRESENT DISCLOSURE
[0094] The present disclosure provides a system for efficiently executing a
system for centrally managing and controlling a plurality of AMRs.
[0095] The present disclosure provides a system that provides very high
5 data rates and very low latency which allows faster decision making of AMRs embedded with advanced capabilities.
[0096] The present disclosure provides a system that enables processing
power closer to the area of application resulting in lower latency.
[0097] The present disclosure provides a system that overcomes network
10 interference and blind spots by providing a much wider signal propagation, support for very high device density and secure connectivity over a licensed spectrum.
[0098] The present disclosure provides a system that offers ultra-low
latency and high data transfer speeds, enabling real-time communication between robotic systems and the central control unit.
15 [0099] The present disclosure provides a system that provides scalability
and flexibility in adapting to changing business needs by handling a massive number of connected devices simultaneously, so that warehouses can deploy a larger fleet of AMRs without experiencing network congestion.
[0100] The present disclosure provides a system that enables real-time
20 monitoring and control of AMRs to quickly respond to safety alerts, avoid collisions, and navigate complex environments with precision.
[0101] The present disclosure provides a system that operates at higher
speeds and optimizes their movements, reducing energy consumption and labor costs for an improved inventory accuracy and faster order fulfillment can minimize 25 stockouts and increase customer satisfaction.

We Claim:
1. A system (108) for centrally managing and controlling a plurality of Autonomous Mobile Robots (AMRs) the system (108) comprising:
a network module (210) configured to provide a private network
5 coverage for each of the plurality of AMRs;
a Fleet Management System (FMS) (212) deployed over an edge of a network,), configured to provide one or more real-time instructions to the plurality of AMRs; and
a computing module (218) installed within each of the plurality of
10 AMRs to enable seamless communication among the plurality of AMRs and
the FMS (212) over the private network based on the one or more real-time
instructions, wherein the one or more real-time instructions is provided to
manage and control operations of the plurality of AMRs.
15 2. The system (108) as claimed in claim 1, wherein to provide the private
network coverage, the network module (210) comprises a Distributed Antenna System (DAS) powered by an Outdoor Small Cell (ODSC) (116).
3. The system (108) as claimed in claim 1, wherein deployment of the FMS
20 (212) over the edge of the network provides Ultra Reliable Low Latency
Communication (URLLC).
4. The system (108) as claimed in claim 1, wherein the plurality of AMRs is
equipped with an artificial intelligence for navigating each of the plurality
25 of AMRs along dynamic routes and detecting obstacles in real-time.
5. The system (108) as claimed in claim 1, wherein the network module (210)
is one of a private network module or a public network module to provide a
wider signal propagation, support for high device density, and secure
30 connectivity over a licensed spectrum.

6. A method (500) for centrally managing and controlling a plurality of
Autonomous Mobile Robots (AMRs), the method (500) comprising:
establishing (502), by a network module (210), a private network
coverage for each of the plurality of AMRs;
5 providing (504), by a Fleet Management System (FMS) (212), one or
more real-time instructions to the plurality of AMRs; and
upgrading (506), by a computing module (218), the plurality of AMRs
to enable seamless communication among the plurality of AMRs and the
FMS (212) over the private network based on the one or more real-time
10 instructions, wherein the one or more real-time instructions is provided to
manage and control operations of the plurality of AMRs.
7. The method (500) as claimed in claim 6, further comprising achieving Ultra
Reliable Low Latency Communication (URLLC) between the FMS (212)
15 and the plurality of AMRs based on deployment of the FMS (212) over an
edge of the network.
8. The method (500) as claimed in claim 6, further comprising enabling
navigation for the plurality of AMRs using an artificial intelligence for
20 dynamic routing and obstacle detection in real-time.
9. A user equipment (UE) (104) configured to manage and control a plurality
of Autonomous Mobile Robots (AMRs), the UE (104) comprising:
a processor (202); and
25 a computer readable storage medium storing programming for
execution by the processor (202), the programming including instructions to:
establish a private network coverage through a network module (210) for each of the plurality of AMRs;

provide one or more real-time instructions to the plurality of AMRs through a Fleet Management System (FMS) (212) and via the UE (104); and
upgrade the plurality of AMRs through a computing module
5 (218) to enable seamless communication among the plurality of
AMRs and the FMS (212) over the private network based on the one or more real-time instructions, wherein the one or more real-time instructions is provided to manage and control operations of the plurality of AMRs. 10
10. The UE (104) as claimed in claim 9, wherein the programming including instructions to enable navigation for the plurality of AMRs using an artificial intelligence for dynamic routing and obstacle detection in real¬time.
15 Dated this 18 day of June 2024
~Digitally signed~
D. Jayaseelan Solomon
REG.NO:IN/PA-324
of De Penning & De Penning
Agent for the Applicants