FIELD OF THE PRESENT DISCLOSURE
[0001] The present disclosure generally relates to autonomous guided vehicles, such as a robot vehicle, implemented to move in a work area comprising a first matrix of first ground markers, and particularly to a system and method for automatically calibrating odometry parameters of such robot vehicle.

BACKGROUND
[0002] Autonomous guided vehicles (AGVs), also known as robot vehicles, are increasingly being employed for transporting goods and materials from one place to another in constrained environments, such as a factory or a warehouse. For example, robot vehicles are used in warehouse environments to assist with inventory management by transporting goods from one area of the warehouse to another. In a warehouse, the robot vehicle may travel from a loading area to a dropping area based on a control system and without intervention from users. In a manufacturing plant, the robot vehicles can transport items such as heavy vehicle components like engines, chassis, etc. along a route along a floor of the manufacturing plant to deliver the payload from one location to another or to allow various manufacturing operations to be performed thereon. Robot vehicles may offer the ability to carry payloads too heavy for a person to carry and without the supervision of a person, while also offering the flexibility to be reconfigured to follow a different route or carry different types of payloads.
[0003] Most systems involving such robot vehicles implement ground markers placed on a floor, usually in the form of a matrix, to enable the robot vehicles to follow a path defined using a combination of such ground markers. The robot vehicle determines its position with respect to the floor based on the ground marker in vicinity thereof. The very essence of the robot vehicles is that its movements are accurately predetermined, so as to accurately follow the predefined path. However, due to operational wear, mechanical degradation, electrical degradation, temperature variation, etc., the estimated value of position error accumulates over operation of the robot vehicles. This can cause the robot vehicle to deviate from the predefined path during its operation, or have a certain bias while following the predefined path. Therefore, the robot vehicle’s odometry needs to be calibrated regularly over its operational life for correcting these variations. For this purpose, the robot vehicle may need to be removed from the work area, which affects the system’s operation. It may be noted that since unimpeded system operation highly depends upon robot vehicle’s availability, downtime or maintenance is undesirable and can incur high costs
[0004] Therefore, in light of the foregoing discussion, there exists a need to overcome problems associated with conventional systems and methods for calibrating odometry parameters of a robot vehicle which is fast and automated, and such that the robot vehicle may be sent for calibration while minimally affecting system’s throughput.

SUMMARY
[0005] In an aspect, a system for automatically calibrating odometry parameters of a robot vehicle implemented to move in a work area comprising a first matrix of first ground markers during an operational cycle thereof is provided. The system comprises an odometry control arrangement provided in the robot vehicle. The odometry control arrangement is configured to control movement of the robot vehicle in the work area based on the first ground markers therein. The system also comprises a sensing arrangement configured to estimate a position of the robot vehicle with respect to one of the first ground markers, from the first matrix of first ground markers, in vicinity thereof when moved using the odometry control arrangement during the operational cycle thereof, and determine an odometry error in the movement of the robot vehicle in the work area based on the estimated position of the robot vehicle with respect to one of the first ground markers. The system also comprises a calibration zone located outside of the work area. The calibration zone comprises a second matrix of second ground markers, with a density of the second ground markers in the second matrix of second ground markers being greater than a density of the first ground markers in the first matrix of first ground markers. The system further comprises a processing unit. The processing unit is configured to: determine a suitable time for the robot vehicle to be moved out of the work area based, at least in part, on the operational cycle thereof in response to determination of the odometry error by the sensing arrangement; configure the robot vehicle to move to the calibration zone at the determined suitable time therefor; configure the robot vehicle to move, using the odometry control arrangement thereof, along a closed geometric loop starting from one of the second ground markers and ending at the same said one of the second ground markers, from the second matrix of second ground markers in the calibration zone; estimate, using the sensing arrangement, a position of the robot vehicle with respect to the said one of the second ground markers after completion of the movement along the said closed geometric loop; determine an offset based on the estimated position of the robot vehicle with respect to the said one of the second ground markers; calibrate the odometry control arrangement of the robot vehicle based on the determined offset; and configure the robot vehicle to move to the work area after calibration of the odometry control arrangement thereof.
[0006] In one or more embodiments, the sensing arrangement is provided in the robot vehicle. Herein, the sensing arrangement comprises one or more of: a set of wheel encoders associated with drive wheels of the robot vehicle, an odometer, an inertial measurement unit and a marker recognizer.
[0007] In one or more embodiments, the sensing arrangement is external to the robot vehicle. Herein, the sensing arrangement comprises one or more imaging device arranged to provide a view covering at least the work area and the calibration zone.
[0008] In one or more embodiments, the sensing arrangement is configured to determine one or more of: a cross track error, a number of missed first ground markers and an average of goal reaching tolerances, based on the estimated position of the robot vehicle with respect to one of the first ground markers during the operational cycle thereof, to determine the odometry error.
[0009] In one or more embodiments, the processing unit is configured to determine the suitable time based on workload of the robot vehicle in the work area.
[0010] In one or more embodiments, the processing unit is configured to determine the suitable time as time of completion of the operational cycle for the robot vehicle.
[0011] In one or more embodiments, a ratio of the density of the second ground markers in the second matrix of second ground markers in the calibration zone to the density of the first ground markers in the first matrix of first ground markers in the work area is in a range of 4:1 to 8:1.
[0012] In another aspect, a method for automatically calibrating odometry parameters of a robot vehicle implemented to move in a work area comprising a first matrix of first ground markers during an operational cycle thereof is provided. The method comprises estimating a position of the robot vehicle with respect to one of the first ground markers, from the first matrix of first ground markers, in vicinity thereof when moved using an odometry control arrangement thereof, during the operational cycle thereof. The method further comprises determining an odometry error in the movement of the robot vehicle in the work area based on the estimated position of the robot vehicle with respect to one of the first ground markers. The method further comprises determining a suitable time for the robot vehicle to be moved out of the work area based, at least in part, on the operational cycle thereof in response to determination of the odometry error. The method further comprises configuring the robot vehicle to move to a calibration zone, located outside of the work area, at the determined suitable time therefor, the calibration zone comprising a second matrix of second ground markers, with a density of the second ground markers in the second matrix of second ground markers being greater than a density of the first ground markers in the first matrix of first ground markers. The method further comprises configuring the robot vehicle to move, using the odometry control arrangement thereof, along a closed geometric loop starting from one of the second ground markers and ending at the same said one of the second ground markers, from the second matrix of second ground markers in the calibration zone. The method further comprises estimating a position of the robot vehicle with respect to the said one of the second ground markers after completion of the movement along the said closed geometric loop. The method further comprises determining an offset based on the estimated position of the robot vehicle with respect to the said one of the second ground markers. The method further comprises calibrating the odometry control arrangement of the robot vehicle based on the determined offset. The method further comprises configuring the robot vehicle to move to the work area after calibration of the odometry control arrangement thereof.
[0013] In one or more embodiments, the method further comprises determining one or more of: a cross track error, a number of missed first ground markers and an average of goal reaching tolerances, based on the estimated position of the robot vehicle with respect to one of the first ground markers during the operational cycle thereof, to determine the odometry error.
[0014] In one or more embodiments, the method further comprises determining the suitable time based on workload of the robot vehicle in the work area.
[0015] The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

BRIEF DESCRIPTION OF THE FIGURES
[0016] For a more complete understanding of example embodiments of the present disclosure, reference is now made to the following descriptions taken in connection with the accompanying drawings in which:
[0017] FIG. 1 illustrates a schematic of a system that may reside on and may be executed by a computer, which may be connected to a network, in accordance with one or more embodiments of the present disclosure;
[0018] FIG. 2 illustrates an exemplary computing system for positioning an autonomous vehicle at a site in a floor space, in accordance with one or more embodiments of the present disclosure;
[0019] FIG. 3 illustrates an exemplary implementation of the system for a work area in which a fleet of robot vehicles are operated, in accordance with one or more embodiments of the present disclosure;
[0020] FIG. 4 illustrates a diagrammatic representation of a calibration zone implemented with the system, in accordance with one or more embodiments of the present disclosure; and
[0021] FIG. 5 illustrates a flowchart listing steps involved in a method for automatically calibrating odometry parameters of a robot vehicle, in accordance with one or more embodiments of the present disclosure.

DETAILED DESCRIPTION
[0022] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure is not limited to these specific details.
[0023] Reference in this specification to “one embodiment” or “an embodiment” 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. The appearance of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Further, the terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items. Moreover, various features are described which may be exhibited by some embodiments and not by others. Similarly, various requirements are described which may be requirements for some embodiments but not for other embodiments.
[0024] Furthermore, in the following detailed description of the present disclosure, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be understood that the present disclosure may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the present disclosure.
[0025] Embodiments described herein may be discussed in the general context of computer-executable instructions residing on some form of computer-readable storage medium, such as program modules, executed by one or more computers or other devices. By way of example, and not limitation, computer-readable storage media may comprise non-transitory computer-readable storage media and communication media; non-transitory computer-readable media include all computer-readable media except for a transitory, propagating signal. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types. The functionality of the program modules may be combined or distributed as desired in various embodiments.
[0026] Some portions of the detailed description that follows are presented and discussed in terms of a process or method. Although steps and sequencing thereof are disclosed in figures herein describing the operations of this method, such steps and sequencing are exemplary. Embodiments are well suited to performing various other steps or variations of the steps recited in the flowchart of the figure herein, and in a sequence other than that depicted and described herein. Some portions of the detailed descriptions that follow are presented in terms of procedures, logic blocks, processing, and other symbolic representations of operations on data bits within a computer memory. These descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. In the present application, a procedure, logic block, process, or the like, is conceived to be a self-consistent sequence of steps or instructions leading to a desired result. The steps are those utilizing physical manipulations of physical quantities. Usually, although not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as transactions, bits, values, elements, symbols, characters, samples, pixels, or the like.
[0027] In some implementations, any suitable computer usable or computer readable medium (or media) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer-usable, or computer-readable, storage medium (including a storage device associated with a computing device) may be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fibre, a portable compact disc read-only memory (CD-ROM), an optical storage device, a digital versatile disk (DVD), a static random access memory (SRAM), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, a media such as those supporting the internet or an intranet, or a magnetic storage device. Note that the computer-usable or computer-readable medium could even be a suitable medium upon which the program is stored, scanned, compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. In the context of the present disclosure, a computer-usable or computer-readable, storage medium may be any tangible medium that can contain or store a program for use by or in connection with the instruction execution system, apparatus, or device.
[0028] In some implementations, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. In some implementations, such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. In some implementations, the computer readable program code may be transmitted using any appropriate medium, including but not limited to the internet, wireline, optical fibre cable, RF, etc. In some implementations, a computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
[0029] In some implementations, computer program code for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object-oriented programming language such as Java®, Smalltalk, C++ or the like. Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates. However, the computer program code for carrying out operations of the present disclosure may also be written in conventional procedural programming languages, such as the "C" programming language, PASCAL, or similar programming languages, as well as in scripting languages such as JavaScript, PERL, or Python. In present implementations, the used language for training may be one of Python, TensorflowTM, Bazel, C, C++. Further, decoder in user device (as will be discussed) may use C, C++ or any processor specific ISA. Furthermore, assembly code inside C/C++ may be utilized for specific operation. Also, ASR (automatic speech recognition) and G2P decoder along with entire user system can be run in embedded Linux (any distribution), Android, iOS, Windows, or the like, without any limitations. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user’s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user’s computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the internet using an Internet Service Provider). In some implementations, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs) or other hardware accelerators, micro-controller units (MCUs), or programmable logic arrays (PLAs) may execute the computer readable program instructions/code by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.
[0030] In some implementations, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus (systems), methods and computer program products according to various implementations of the present disclosure. Each block in the flowchart and/or block diagrams, and combinations of blocks in the flowchart and/or block diagrams, may represent a module, segment, or portion of code, which comprises one or more executable computer program instructions for implementing the specified logical function(s)/act(s). These computer program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program instructions, which may execute via the processor of the computer or other programmable data processing apparatus, create the ability to implement one or more of the functions/acts specified in the flowchart and/or block diagram block or blocks or combinations thereof. It should be noted that, in some implementations, the functions noted in the block(s) may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved.
[0031] In some implementations, these computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks or combinations thereof.
[0032] In some implementations, the computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed (not necessarily in a particular order) on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts (not necessarily in a particular order) specified in the flowchart and/or block diagram block or blocks or combinations thereof.
[0033] Referring now to the example implementation of FIG. 1, there is shown a system 100 that may reside on and may be executed by a computer (e.g., computer 12), which may be connected to a network (e.g., network 14) (e.g., the internet or a local area network). Examples of computer 12 may include, but are not limited to, a personal computer(s), a laptop computer(s), mobile computing device(s), a server computer, a series of server computers, a mainframe computer(s), or a computing cloud(s). In some implementations, each of the aforementioned may be generally described as a computing device. In certain implementations, a computing device may be a physical or virtual device. In many implementations, a computing device may be any device capable of performing operations, such as a dedicated processor, a portion of a processor, a virtual processor, a portion of a virtual processor, a portion of a virtual device, or a virtual device. In some implementations, a processor may be a physical processor or a virtual processor. In some implementations, a virtual processor may correspond to one or more parts of one or more physical processors. In some implementations, the instructions/logic may be distributed and executed across one or more processors, virtual or physical, to execute the instructions/logic. Computer 12 may execute an operating system, for example, but not limited to, Microsoft® Windows®; Mac® OS X®; Red Hat® Linux®, or a custom operating system. (Microsoft and Windows are registered trademarks of Microsoft Corporation in the United States, other countries or both; Mac and OS X are registered trademarks of Apple Inc. in the United States, other countries or both; Red Hat is a registered trademark of Red Hat Corporation in the United States, other countries or both; and Linux is a registered trademark of Linus Torvalds in the United States, other countries or both).
[0034] In some implementations, the instruction sets and subroutines of system 100, which may be stored on storage device, such as storage device 16, coupled to computer 12, may be executed by one or more processors (not shown) and one or more memory architectures included within computer 12. In some implementations, storage device 16 may include but is not limited to: a hard disk drive; a flash drive, a tape drive; an optical drive; a RAID array (or other array); a random-access memory (RAM); and a read-only memory (ROM).
[0035] In some implementations, network 14 may be connected to one or more secondary networks (e.g., network 18), examples of which may include but are not limited to: a local area network; a wide area network; or an intranet, for example.
[0036] In some implementations, computer 12 may include a data store, such as a database (e.g., relational database, object-oriented database, triplestore database, etc.) and may be located within any suitable memory location, such as storage device 16 coupled to computer 12. In some implementations, data, metadata, information, etc. described throughout the present disclosure may be stored in the data store. In some implementations, computer 12 may utilize any known database management system such as, but not limited to, DB2, in order to provide multi-user access to one or more databases, such as the above noted relational database. In some implementations, the data store may also be a custom database, such as, for example, a flat file database or an XML database. In some implementations, any other form(s) of a data storage structure and/or organization may also be used. In some implementations, system 100 may be a component of the data store, a standalone application that interfaces with the above noted data store and/or an applet / application that is accessed via client applications 22, 24, 26, 28. In some implementations, the above noted data store may be, in whole or in part, distributed in a cloud computing topology. In this way, computer 12 and storage device 16 may refer to multiple devices, which may also be distributed throughout the network.
[0037] In some implementations, computer 12 may execute application 20 for automatically calibrating odometry parameters of a robot vehicle. In some implementations, system 100 and/or application 20 may be accessed via one or more of client applications 22, 24, 26, 28. In some implementations, system 100 may be a standalone application, or may be an applet / application / script / extension that may interact with and/or be executed within application 20, a component of application 20, and/or one or more of client applications 22, 24, 26, 28. In some implementations, application 20 may be a standalone application, or may be an applet / application / script / extension that may interact with and/or be executed within system 100, a component of system 100, and/or one or more of client applications 22, 24, 26, 28. In some implementations, one or more of client applications 22, 24, 26, 28 may be a standalone application, or may be an applet / application / script / extension that may interact with and/or be executed within and/or be a component of system 100 and/or application 20. Examples of client applications 22, 24, 26, 28 may include, but are not limited to, a standard and/or mobile web browser, an email application (e.g., an email client application), a textual and/or a graphical user interface, a customized web browser, a plugin, an Application Programming Interface (API), or a custom application. The instruction sets and subroutines of client applications 22, 24, 26, 28, which may be stored on storage devices 30, 32, 34, 36, coupled to user devices 38, 40, 42, 44, may be executed by one or more processors and one or more memory architectures incorporated into user devices 38, 40, 42, 44.
[0038] In some implementations, one or more of storage devices 30, 32, 34, 36, may include but are not limited to: hard disk drives; flash drives, tape drives; optical drives; RAID arrays; random access memories (RAM); and read-only memories (ROM). Examples of user devices 38, 40, 42, 44 (and/or computer 12) may include, but are not limited to, a personal computer (e.g., user device 38), a laptop computer (e.g., user device 40), a smart/data-enabled, cellular phone (e.g., user device 42), a notebook computer (e.g., user device 44), a tablet (not shown), a server (not shown), a television (not shown), a smart television (not shown), a media (e.g., video, photo, etc.) capturing device (not shown), and a dedicated network device (not shown). User devices 38, 40, 42, 44 may each execute an operating system, examples of which may include but are not limited to, Android®, Apple® iOS®, Mac® OS X®; Red Hat® Linux®, or a custom operating system.
[0039] In some implementations, one or more of client applications 22, 24, 26, 28 may be configured to effectuate some or all of the functionality of system 100 (and vice versa). Accordingly, in some implementations, system 100 may be a purely server-side application, a purely client-side application, or a hybrid server-side / client-side application that is cooperatively executed by one or more of client applications 22, 24, 26, 28 and/or system 100.
[0040] In some implementations, one or more of client applications 22, 24, 26, 28 may be configured to effectuate some or all of the functionality of application 20 (and vice versa). Accordingly, in some implementations, application 20 may be a purely server-side application, a purely client-side application, or a hybrid server-side / client-side application that is cooperatively executed by one or more of client applications 22, 24, 26, 28 and/or application 20. As one or more of client applications 22, 24, 26, 28, system 100, and application 20, taken singly or in any combination, may effectuate some or all of the same functionality, any description of effectuating such functionality via one or more of client applications 22, 24, 26, 28, system 100, application 20, or combination thereof, and any described interaction(s) between one or more of client applications 22, 24, 26, 28, system 100, application 20, or combination thereof to effectuate such functionality, should be taken as an example only and not to limit the scope of the disclosure.
[0041] In some implementations, one or more of users 46, 48, 50, 52 may access computer 12 and system 100 (e.g., using one or more of user devices 38, 40, 42, 44) directly through network 14 or through secondary network 18. Further, computer 12 may be connected to network 14 through secondary network 18, as illustrated with phantom link line 54. System 100 may include one or more user interfaces, such as browsers and textual or graphical user interfaces, through which users 46, 48, 50, 52 may access system 100.
[0042] In some implementations, the various user devices may be directly or indirectly coupled to network 14 (or network 18). For example, user device 38 is shown directly coupled to network 14 via a hardwired network connection. Further, user device 44 is shown directly coupled to network 18 via a hardwired network connection. User device 40 is shown wirelessly coupled to network 14 via wireless communication channel 56 established between user device 40 and wireless access point (i.e., WAP) 58, which is shown directly coupled to network 14. WAP 58 may be, for example, an IEEE 802.11a, 802.11b, 802.11g, Wi-Fi®, RFID, and/or BluetoothTM (including BluetoothTM Low Energy) device that is capable of establishing wireless communication channel 56 between user device 40 and WAP 58. User device 42 is shown wirelessly coupled to network 14 via wireless communication channel 60 established between user device 42 and cellular network / bridge 62, which is shown directly coupled to network 14.
[0043] In some implementations, some or all of the IEEE 802.11x specifications may use Ethernet protocol and carrier sense multiple access with collision avoidance (i.e., CSMA/CA) for path sharing. The various 802.11x specifications may use phase-shift keying (i.e., PSK) modulation or complementary code keying (i.e., CCK) modulation, for example, BluetoothTM (including BluetoothTM Low Energy) is a telecommunications industry specification that allows, e.g., mobile phones, computers, smart phones, and other electronic devices to be interconnected using a short-range wireless connection. Other forms of interconnection (e.g., Near Field Communication (NFC)) may also be used.
[0044] For the purposes of the present disclosure, the system 100 may include a fleet management system. Herein, FIG. 2 is a block diagram of an example of the fleet management system 200 capable of implementing embodiments according to the present disclosure. The fleet management system 200 is implemented for issuing commands for managing and controlling operations of a fleet of robot vehicles (as will be described later in more detail), which, in turn, may be utilized in a warehouse environment, a manufacturing plant and the like. In one embodiment, the application 20 for automatically calibrating odometry parameters of a robot vehicle as described above may be executed as a part of the fleet management system 200 as described herein. Thereby, for example in case of a warehouse, the system 100 may be broader system such as the warehouse management system (WMS) as known in the art, in which the fleet management system 200 may be executed for managing and controlling operations of a fleet of robot vehicles. Hereinafter, the terms “system 100” and “fleet management system 200” have been broadly interchangeably used to represent means for managing and controlling operations of a fleet of robot vehicles in a work environment, without any limitations.
[0045] In the example of FIG. 2, the fleet management system 200 includes a processing unit 205 for running software applications (such as, the application 20 of FIG. 1) and optionally an operating system. Memory 210 stores applications and data for use by the processing unit 205. Storage 215 provides non-volatile storage for applications and data and may include fixed disk drives, removable disk drives, flash memory devices, and CD-ROM, DVD-ROM or other optical storage devices. An optional user input device 220 includes devices that communicate user inputs from one or more users to the fleet management system 200 and may include keyboards, mice, joysticks, touch screens, etc. A communication or network interface 225 is provided which allows the fleet management system 200 to communicate with other computer systems via an electronic communications network, including wired and/or wireless communication and including an Intranet or the Internet. In one embodiment, the fleet management system 200 receives instructions and user inputs from a remote computer through communication interface 225. Communication interface 225 can comprise a transmitter and receiver for communicating with remote devices. An optional display device 250 may be provided which can be any device capable of displaying visual information in response to a signal from the fleet management system 200. The components of the fleet management system 200, including the processing unit 205, the memory 210, the data storage 215, the user input devices 220, the communication interface 225, and the display device 250, may be coupled via one or more data buses 260.
[0046] In the embodiment of FIG. 2, a graphics system 230 may be coupled with the data bus 260 and the components of the fleet management system 200. The graphics system 230 may include a physical graphics processing unit (GPU) 235 and graphics memory. The GPU 235 generates pixel data for output images from rendering commands. The physical GPU 235 can be configured as multiple virtual GPUs that may be used in parallel (concurrently) by a number of applications or processes executing in parallel. For example, mass scaling processes for rigid bodies or a variety of constraint solving processes may be run in parallel on the multiple virtual GPUs. Graphics memory may include a display memory 240 (e.g., a framebuffer) used for storing pixel data for each pixel of an output image. In another embodiment, the display memory 240 and/or additional memory 245 may be part of the memory 210 and may be shared with the processing unit 205. Alternatively, the display memory 240 and/or additional memory 245 can be one or more separate memories provided for the exclusive use of the graphics system 230. In another embodiment, graphics system 230 includes one or more additional physical GPUs 255, similar to the GPU 235. Each additional GPU 255 may be adapted to operate in parallel with the GPU 235. Each additional GPU 255 generates pixel data for output images from rendering commands. Each additional physical GPU 255 can be configured as multiple virtual GPUs that may be used in parallel (concurrently) by a number of applications or processes executing in parallel, e.g., processes that solve constraints. Each additional GPU 255 can operate in conjunction with the GPU 235, for example, to simultaneously generate pixel data for different portions of an output image, or to simultaneously generate pixel data for different output images. Each additional GPU 255 can be located on the same circuit board as the GPU 235, sharing a connection with the GPU 235 to the data bus 260, or each additional GPU 255 can be located on another circuit board separately coupled with the data bus 260. Each additional GPU 255 can also be integrated into the same module or chip package as the GPU 235. Each additional GPU 255 can have additional memory, similar to the display memory 240 and additional memory 245, or can share the memories 240 and 245 with the GPU 235. It is to be understood that the circuits and/or functionality of GPU as described herein could also be implemented in other types of processors, such as general-purpose or other special-purpose coprocessors, or within a CPU.
[0047] Referring to FIG. 3, illustrated is an implementation of the system 100 for a work area 300 in which a fleet of robot vehicles are operated, in accordance with one or more embodiments of the present disclosure. In the illustration of FIG. 3, one robot vehicle has been shown and represented by numeral 302, although it may be appreciated that there may be multiple robot vehicles 302, as part of the fleet of robot vehicles, operating in the work area 300. Further, it may be appreciated that the work area 300 may be part of a larger floor space, e.g., in a warehouse environment (not shown) or the like. Herein, the work area 300 is shown to include the robot vehicle 302. The robot vehicle 302 may be utilized for various operations in the work area 300, like transferring of goods, such as cartons, in the work area 300, which is typical, e.g., for a warehouse environment. The robot vehicle 302 may be configured to perform at least one operation in a cycle, which may involve the robot vehicle 302 to travel from one position in the work area 300 to another, and this may be defined as an “operational cycle” of the robot vehicle 302.
[0048] In the present embodiments, as shown in FIG. 3, the work area 300 includes a first matrix of first ground markers 306. In other words, the first ground markers 306 are arranged in a manner to define the first matrix of first ground markers 306. Herein, the term "ground marker" is meant to include any number and all types of marks that serve the distinguishing function, either in isolation or combination. Such ground markers may include, but are not limited to, geometric shapes or characters that superficially and/or structurally alter the appearance of the work area 300, that may be easily recognized by compatible sensing means, which may be, in present examples, marker recognizers provided in the robot vehicles 302 as discussed later. In the present illustration, the first ground markers 306 are shown as regular sized squares; however, other shapes may be contemplated without any limitations. Further, as may be seen, the first matrix of first ground markers 306 virtually divide the work area 300 into a plurality of grids 308, with each such grid 308 being generally the same size (area) as the robot vehicle 302.
[0049] In the present examples, the robot vehicle 302 may include a marker recognizer 310 (generally represented in FIG. 3). Such marker recognizer 310 may be provided in the robot vehicle 302. The marker recognizer 310 may be configured to recognize the ground markers, including the first ground markers 306. In the present example, the marker recognizer 310 may be in the form of, but not limited to, a camera provided in a body of the robot vehicle 302 and pointed to a floor of the work area 300 and/or a scanner configured to distinguish colours when the ground markers, including the first ground markers 306, may be of a substantially different from the floor of the work area 300, or the like. Such marker recognizer 310 may be contemplated by a person skilled in the art and thus has not been described in any more detail herein for the brevity of the present disclosure.
[0050] Herein, the system 100 may define a path, i.e., a predefined path (such as, an exemplary predefined path 312 as shown in FIG. 3) to be followed by the robot vehicle 302 in the work area 300. The predefined path 312 may be defined by virtually linking multiple first ground markers 306 (as a virtual track), in various possible combinations, for the robot vehicle 302 to travel thereon. Typically, the predefined path 312 as provided by the system 100 is a navigation path including a set of straight lines passing through centres of the first ground markers 306, in the first matrix of first ground markers 306 in the work area 300. Such arrangement using the ground markers may be contemplated by a person skilled in the art and thus has not been described further for the brevity of the present disclosure.
[0051] The system 100 includes an odometry control arrangement 320 (as schematically shown in FIG. 3). The odometry control arrangement 320 is provided in the robot vehicle 302. Herein, “odometry” refers to the use of data from motion sensors to estimate change in position over time. In the present robot vehicle 302, the odometry control arrangement 320 is configured to estimate a position of the robot vehicle 302 relative to a starting location. By estimating such position, as may be contemplated, the odometry control arrangement 320 may be implemented to control movements of the robot vehicle 302 in the work area 300, such that the robot vehicle 302 may be able to follow the predefined path 312 (as discussed earlier). In the present embodiments, the odometry control arrangement 320 is configured to control movement of the robot vehicle 302 in the work area 300 based on the first ground markers 306 therein. Specifically, the odometry control arrangement 320 in the robot vehicle 302 may enable the robot vehicle 302 to move (change its position) in the work area 300 from a current first ground marker 306 to a next first ground marker 306, and thereby follow the predefined path 312 as provided by the system 100.
[0052] It may be appreciated that the odometry control arrangement 320 may be in the form of a controller which may be any processing device, system or part thereof that controls at least one operation of the device. Such controller may be implemented in hardware, firmware or software, or some combination of at least two of the same. It should be noted that the functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. Such controller may be a multi-core processor, a single core processor, or a combination of one or more multi-core processors and one or more single core processors. For example, the one or more processors may be embodied as one or more of various processing devices, such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuitry with or without an accompanying DSP, or various other processing devices including integrated circuits such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a microcontroller unit (MCU), a hardware accelerator, a special-purpose computer chip, or the like. Further, the memory may include one or more non-transitory computer-readable storage media that can be read or accessed by other components in the device. The memory may be any computer-readable storage media, including volatile and/or non-volatile storage components, such as optical, magnetic, organic or other memory or disc storage, which can be integrated in whole or in part with the device. In some examples, the memory may be implemented using a single physical device (e.g., optical, magnetic, organic or other memory or disc storage unit), while in other embodiments, the memory may be implemented using two or more physical devices without any limitations.
[0053] The system 100 also includes a sensing arrangement 330. The sensing arrangement 330 is configured to estimate a position of the robot vehicle 302 with respect to one of the first ground markers 306, from the first matrix of first ground markers 306, in vicinity thereof when the robot vehicle 302 is moved using the odometry control arrangement 320 during the operational cycle thereof. In other words, the sensing arrangement 330 may determine a relative position of the robot vehicle 302 with respect to the first ground marker 306 in vicinity thereof. Herein, by the term “the first ground marker 306 in vicinity thereof” means the first ground marker 306 from which the robot vehicle 302 may have started to be moved to the next first ground marker 306 as per the predefined path 312, or the next first ground marker 306 to which the robot vehicle 302 is supposed to reach as per the predefined path 312.
[0054] In an embodiment, the sensing arrangement 330 is provided in the robot vehicle 302. That is, the sensing arrangement 330 may be designed to monitor movement of the robot vehicle 302 from within to estimate the position of the robot vehicle 302 relative to its starting location in the work area 300. For this purpose, the sensing arrangement 330 includes one or more of: a set of wheel encoders associated with drive wheels of the robot vehicle 302, an odometer, an inertial measurement unit and a marker recognizer (such as, the marker recognizer 310). That is, in one example, for wheel-driven robot vehicle 302, the wheel encoders (not shown) may be associated with one or more of its drive wheels, and such wheel encoders may determine the distance travelled by the robot vehicle 302 and thereby the estimate the position of the robot vehicle 302 relative to its starting location in the work area 300. In another example, the odometer (not shown) associated with the robot vehicle 302 (or specifically, the drive wheels of the robot vehicle 302) may perform the same function to estimate the position of the robot vehicle 302 relative to its starting location in the work area 300. In still other example, the inertial measurement unit (IMU) (not shown) associated with the robot vehicle 302 may perform the same function (as may be contemplated by a person skilled in the art) to estimate the position of the robot vehicle 302 relative to its starting location in the work area 300. In still other examples, the marker recognizer 310 that may be provided in the robot vehicle 302 may recognize the first ground markers 306, and by keeping count of the number of such recognized first ground markers 306 and known change in directions as per the predefined path 312, the sensing arrangement 330 may use the recognized first ground markers 306 to estimate the position of the robot vehicle 302 relative to its starting location in the work area 300.
[0055] In another embodiment, the sensing arrangement 330 is external to the robot vehicle 302. That is, the sensing arrangement 330 may not be disposed in the robot vehicle 302 itself, but may be located outside the robot vehicle 302. In such case, the sensing arrangement 330 may monitor the movement of the robot vehicle 302 to estimate the position of the robot vehicle 302 relative to its starting location in the work area 300. For this purpose, the sensing arrangement 330 includes one or more imaging device (not shown) arranged to provide a view covering at least the work area 300 to capture image frames thereof while the robot vehicle 302 may be performing operations therein. In an example, the imaging device may include a camera. In other examples, the imaging device may include infrared image capturing device, LiDAR, RADAR or the like without any limitations. By using image analysis on the captured image frames from the imaging device, the sensing arrangement 330 may estimate a position of the robot vehicle 302 with respect to one of the first ground markers 306, from the first matrix of first ground markers 306, in vicinity thereof, as would be understood by a person skilled in the art.
[0056] In some embodiments, the sensing arrangement 330 may be disposed both in the robot vehicle 302 as well external to the robot vehicle 302. It may be understood that in case the marker recognizer 310 (as part of the sensing arrangement 330 internal to the robot vehicle 302) may be damaged which may be causing an odometry error (as discussed in the subsequent paragraphs), then the external sensing arrangement 330 may be used to estimate the position of the robot vehicle 302 with respect to one of the first ground markers 306, from the first matrix of first ground markers 306, in vicinity thereof when the robot vehicle 302 is moved using the odometry control arrangement 320 during the operational cycle thereof.
[0057] The sensing arrangement 330 is further configured to determine an odometry error in the movement of the robot vehicle 302 in the work area 300 based on the estimated position of the robot vehicle 302 with respect to one of the first ground markers 306. Herein, the term “odometry error” represents a navigation error in the robot vehicle 302 in the work area 300. As discussed, the predefined path 312 as provided by the system 100 is a navigation path including a set of straight lines passing through centres of the first ground markers 306, in the first matrix of first ground markers 306 in the work area 300. Such navigation error may occur when the robot vehicle 302 may deviate from such straight lines (e.g., missing the centres of the first ground markers 306) while supposedly following the predefined path 312 during the operational cycle thereof. In an example implementation, the sensing arrangement 330 may utilize the processing unit 205 of the system 100 for performing the computation and calculations (as described in the proceeding paragraphs) required for confirming the odometry error in the movement of the robot vehicle 302 as per embodiments of the present disclosure.
[0058] According to embodiments of the present disclosure, the sensing arrangement 330 is configured to determine one or more of: a cross track error, a number of missed first ground markers and an average of goal reaching tolerances, based on the estimated position of the robot vehicle 302 with respect to one of the first ground markers 306 during the operational cycle thereof, to determine the odometry error. In an example, the odometry error in the movement of the robot vehicle 302 may be determined based on lateral error (cross track error) which is the distance between the geometric centre of the marker recognizer 310 on the robot vehicle 302 and the closest point on the predefined path 312. Lateral error is the principal measure of how close the position of the robot vehicle 302 is to the desired position along the predefined path 312. In an example, the odometry error may be determined based on number of emergency stop incidents of the robot vehicle 302 during the operational cycle. Such emergency stop incidents of the robot vehicle 302 may occur when the robot vehicle 302 would stop or would have to be stopped (either manually or automatically by the system 100) due to improper functioning of the odometry control arrangement 320 therein. In an example, the odometry error may be determined based on average goal reaching error of the robot vehicle 302. Herein, the average goal reaching error may include longitudinal error which is defined as a difference between the centre of the first ground marker 306 and the centre of the marker recognizer 310 along a direction of movement of the robot vehicle 302, and an orientation error which is defined as the angular difference between the heading of the robot vehicle 302 (in the direction of movement) and the first ground marker 306. In an example, the odometry error may be determined based on number of missed first ground markers by the robot vehicle 302 during its operational cycle while supposedly following the predefined path 312. As during conventional operation, the first ground marker 306 is to be detected at a fixed/variable set of distances, and if the first ground marker 306 is not detected (e.g., by the marker recogniser 310) at the said fixed/variable distance (or the ground marker count threshold) during the operational cycle in the work area 300, the incident is counted as a missed first ground marker.
[0059] It may be appreciated that all these determined errors may generally be determined based on the estimated position of the robot vehicle 302 with respect to one of the first ground markers 306. These different errors are recorded and quantified by the sensing arrangement 330 to determine an average/rolling values of such errors in isolation or combination during the operational cycle of the robot vehicle 302, and if such average exceeds a predetermined threshold, the sensing arrangement 330 may confirm the odometry error in the movement of the robot vehicle 302 in the work area 300.
[0060] As discussed, most systems involving the robot vehicles (such as the robot vehicle 302) requires that the movements of the robot vehicle are accurate in the work area (such as the work area 300) for its proper operation. That is, the robot vehicle may need to accurately follow the predefined path using the ground markers. However, due to operational wear, mechanical degradation, electrical degradation, temperature variation, etc., the robot vehicle may accumulate position error over its various operation cycles. This can cause the robot vehicle to deviate from the predefined path during its operation or have a certain bias while following the predefined path. Therefore, the robot vehicle’s odometry needs to be recalibrated over its operational life for correcting these variations.
[0061] In embodiments of the present disclosure, as illustrated in FIG. 3, the system 100 includes a calibration zone 340 located outside of the work area 300. In an example, the calibration zone 340 may be located adjacent to the work area 300, as shown in FIG. 3. In other examples, the work area 300 may have an “empty” section (i.e., any section that does not include the first ground markers 306 placed therein), e.g., in a middle or some other region therein, and the calibration zone 340 may be located in such empty section relative to the work area 300. In still other examples, the calibration zone 340 may be located remote to the work area 300, within the floor space of the work environment, without any limitations. As shown, the calibration zone 340 may generally be much smaller in area as compared to the work area 300. Typically, the calibration zone 340 may have a square or a rectangular shape; however, other shapes may be contemplated. FIG. 4 illustrates a diagrammatic representation of the calibration zone 340 implemented with the system 100, in accordance with one or more embodiments of the present disclosure. In the illustration of FIG. 4, one of the robot vehicles 302 has been shown to be operating in the calibration zone 340.
[0062] As illustrated in FIGS. 3 and 4, in combination, the calibration zone 340 includes a second matrix of second ground markers 342. As illustrated, the second ground markers 342 may generally be similar in configuration to the first ground markers 306 as described earlier, i.e., the second ground markers 342 may generally have the same shape, size and design as the first ground markers 306. However, in some examples, the second ground markers 342 may be smaller in size or may have different shape without departing from the scope and the spirit of the present disclosure. Further, as may be seen, the second matrix of second ground markers 342 virtually divides a portion of the calibration zone 340 into a plurality of grids 344. Herein, the second matrix of second ground markers 342 may cover the said portion of the calibration zone 340, and further a set of second ground markers 342 may be located outside of the said portion of the calibration zone 340. Further, each such grid 344 may be generally be smaller than the size (area) of the robot vehicle 302 without any limitations. In another example, the second matrix of second ground markers 342 may virtually divide the entire calibration zone 340 into the plurality of grids 344 without any limitations.
[0063] In the present embodiments, a density of the second ground markers 342 in the second matrix of second ground markers 342 in the calibration zone 340 is greater than a density of the first ground markers 306 in the first matrix of first ground markers 306 in the work area 300. That is, the second ground markers 342 are more densely packed in the second matrix of second ground markers 342 in the calibration zone 340 as compared to the first ground markers 306 in the first matrix of first ground markers 306 in the work area 300. In the present examples, the density of the second ground markers 342 in the second matrix of second ground markers 342 in the calibration zone 340 is based on at least one of: a sensitivity of the sensing arrangement 330, a sensitivity of the marker recognizer 310, and a geometric area of the second ground markers 342. It may be appreciated that when the sensing arrangement 330 is external to the robot vehicle 302, the one or more imaging device used thereby may be arranged to also provide a view covering the calibration zone 340 in addition to the work area 300, in order to capture image frames thereof while the robot vehicle 302 may be performing calibration operations therein (as discussed later). In an example, the imaging device may include a camera. In other examples, the imaging device may include infrared image capturing device, LiDAR, RADAR or the like without any limitations. Herein, the sensitivity of the marker recognizer 310 may be dependent on a field-of-view (FoV) of the marker recognizer 310, including horizontal FoV as well as vertical horizontal FoV therefor. Herein, larger the sensitivity of the marker recognizer 310, higher the density of the second ground markers 342 in the second matrix of second ground markers 342 in the calibration zone 340 could be used. Further, the geometric area of the second ground markers 342 may be fixed based on the sensitivity of the marker recognizer 310, i.e., smaller the geometric area of the second ground markers 342 that may be recognized by the marker recognizer 310, higher the density of the second ground markers 342 in the second matrix of second ground markers 342 in the calibration zone 340 could be used.
[0064] In an embodiment, a ratio of the density of the second ground markers 342 in the second matrix of second ground markers 342 in the calibration zone 340 to the density of the first ground markers 306 in the first matrix of first ground markers 306 in the work area 300 is in a range of 4:1 to 8:1. In a preferred embodiment, the ratio of the density of the second ground markers 342 in the second matrix of second ground markers 342 in the calibration zone 340 to the density of the first ground markers 306 in the first matrix of first ground markers 306 in the work area 300 is 6:1. It may be appreciated that for the embodiments of the present disclosure, any reference to the “density” of ground markers means “density of placement” of the corresponding ground markers in the respective matrices thereof.
[0065] As discussed, the robot vehicle’s odometry needs to be recalibrated over its operational life for correcting odometry errors accumulated over time. If the sensing arrangement 330 determines the odometry error in the movement of the robot vehicle 302 in the work area 300, then it may be concluded that the odometry control arrangement 320 provided in the robot vehicle 302 may need to be re-calibrated. In an example, the sensing arrangement 330 may first check if the determined odometry error is greater than a predetermined threshold, and only then may confirm that the odometry control arrangement 320 provided in the robot vehicle 302 may need to be re-calibrated. For the purpose of the present disclosure, the robot vehicle 302 needs to be sent to the calibration zone 340 as a part of performing a recalibration routine, for calibration of the odometry control arrangement 320 therein. For this purpose, the robot vehicle 302 may need to be removed from the work area 300, which affects the operation of the system 100. It may be noted that since unimpeded system operation highly depends upon availability of the robot vehicle 302 to complete the operational cycle, downtime or maintenance, e.g., due to removal of the robot vehicle 302 from the work area 300, is undesirable and can incur high costs in the system 100, and thus needs to be minimized for efficient operation of the present system 100. Therefore, the present system 100 may also determine when the robot vehicle 302 may need to be moved to the calibration zone 340 for calibration of the odometry control arrangement 320 therein.
[0066] For this purpose, the processing unit 205 is configured to determine a suitable time for the robot vehicle 302 to be moved out of the work 300 area based, at least in part, on the operational cycle thereof in response to determination of the odometry error by the sensing arrangement 330. That is, the processing unit 205 may determine the time when the robot vehicle 302 may be sent to the calibration zone 340 for calibration of the odometry control arrangement 320 therein such that to minimally affect the overall operation of the system 100. In an embodiment, the processing unit 205 is configured to determine the suitable time based on workload of the robot vehicle 302 in the work area 300. Particularly, if the robot vehicle 302 may be handling a critical task of the overall operation, which if not completed may otherwise affect operations of various other components in the system 100, or may be required to complete a current task, and the determined odometry error may still be within the said predetermined threshold and thereby not significantly affect the current task), then it may delay a start of the recalibration routine. In another embodiment, the processing unit 205 is configured to determine the suitable time as time of completion of the operational cycle for the robot vehicle 302. That is, the system 100 may determine when the current operational cycle of the robot vehicle 302 may be completed, including all tasks involved therein. And when all such tasks may be expected to be completed, the system 100 may define that particular time as the suitable time for the robot vehicle 302 to be moved out of the work area 300, such that the overall operation of the system 100 is not affected at all.
[0067] The processing unit 205 is further configured to configure the robot vehicle 302 to move to the calibration zone 340 at the determined suitable time therefor. That is, the system 100 sends a command to the robot vehicle 302 to move to the calibration zone 340 at the determined suitable time. With the robot vehicle 302 being autonomous, it may move to the calibration zone 340 without any human intervention, using the odometry control arrangement 320 provided therein. In case, the determined odometry error for the odometry control arrangement 320 may be significantly high such that the robot vehicle 302 may not be in a condition to reach the calibration zone 340 autonomously, then the system 100 may generate an alarm for the like as an indication for a human operator to support and move the robot vehicle 302 to the calibration zone 340, for performing the required recalibration routine.
[0068] The processing unit 205 is further configured to configure the robot vehicle 302 to move, using the odometry control arrangement 320 thereof, along a closed geometric loop (represented in FIG. 4 with the numeral 410) starting from one of the second ground markers 342 and ending at the same said one of the second ground markers 342, from the second matrix of second ground markers 342 in the calibration zone 340. That is, when the robot vehicle 302 may reach the calibration zone 340, the system 100 instructs the robot vehicle 302 to start from one of the second ground markers 342 and define a closed loop path for the robot vehicle 302 using the second matrix of second ground markers 342 in the calibration zone 340, as part of the recalibration routine. Such process has been schematically illustrated in FIG. 4 for reference. Usually, the robot vehicle 302 may be instructed to start from one of the second ground markers 342 in the second matrix of second ground markers 342 in the calibration zone 340. For example, as shown in FIG. 4, the robot vehicle 302 may start from one of the second ground markers 342 located at one of the corners in the said portion with the second ground markers 342 in the calibration zone 340. However, it may be appreciated that the robot vehicle 302 could start from any of the second ground markers 342 in the said portion with the second ground markers 342 in the calibration zone 340. The robot vehicle 302 may further usually be instructed to define the closed geometric loop 410 in the shape of a square, a rectangle, a circle, or the like.
[0069] The processing unit 205 is further configured to estimate, using the sensing arrangement 330, a position of the robot vehicle 302 with respect to the said one of the second ground markers 342 after completion of the movement along the said closed geometric closed geometric loop 410. That is, when the robot vehicle 302 may have completed the closed geometric loop 410 and may have reached back the same second ground marker 342 (or at least in vicinity thereof) from which the robot vehicle 302 started (such as, the corner second ground marker 342 in the second matrix of second ground markers 342), the sensing arrangement 330 is instructed to estimate the position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the end of the closed geometric loop 410 in comparison to the position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the start of the closed geometric loop 410. The steps involved in such relative determination may be contemplated and thus not described herein.
[0070] The processing unit 205 is further configured to determine an offset based on the estimated position of the robot vehicle 302 with respect to the said one of the second ground markers 242. Specifically, herein, the offset is determined as the difference in estimated position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the end of the closed geometric loop 410 in comparison to the position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the start of the closed geometric loop 410. The determined offset may provide an indication of possible positional inaccuracy in the movement of the robot vehicle 302 when following a path (like, the predefined path 312) using the ground markers (such as, the first ground markers 306 in the work area 300). It may be understood that the determined offset may include a set of offsets for multiple parameters utilized by the odometry control arrangement 320 of the robot vehicle 302 for controlling movement of the robot vehicle 302 in the work area 300. Such multiple parameters may correspond to one or more of lateral error, longitudinal error, orientation error and the like, as discussed above.
[0071] In an embodiment, the processing unit 205 may perform the recalibration routine multiple number of times, or at least for two times. The processing unit 205 may compare the offsets determined from each of the recalibration routines. If the determined offsets for two or more consecutively performed recalibration routines may be within a predefined margin of each other (e.g., ± 10%), then the determined value of the offset may be implemented for further processing; or otherwise (i.e., when not within the predefined margin) such determined value of the offset may be rejected, and the recalibration routine may be performed again as per the process described herein.
[0072] The processing unit 205 is further configured to calibrate the odometry control arrangement 320 of the robot vehicle 302 based on the determined offset. Herein, the determined offset is stored in a memory (such as, the memory 210) of the system 100. Such stored offset may be applied by the odometry control arrangement 320 every time to the said parameters, when the corresponding parameter may be implemented for controlling the movement of the robot vehicle 302 in the work area 300. This way the determined odometry error due to some issue with the odometry control arrangement 320 of the robot vehicle 302 may be compensated, by application of the determined offset therefor.
[0073] The processing unit 205 is further configured to configure the robot vehicle 302 to move to the work area 300 after calibration of the odometry control arrangement 320 thereof. That is, once the recalibration routine is completed, the robot vehicle 302 is instructed by the system 100 to move back to the work area 300 to be able to perform regulation operations thereof. With the odometry control arrangement 320 of the robot vehicle 302 now being calibrated, the robot vehicle 302 may be able to precisely follow the predefined path 312 therefor (as provided by the system 100) during the operational cycle thereof, and thereby resulting in (contributing to) even more efficient operation of the present system 100.
[0074] The present disclosure further provides a method for automatically calibrating odometry parameters of a robot vehicle implemented to move in a work area comprising a first matrix of first ground markers during an operational cycle thereof. Various embodiments and variants disclosed above, with respect to the aforementioned system 100, apply mutatis mutandis to the present method. FIG. 5 is a flowchart 500 of a method for automatically calibrating odometry parameters of a robot vehicle implemented to move in a work area comprising a first matrix of first ground markers during an operational cycle thereof. The various steps involved in the present method has been depicted as blocks in the flowchart 500 of FIG. 5, and the details for the same have been provided hereinafter.
[0075] At step 502, the method includes estimating a position of the robot vehicle with respect to one of the first ground markers, from the first matrix of first ground markers, in vicinity thereof when moved using an odometry control arrangement thereof, during the operational cycle thereof. For this purpose, the sensing arrangement 330 may determine a relative position of the robot vehicle 302 with respect to the first ground marker 306 in vicinity thereof. Herein, the sensing arrangement 330 may be provided in the robot vehicle 302 and/or external to the robot vehicle 302.
[0076] At step 504, the method includes determining an odometry error in the movement of the robot vehicle in the work area based on the estimated position of the robot vehicle with respect to one of the first ground markers. Herein, the term “odometry error” represents a navigation error in the robot vehicle 302 in the work area 300. As discussed, the predefined path 312 as provided by the system 100 is a navigation path including a set of straight lines passing through centres of the first ground markers 306, in the first matrix of first ground markers 306 in the work area 300. Such navigation error may occur when the robot vehicle 302 may deviate from such straight lines (e.g., missing the centres of the first ground markers 306) while supposedly following the predefined path 312 during the operational cycle thereof. In an example implementation, the sensing arrangement 330 may utilize the processing unit 205 of the system 100 for performing the computation and calculations (as described in the proceeding paragraphs) required for confirming the odometry error in the movement of the robot vehicle 302 as per embodiments of the present disclosure.
[0077] At step 506, the method includes determining a suitable time for the robot vehicle to be moved out of the work area based, at least in part, on the operational cycle thereof in response to determination of the odometry error. For this purpose, the processing unit 205 may determine the time when the robot vehicle 302 may be sent to the calibration zone 340 for calibration of the odometry control arrangement 320 therein such that to minimally affect the overall operation of the system 100. In an embodiment, the processing unit 205 is configured to determine the suitable time based on workload of the robot vehicle 302 in the work area 300. Particularly, if the robot vehicle 302 may be handling a critical task of the overall operation, which if not completed may otherwise affect operations of various other components in the system 100, or may be required to complete a current task, and the determined odometry error may still be within the said predetermined threshold and thereby not significantly affect the current task), then it may delay a start of the recalibration routine. In another embodiment, the processing unit 205 is configured to determine the suitable time as time of completion of the operational cycle for the robot vehicle 302. That is, the system 100 may determine when the current operational cycle of the robot vehicle 302 may be completed, including all tasks involved therein. And when all such tasks may be expected to be completed, the system 100 may define that particular time as the suitable time for the robot vehicle 302 to be moved out of the work area 300, such that the overall operation of the system 100 is not affected at all.
[0078] At step 508, the method includes configuring the robot vehicle to move to a calibration zone, located outside of the work area, at the determined suitable time therefor, the calibration zone comprising a second matrix of second ground markers, with a density of the second ground markers in the second matrix of second ground markers being greater than a density of the first ground markers in the first matrix of first ground markers. For this purpose, the system 100 sends a command to the robot vehicle 302 to move to the calibration zone 340 at the determined suitable time. With the robot vehicle 302 being autonomous, it may move to the calibration zone 340 without any human intervention, using the odometry control arrangement 320 provided therein. In case, the determined odometry error for the odometry control arrangement 320 may be significantly high such that the robot vehicle 302 may not be in a condition to reach the calibration zone 340 autonomously, then the system 100 may generate an alarm for the like as an indication for a human operator to support and move the robot vehicle 302 to the calibration zone 340, for performing the required recalibration routine.
[0079] At step 510, the method includes configuring the robot vehicle to move, using the odometry control arrangement thereof, along a closed geometric loop starting from one of the second ground markers and ending at the same said one of the second ground markers, from the second matrix of second ground markers in the calibration zone. For this purpose, when the robot vehicle 302 may reach the calibration zone 340, the system 100 instructs the robot vehicle 302 to start from one of the second ground markers 342 and define a closed loop path for the robot vehicle 302 using the second matrix of second ground markers 342 in the calibration zone 340, as part of the recalibration routine. Such process has been schematically illustrated in FIG. 4 for reference. Usually, the robot vehicle 302 may be instructed to start from one of the second ground markers 342 (such as, but not limited to, located at one of the corners in the second matrix of second ground markers 342) in the calibration zone 340 (as shown in FIG. 4). The robot vehicle 302 may further usually be instructed to define the closed geometric loop (represented in FIG. 4 with the numeral 410) in the shape of a square or a rectangle, or the like.
[0080] At step 512, the method includes estimating a position of the robot vehicle with respect to the said one of the second ground markers after completion of the movement along the said closed geometric loop. For this purpose, when the robot vehicle 302 may have completed the closed geometric loop 410 and may have reached back the same second ground marker 342 (or at least in vicinity thereof) from which the robot vehicle 302 started (such as, the corner second ground marker 342 in the second matrix of second ground markers 342), the sensing arrangement 330 is instructed to estimate the position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the end of the closed geometric loop 410 in comparison to the position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the start of the closed geometric loop 410. The steps involved in such relative determination may be contemplated and thus not described herein.
[0081] At step 514, the method includes determining an offset based on the estimated position of the robot vehicle with respect to the said one of the second ground markers. For this purpose, the offset is determined as the difference in estimated position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the end of the closed geometric loop 410 in comparison to the position of the robot vehicle 302 with respect to the said corner second ground marker 342 at the start of the closed geometric loop 410. The determined offset may provide an indication of possible positional inaccuracy in the movement of the robot vehicle 302 when following a path (like, the predefined path 312) using the ground markers (such as, the first ground markers 306 in the work area 300). It may be understood that the determined offset may include a set of offsets for multiple parameters utilized by the odometry control arrangement 320 of the robot vehicle 302 for controlling movement of the robot vehicle 302 in the work area 300. Such multiple parameters may correspond to one or more of lateral error, longitudinal error, orientation error and the like, as discussed above. In an embodiment, the processing unit 205 may perform the recalibration routine multiple number of times, or at least for two times. The processing unit 205 may compare the offsets determined from each of the recalibration routines. If the determined offsets for two or more consecutively performed recalibration routines may be within a predefined margin of each other (e.g., ± 10%), then the determined value of the offset may be implemented for further processing; or otherwise (i.e., when not within the predefined margin) such determined value of the offset may be rejected, and the recalibration routine may be performed again as per the process described herein.
[0082] At step 516, the method includes calibrating the odometry control arrangement of the robot vehicle based on the determined offset. For this purpose, the determined offset is stored in a memory (such as, the memory 210) of the system 100. Such stored offset may be applied by the odometry control arrangement 320 every time to the said parameters, when the corresponding parameter may be implemented for controlling the movement of the robot vehicle 302 in the work area 300. This way the determined odometry error due to some issue with the odometry control arrangement 320 of the robot vehicle 302 may be compensated, by application of the determined offset therefor.
[0083] At step 518, the method includes configuring the robot vehicle to move to the work area after calibration of the odometry control arrangement thereof. For this purpose, once the recalibration routine is completed, the robot vehicle 302 is instructed by the system 100 to move back to the work area 300 to be able to perform regulation operations thereof. With the odometry control arrangement 320 of the robot vehicle 302 now being calibrated, the robot vehicle 302 may be able to precisely follow the predefined path 312 therefor (as provided by the system 100) during the operational cycle thereof, and thereby resulting in (contributing to) even more efficient operation.
[0084] In an embodiment, the method further includes determining one or more of: a cross track error, a number of missed first ground markers and an average of goal reaching tolerances, based on the estimated position of the robot vehicle with respect to one of the first ground markers during the operational cycle thereof, to determine the odometry error. In an example, the odometry error in the movement of the robot vehicle 302 may be determined based on lateral error (cross track error) which is the distance between the geometric centre of the marker recognizer 310 on the robot vehicle 302 and the closest point on the predefined path 312. Lateral error is the principal measure of how close the position of the robot vehicle 302 is to the desired position along the predefined path 312. In an example, the odometry error may be determined based on number of emergency stop incidents of the robot vehicle 302 during the operational cycle. Such emergency stop incidents of the robot vehicle 302 may occur when the robot vehicle 302 would stop or would have to be stopped (either manually or automatically by the system 100) due to improper functioning of the odometry control arrangement 320 therein. In an example, the odometry error may be determined based on the average goal reaching error of the robot vehicle 302. Herein, the average goal reaching error may include longitudinal error which is defined as a difference between the centre of the first ground marker 306 and the centre of the marker recognizer 310 along a direction of movement of the robot vehicle 302, and an orientation error which is defined as the angular difference between the heading of the robot vehicle 302 (in the direction of movement) and the first ground marker 306. In an example, the odometry error may be determined based on number of missed first ground markers by the robot vehicle 302 during its operational cycle while supposedly following the predefined path 312. As during conventional operation, the first ground marker 306 is to be detected at a fixed/variable set of distances, and if the first ground marker 306 is not detected (e.g., by the marker recogniser 310) at the said fixed/variable distance (or the ground marker count threshold) during the operational cycle in the work area 300, the incident is counted as a missed first ground marker. It may be appreciated that all these determined errors may generally be determined based on the estimated position of the robot vehicle 302 with respect to one of the first ground markers 306. These different errors are recorded and quantified by the sensing arrangement 330 to determine an average/rolling values of such errors in isolation or combination during the operational cycle of the robot vehicle 302, and if such average exceeds a predetermined threshold, the sensing arrangement 330 may confirm the odometry error in the movement of the robot vehicle 302 in the work area 300.
[0085] In an embodiment, the method further includes determining the suitable time based on workload of the robot vehicle in the work area. That is, if the robot vehicle 302 may be handling a critical task of the overall operation, which if not completed may otherwise affect operations of various other components in the system 100, or may be required to complete a current task, and the determined odometry error may still be within the said predetermined threshold and thereby not significantly affect the current task), then it may delay a start of the recalibration routine. Further, if the system 100 may determine when the current operational cycle of the robot vehicle 302 may be completed, including all tasks involved therein. And when all such tasks may be expected to be completed, the system 100 may define that particular time as the suitable time for the robot vehicle 302 to be moved out of the work area 300, such that the overall operation of the system 100 is not affected at all.
[0086] The system and the method of the present disclosure provide for automatically calibrating odometry parameters of the robot vehicle. It may be appreciated that the robot vehicles may already have means (like, the sensing arrangement) for providing information about exceptions, contingencies, recorded incidents, faults, runtimes (such as, max path deviation, average goal reach accuracy, total distance run etc.). Herein, the robot vehicles are commanded to undergo an automatic calibration routine in an opportunistic manner by the present system based on the frequency of exception events or by similar means. The present disclosure addresses and corrects for the fact that systemic and non-systemic odometry errors accumulate over the operational life for an autonomous robot, like the present robot vehicle. The present disclosure provides that the odometry errors are corrected in an opportunistic fashion subsequently followed by an automated calibration routine.
[0087] Herein, the fleet management system determines if the robot vehicle needs to be calibrated (sent to the calibration zone), if the average/ rolling average values during runtime of any of the working situations exceed a predetermined threshold in the operational cycle thereof. The fleet management system monitors working situation of each of the robot vehicles in the fleet of robot vehicles in the work area. The fleet management system receives an exception signal if any one of the robot vehicles may have an odometry error. The fleet management system determines if that particular robot vehicle needs to be re-calibrated. If yes, then the fleet management system may allocate the calibration zone to the robot vehicle. The fleet management system may then send command to the robot vehicle to move to the calibration zone such that it may not significantly affect the normal operation. The robot vehicle receives the position information (coordinates) of calibration zone and move to the calibration zone. The robot vehicle estimates its position from the dense second ground markers in the calibration zone by performing recalibration routine, involving moving in the closed geometric loop. Such recalibration routine may be performed multiple times to determine the respective offsets. Further, it may be checked if the determined offsets are within predefined margin. If not, the recalibration routine may again be performed. If yes, the determined offset is applied to the robot vehicle, which may then resume its normal operation by moving back from the calibration zone to the work area.
[0088] By following the above process, the present disclosure provides for calibration process to be made autonomous and opportunistic, i.e., the system will choose when to send the robot vehicle working in a common work area for the calibration process without affecting system throughput, and thereby provide non-stop robot operation of the system. The present disclosure ensures self-maintenance and predictive maintenance of the robot vehicle. The present disclosure may be implemented for any type of robot vehicles using grid based navigation. The present disclosure improves robot performance, improves system stability, and reduces system, downtime.
[0089] The foregoing descriptions of specific embodiments of the present disclosure have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the present disclosure to the precise forms disclosed, and obviously many modifications and variations are possible in light of the above teaching. The exemplary embodiment was chosen and described in order to best explain the principles of the present disclosure and its practical application, to thereby enable others skilled in the art to best utilize the present disclosure and various embodiments with various modifications as are suited to the particular use contemplated.

Claims:

WE CLAIM
1. A system for automatically calibrating odometry parameters of a robot vehicle implemented to move in a work area comprising a first matrix of first ground markers during an operational cycle thereof, the system comprising:
an odometry control arrangement provided in the robot vehicle, the odometry control arrangement configured to control movement of the robot vehicle in the work area based on the first ground markers therein;
a sensing arrangement configured to estimate a position of the robot vehicle with respect to one of the first ground markers, from the first matrix of first ground markers, in vicinity thereof when moved using the odometry control arrangement during the operational cycle thereof, and determine an odometry error in the movement of the robot vehicle in the work area based on the estimated position of the robot vehicle with respect to one of the first ground markers; and
a calibration zone located outside of the work area, the calibration zone comprising a second matrix of second ground markers, with a density of the second ground markers in the second matrix of second ground markers being greater than a density of the first ground markers in the first matrix of first ground markers;
a processing unit configured to:
determine a suitable time for the robot vehicle to be moved out of the work area based, at least in part, on the operational cycle thereof in response to determination of the odometry error by the sensing arrangement;
configure the robot vehicle to move to the calibration zone at the determined suitable time therefor;
configure the robot vehicle to move, using the odometry control arrangement thereof, along a closed geometric loop starting from one of the second ground markers and ending at the same said one of the second ground markers, from the second matrix of second ground markers in the calibration zone;
estimate, using the sensing arrangement, a position of the robot vehicle with respect to the said one of the second ground markers after completion of the movement along the said closed geometric loop;
determine an offset based on the estimated position of the robot vehicle with respect to the said one of the second ground markers;
calibrate the odometry control arrangement of the robot vehicle based on the determined offset; and
configure the robot vehicle to move to the work area after calibration of the odometry control arrangement thereof.

2. The system as claimed in claim 1, wherein the sensing arrangement is provided in the robot vehicle, and wherein the sensing arrangement comprises one or more of: a set of wheel encoders associated with drive wheels of the robot vehicle, an odometer, an inertial measurement unit and a marker recognizer.

3. The system as claimed in claim 1, wherein the sensing arrangement is external to the robot vehicle, and wherein the sensing arrangement comprises one or more imaging device arranged to provide a view covering at least the work area and the calibration zone.

4. The system as claimed in claim 1, wherein the sensing arrangement is configured to determine one or more of: a cross track error, a number of missed first ground markers and an average of goal reaching tolerances, based on the estimated position of the robot vehicle with respect to one of the first ground markers during the operational cycle thereof, to determine the odometry error.

5. The system as claimed in claim 1, wherein the processing unit is configured to determine the suitable time based on workload of the robot vehicle in the work area.

6. The system as claimed in claim 1, wherein the processing unit is configured to determine the suitable time as time of completion of the operational cycle for the robot vehicle.

7. The system as claimed in claim 1, wherein a ratio of the density of the second ground markers in the second matrix of second ground markers in the calibration zone to the density of the first ground markers in the first matrix of first ground markers in the work area is in a range of 4:1 to 8:1.

8. A method for automatically calibrating odometry parameters of a robot vehicle implemented to move in a work area comprising a first matrix of first ground markers during an operational cycle thereof, the method comprising:
estimating a position of the robot vehicle with respect to one of the first ground markers, from the first matrix of first ground markers, in vicinity thereof when moved using an odometry control arrangement thereof, during the operational cycle thereof;
determining an odometry error in the movement of the robot vehicle in the work area based on the estimated position of the robot vehicle with respect to one of the first ground markers;
determining a suitable time for the robot vehicle to be moved out of the work area based, at least in part, on the operational cycle thereof in response to determination of the odometry error;
configuring the robot vehicle to move to a calibration zone, located outside of the work area, at the determined suitable time therefor, the calibration zone comprising a second matrix of second ground markers, with a density of the second ground markers in the second matrix of second ground markers being greater than a density of the first ground markers in the first matrix of first ground markers;
configuring the robot vehicle to move, using the odometry control arrangement thereof, along a closed geometric loop starting from one of the second ground markers and ending at the same said one of the second ground markers, from the second matrix of second ground markers in the calibration zone;
estimating a position of the robot vehicle with respect to the said one of the second ground markers after completion of the movement along the said closed geometric loop;
determining an offset based on the estimated position of the robot vehicle with respect to the said one of the second ground markers;
calibrating the odometry control arrangement of the robot vehicle based on the determined offset; and
configuring the robot vehicle to move to the work area after calibration of the odometry control arrangement thereof.

9. The method as claimed in claim 8 further comprising determining one or more of: a cross track error, a number of missed first ground markers and an average of goal reaching tolerances, based on the estimated position of the robot vehicle with respect to one of the first ground markers during the operational cycle thereof, to determine the odometry error.

10. The method as claimed in claim 8 further comprising determining the suitable time based on workload of the robot vehicle in the work area.