Automated laboratory system and method therefor

Abstract

An automated laboratory system having three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules. Each of the laboratory modules has: a respective enclosure, and a respective function in regard to a sample process. The function is different from that of another of the three or more laboratory modules. Each of the respective enclosures forms one or more spaces allowing objects to be passed therethrough so as to allow the generally lateral transfer of an object into, out of, or between laboratory modules.

Description

AUTOMATED LABORATORY SYSTEM AND METHOD THEREFORFIELD

[0001] The present disclosure relates to equipment of the type used in high throughput analytical laboratories, and also equipment used in small scale research applications. More particularly, the present disclosure relates to equipment for automated handling and processing of samples for analysis.BACKGROUND

[0002] Automation has revolutionized the operation of analytical and research laboratories. By integrating advanced robotics, instrumentation, and software, laboratory automation optimizes workflows, enhances process reproducibility, as well as reducing labor costs.

[0003] At its core, laboratory automation aims to streamline experimental workflows by replacing manual tasks with automated processes. This involves the integration of robotic systems capable of performing a wide array of tasks, ranging from sample preparation and handling, sample analysis, output data analysis and storage.

[0004] Laboratory automation encompasses a diverse array of methodologies tailored to specific process requirements. Liquid handling robots, equipped with precision pipetting systems, enable accurate dispensing of reagents and samples, facilitating high-throughput screening and assay development. Integrated robotic workstations automate sample preparation workflows, including DNA extraction, purification, and amplification, revolutionizing genomics and molecular biology research. High-content imaging systems coupled with automated analysis software enable rapid acquisition and analysis of large-scale image datasets, empowering researchers in drug discovery and cell biology.

[0005] Automation is especially prevalent in high throughput analytical laboratories of the type used to analyses samples of clinical, environmental and industrial origin. Such laboratories aretasked with performing analysis on hundreds or thousands of individual samples per day, and automation is absolutely essential to operations.

[0006] Generally, the automation is provided as partial laboratory automation, total laboratory automation, and modular laboratory automation. With partial automation, automated work cells perform highly repetitive tasks with human oversight. These automated work cells are typically incompatible with other automated systems. With total automation, the processing of samples is entirely automated by employing conveyor transports, robotics, analysis interfaces, and sample storage systems. Total laboratory automation systems generally provide and end-to-end solution, where sample processing can be streamlined and completely automated. However, total laboratory automation systems have low flexibility that prohibits easy and cost effective reconfiguration of the system. Modular laboratory automation attempts to combine partial laboratory automation with total laboratory automation by integrating sample processing equipment into modular work cells. Here, the sample processing equipment of the work cell is arrayed adjacent one another on a workbench where the samples are transferred indirectly between the processing equipment by automation or humans. The area or floor space occupied by the processing equipment, arrayed on the workbench, varies depending on the number of processes performed within the work cell.

[0007] It is an aspect of the present disclosure to provide an improvement to the prior art. It is a further aspect of the present disclosure to provide a useful alternative to the prior art.

[0008] The discussion of documents, acts, materials, devices, articles and the like is included in this specification solely for the purpose of providing a context for the present disclosure. It is not suggested or represented that any or all of these matters formed part of the prior art base or were common general knowledge in the field relevant to the present disclosure as it existed before the priority date of each claim of this application.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The foregoing aspects and other features of the disclosed embodiment are explained in the following description, taken in connection with the accompanying drawings, wherein:

[0010] FIG. 1 is a schematic perspective illustration of an exemplary collaborative process facility incorporating aspects of the present disclosure;

[0011] FIG. 2 is a schematic perspective illustration of a portion of a laboratory module of the collaborative process facility of FIG. 1 in accordance with aspects of the present disclosure;

[0012] Figs. 3A and 3B are schematic perspective illustrations of portions of the collaborative process facility of FIG. 1 in accordance with aspects of the present disclosure;

[0013] Figs. 4-9 are schematic perspective illustrations of portions of the collaborative process facility of FIG. 1 in accordance with aspects of the present disclosure;

[0014] FIG. 10 illustrates and exemplary high-level software architecture for controlling operation of the collaborative process facility of FIG. 1 in accordance with aspects of the present disclosure;

[0015] FIG. 11 is an exemplary illustration of a finite state machine in accordance with aspects of the present disclosure;

[0016] FIG. 12 is an exemplary illustration of a neural network in accordance with aspects of the present disclosure;

[0017] FIG. 13 is an exemplary illustration of a neural network providing weights to a finite state machine in accordance with aspects of the present disclosure;

[0018] FIG. 14 illustrates an exemplary process for controlling the collaborative process facility with a finite state machine and a neural network in accordance with aspects of the present disclosure;

[0019] FIG. 15 is a flow diagram of a method in accordance with aspects of the present disclosure;

[0020] FIG. 16 is a schematic illustration of target image acquisition in accordance with aspects of the present disclosure;

[0021] FIG. 17 is an exemplary array of targets in accordance with aspects of the present disclosure;

[0022] FIG. 18 is an exemplary flow diagram in accordance with aspects of the present disclosure;

[0023] FIG. 19 is a schematic illustration of target image acquisition in accordance with aspects of the present disclosure; and

[0024] FIG. 20 is a schematic illustration a three laboratory modules of the type shown in FIG. 2, arranged linearly. The double headed arrows show the direction of movement of an object (such as a sample tube) between the laboratory modules.

[0025] Unless otherwise indicated herein, features of the drawings labelled with the same numeral are taken to be the same features, or at least functionally similar features, when used across different drawings.

[0026] The drawings are not prepared to any particular scale or dimension and are not presented as being a completely accurate presentation of the various embodiments.SUMMARY

[0027] In a first aspect, but not necessarily the broadest aspect, there is provided an automated laboratory system comprising: three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules, each of the three or more laboratory modules has: a respective enclosure, and a respective predetermined function characteristic disposed so as to effect a respective predetermined sampleprocess, the predetermined function characteristic of at least one of the laboratory modules being different from another predetermined function characteristic of another of the different laboratory modules, wherein each of the respective enclosures forms one or more spaces allowing passage of objects therethrough so as to allow the generally lateral transfer of an object into, out of, or between two or three of the three or more laboratory modules.

[0028] In one embodiment of the first aspect, the one or more spaces allow passage of objects to and from a space external to the enclosure, the space not being within an enclosure of another of the one of the three or more laboratory modules.

[0029] In one embodiment of the first aspect, the automated laboratory system comprises a robotic transport configured to transfer of an object into, out of, or between the three or more laboratory modules.

[0030] In one embodiment of the first aspect, the one or more spaces allows for the passage of at least a portion the robotic transport therethrough.

[0031] In one embodiment of the first aspect, the robotic transport is separate from, or is not contained within, the three or more laboratory modules.

[0032] In one embodiment of the first aspect, the robotic transport comprises a member configured to pass through the one or more spaces so as locate an object alternately internal and external to the respective enclosure.

[0033] In one embodiment of the first aspect, the member is part of an articulated or nonarticulated arm.

[0034] In one embodiment of the first aspect, the robotic transport is configured to transport an object along an axis of the three or more laboratory modules.

[0035] In one embodiment of the first aspect, the robotic transport is configured to transport an object along each of two axes of the three or more laboratory modules.

[0036] In one embodiment of the first aspect, the robotic transport is configured to transport an object along each of three axes of the three or more laboratory modules.

[0037] In one embodiment of the first aspect, the robotic transport is configured to transport an object along a vertical axis.

[0038] In one embodiment of the first aspect, the robotic transport is configured to transport an object along a path that is independent of any axis of the three or more laboratory modules.

[0039] In one embodiment of the first aspect, the robotic transport is configured to transport an object bi-directionally along an axis or a path.

[0040] In one embodiment of the first aspect, the robotic transport has three degrees of freedom.

[0041] In one embodiment of the first aspect, the robotic transport does not require a belt, a track, or a guide.

[0042] In one embodiment of the first aspect, the robotic transport is configured to be collaborative with a human.

[0043] In one embodiment of the first aspect, the enclosure(s) are configured to facilitate vertical stacking of two or more laboratory modules.

[0044] In one embodiment of the first aspect, the one of more laboratory modules comprise two or more vertical levels.

[0045] In one embodiment of the first aspect, the automated laboratory system comprises robotic transport, and the robotic sample transport is configured to transport an object between the two or more vertical levels.

[0046] In one embodiment of the first aspect, the object is a vessel, a sample, a reagent, a rack, or a rack carrier.

[0047] In one embodiment of the first aspect, the selected three or more laboratory modules forms a cluster of laboratory modules, each of the three or more selected laboratory modules having a multi-axis interface configured to effect transfer of objects between laboratory modules by one or more of transferring objects between the laboratory modules internal to the respective enclosures and external to the respective enclosures.

[0048] In one embodiment of the first aspect, each of the different laboratory modules has a modular interface formed by the respective enclosure, the modular interface being configured to interface and connect the three or more laboratory modules, selected for installation, to at least one other laboratory module, of the different and interchangeable laboratory modules, so that the modular interface at least one of: couples the three or more laboratory modules and the at least one other laboratory module to each other, and communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules and the at least one other laboratory module with each other; wherein the compartmentalized predetermined sample process of the selected three or more laboratory modules defines a system sample process, and upon interface with the at least one otherlaboratory module, the system sample process changes from a closed system process to an open system process.

[0049] In one embodiment of the first aspect, the closed system process is characterized by the compartmentalized predetermined sample process respective to the selected three or more laboratory modules.

[0050] In one embodiment of the first aspect, the open system process is characterized by a combination of the compartmentalized predetermined sample process respective to the selected three or more laboratory modules and the at least one other laboratory module interfaced with each other.

[0051] In one embodiment of the first aspect, the open system process changes upon interface of one or more other laboratory modules, from the number of different interchangeable laboratory modules, to the selected three or more laboratory modules.

[0052] In one embodiment of the first aspect, the open system process changes upon de-interface of three or more laboratory modules, from the number of different interchangeable laboratory modules, from the selected three or more laboratory modules.

[0053] In one embodiment of the first aspect, the open system process changes upon interchange of one or more of the selected three or more laboratory modules with a different one or more laboratory module from the number of different interchangeable laboratory modules.

[0054] In one embodiment of the first aspect, the selected three or more laboratory modules forms a cluster of laboratory modules having a predetermined spatial footprint, and the number of different and interchangeable laboratory modules are quasi-fungible with respect to the predetermined spatial footprint.

[0055] In one embodiment of the first aspect, the selected three or more laboratory modules forms a cluster of laboratory modules, each of the three or more selected laboratory modules having a multi-axis interface configured to effect transfer of objects into, out of, or between laboratory modules.

[0056] In one embodiment of the first aspect, the automated laboratory system comprises a robotic transport external to the three or more laboratory modules, the robotic transport being configured to interface with each module of the cluster of laboratory modules through the multi-axis interface and effect the external transfer of objects between two or three of the three or more selected laboratory modules and to and from the three or more selected laboratory modules.

[0057] In one embodiment of the first aspect, at least one axis of the multi-axis interface is a collaborative workspace interface.

[0058] In one embodiment of the first aspect, the three or more laboratory modules is four, five, six, seven, eight, nine or ten laboratory modules.

[0059] In one embodiment of the first aspect, the three or more laboratory modules are arranged so as to allow for a generally linear transfer of the object from the first to the second of the three or more laboratory modules, and from the second to the third of the three or more laboratory modules.

[0060] In a second aspect, there is provided a method for an automated laboratory system, the method comprising: providing three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules, each of the three or more laboratory modules has:a respective enclosure, a respective predetermined function characteristic disposed so as to effect a respective predetermined sample process, and a modular interface formed by the respective enclosure, wherein the predetermined function characteristic of at least one of the different laboratory modules is different from another predetermined function characteristic of another of the different laboratory modules, and wherein each of the respective enclosures forms one or more spaces allowing passage of objects therethrough so as to allow the generally lateral transfer of an object into, out of, or between two or three of the three or more laboratory modules; and interfacing and connecting the three or more laboratory modules selected for installation, via a respective modular interface, to at least one other laboratory module, of the different and interchangeable laboratory modules, so that the respective modular interface at least one of: couples the three or more laboratory modules and the at least one other laboratory module to each other, and communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules and the at least one other laboratory module with each other; wherein the compartmentalized predetermined sample process of the selected three or more laboratory modules defines a system sample process, and upon interface with the at least one other laboratory module, the system sample process changes from a closed system process to an open system process.

[0061] In one embodiment of the second aspect, the closed system process is characterized by the compartmentalized predetermined sample process respective to the selected three or more laboratory modules.

[0062] In one embodiment of the second aspect, the open system process is characterized by a combination of the compartmentalized predetermined sample process respective to the selectedthree or more laboratory modules and the at least one other laboratory module interfaced with each other.

[0063] In one embodiment of the second aspect, the open system process changes upon interface of one or more other laboratory modules, from the number of different interchangeable laboratory modules, to the selected three or more laboratory modules.

[0064] In one embodiment of the second aspect, the open system process changes upon deinterface of three or more laboratory modules, from the number of different interchangeable laboratory modules, from the selected three or more laboratory modules.

[0065] In one embodiment of the second aspect, the open system process changes upon interchange of one or more of the selected three or more laboratory modules with a different one or more laboratory module from the number of different interchangeable laboratory modules.

[0066] In one embodiment of the second aspect, the selected three or more laboratory modules forms a cluster of laboratory modules having a predetermined spatial footprint, and the number of different and interchangeable laboratory modules are quasi-fungible with respect to the predetermined spatial footprint.

[0067] In one embodiment of the second aspect, the selected three or more laboratory modules forms a cluster of laboratory modules, each of the three or more selected laboratory modules having a multi-axis interface configured to effect transfer of objects between laboratory modules by one or more of transferring objects between the laboratory modules internal to the respective enclosures and external to the respective enclosures.

[0068] In one embodiment of the second aspect, the method further comprises interfacing a robotic transport, disposed external to the three or more laboratory modules, with each module of the cluster of laboratory modules through the multi-axis interface and effecting, with the robotictransport, the external transfer of objects between two or three of the three or more selected laboratory modules and to and from the three or more selected laboratory modules.

[0069] In one embodiment of the second aspect, at least one axis of the multi-axis interface is a collaborative workspace interface.

[0070] In any embodiment of the first or the second aspect having robotic transport, the robotic transport may be configured to be collaborative with a human.DETAILED DESCRIPTION

[0071] After considering this description it will be apparent to one skilled in the art how the disclosure is implemented in various alternative embodiments and alternative applications. However, although various embodiments of the present disclosure will be described herein, it is understood that these embodiments are presented by way of example only, and not limitation. As such, this description of various alternative embodiments should not be construed to limit the scope or breadth of the present disclosure. Furthermore, statements of advantages or other aspects apply to specific exemplary embodiments, and not necessarily to all embodiments, or indeed any embodiment covered by the claims.

[0072] Throughout the description and the claims of this specification the word "comprise" and variations of the word, such as "comprising" and "comprises" is not intended to exclude other additives, components, integers or steps.

[0073] Reference throughout 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 . Thus, appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment, but may.

[0074] Reference throughout 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. Thus, appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment, but may.

[0075] It will be appreciated that not all embodiments of the present disclosure have all of the advantages disclosed herein. Some embodiments may have a single advantage, while other may have no advantage at all and are merely a useful alternative to the prior art.

[0076] The present disclosure may be embodied in an automated laboratory system comprising: three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules, each of the three or more laboratory modules has: a respective enclosure, and a respective predetermined function characteristic disposed so as to effect a respective predetermined sample process, the predetermined function characteristic of at least one of the laboratory modules being different from another predetermined function characteristic of another of the different laboratory modules, wherein each of the respective enclosures forms one or more spaces allowing passage of objects (such as vessels) therethrough so as to allow the generally lateral transfer of an object into, out of, or between two or three of the three or more laboratory modules.

[0077] The present disclosure may provide, in some embodiments, an improved automated laboratory system having task-specific modules and a transport robot, the robot being capable of moving a vessel (containing sample or reagent for example) into, out of, and between modules. Moreover, the modules may be arranged horizontally, vertically or diagonally. Modules may bearranged linearly or non-linearly, with interfaces between modules formed between any two, three or more faces or edges or regions. In some embodiments arranged modules may be arranged so as to result in structures such as lines, T-shapes, L-shapes, rings, part-circles, pyramids, cubes etc. The modules may be vertically stackable, or may themselves comprises vertical levels therein, with the transport robot being configured to move vessels vertically with a module or between stacked modules. The transport robot may be configured to also move vessels horizontally between modules. In some embodiments, the transport robot is configured to move vessels vertically and / or horizontally and / or diagonally for the movement of vessels between non-modular elements of a system, such as centrifuges, heat blocks, wash stations and the like.

[0078] In the prior art, linear conveyors transport vessels horizontally only and typically only in a single direction. Thus, an automated process is generally limited to an arrangement whereby a sample is processed in a predetermined set of process steps, and in a predetermined order. Thus, when implemented in a modular manner, each of the modules is arranged end-to-end so as to create a simple production line of sorts. The sample may be conveyed linearly and uni-directionally from the first module, to the second module, then to the third, and so on until the processing steps are complete. If a different set of processing steps is required, the modules must be substituted, duplicated or rearranged accordingly. An aspect of the present disclosure negates the need for such substitution, duplication or rearrangement by allowing modules to be accessed in a non-linear manner, or for only certain modules from a larger set of modules to be used.

[0079] A robotic arm, for example, may be used to transport a vessel between two desired modules, with the modules not necessarily being mutually adjacent, so as to achieve two sequential processing steps. A vessel may be returned to an earlier module for a step to be repeated without the need to provide a duplicate module as would be required in a linear processing arrangement.

[0080] The robotic arm is able to access vessels through laterally disposed spaces formed by module enclosures. The spaces are located such that sample may be transported between modules (and not necessarily between adjacent modules), or to stations outside of any modules (such as awashing station or a centrifuge) so as to increase flexibility in process steps or the order of process steps.

[0081] As will be appreciated, the availability of a larger set of modules (as discussed above) increases the footprint of the overall system. Some embodiments allow for the conservation of bench space or floor space by allowing for the vertical stacking of modules, or for a module to have a number of vertical levels. The system foot print may therefore be substantially decreased, while still retaining the flexibility afforded by the availability of a large set of module-specific processes to the user.

[0082] In vertically stackable modules, the enclosures of a lower module may provide support for an upper module (say, by a vertical wall or pillar), while at the same time leaving clear space through which a vessel may be laterally passed by a robotic arm.

[0083] In modules having a number of vertical levels, the levels may be supported by a wall or a pillar of the module. Again, space is typically left through which a vessel may be laterally passed by a robotic arm. Moreover, space should be left for the robotic arm to enter the interior of the module and move a vessel between levels.

[0084] In some embodiments, and to achieve any required robot access to the interior, a module has an enclosure which is of generally open structure, having one or more spaces on the lateral aspects thereof. Vertical elements and optionally horizontal elements are provided about any space so as to support a roof portion of the module. The roof portion may in turn provide a surface upon which an upper module may locate in a module stacking arrangement. In some embodiments, a roof portion is absent, with the vertical elements and optionally horizontal elements providing direct support to an upper module.

[0085] In some embodiments, stacked modules form a frame -like arrangement, with robot access being permitted by the large lateral spaces formed by the frame.

[0086] FIG. 1 illustrates an exemplary laboratory facility or collaborative process facility 100 in accordance with aspects of the present disclosure. Although the aspects of the present disclosure will be described with reference to the drawings, it should be understood that the aspects of the present disclosure can be embodied in many forms. In addition, any suitable size, shape or type of elements or materials could be used.

[0087] The collaborative process facility 100 is illustrated as a collaborative modular laboratory automation workspace or automated laboratory system 100S in which humans 160 and robotic actuators or transports 150 may interact for processing life sciences samples. As will be described in greater detail herein, also referring to FIG. 2, the automated laboratory system 100S includes quasi-fungible laboratory modules 110 each having one or more respective process or workflow axes PX, PY, PZ. The laboratory modules 110 are quasi-fungible in terms of the space envelope (e.g., spatial footprint and / or volume) occupied by the laboratory modules 110 such that the laboratory modules may be coupled or clustered to each other as modular units, with the spatial footprint and / or volume of the clustered laboratory modules remaining substantially the same. The laboratory modules 110 may be coupled to each other (e.g., coupled or clustered one on the other, coupled or clustered along a longitudinal axis, and / or coupled or clustered along a lateral axis) so that the coupling between processing modules 110 is consistent with or corresponds to the process axes PX, PY, PZ of the coupled processing modules 110. This coupling of the laboratory modules 110 along the process axes PX, PY, PZ provides for one or more of a direct (e.g., internal) transfer (e.g., without employing robotic transport 150) of samples between the laboratory modules along one or more of the process axes PX, PY, PZ and an external transfer (e.g., with employment of robotic transport 150) of samples between the laboratory modules along one or more of the process axes PX, PY, PZ.

[0088] Reference is made to FIG. 20 illustrating three laboratory modules 110P, 110Q and 110R, arranged linearly into a system. Each of the three laboratory modules 110P, 110Q and 11 OR is the same or similar to that illustrated in FIG. 2. Objects (not drawn) such as sample tubes are transferred bidirectionally and generally laterally between the laboratory modules 110P, 110Q and110R, as indicated by the double-headed arrows. In some embodiments, the objects are transferred unidirectionally.

[0089] The collaborative process facility 100 includes one or more workbenches 130 on which processing equipment (such as described herein) is disposed, although in other aspects, one or more of the processing equipment may be disposed on the floor rather than on a workbench 130. For example, FIG. 1 illustrates laboratory modules 110 disposed on workbenches 130 while Figs. 3A, 3B, and 9 illustrate that the laboratory modules 110 may also be disposed on a floor of the collaborative process facility 100. The processing equipment may include three or more laboratory modules 110, one or more process stations 115, one or more analyzers 120, and one or more robotic transport 150, although in other aspects the processing equipment may be any suitable life sciences processing equipment.

[0090] The one or more process stations 115 may include one or more of an environmental control module, a sample reader, a centrifuge, racks, storage unit, a scale, or any other suitable process station configured to perform any suitable process on a life sciences sample and / or sample holder (e.g., tray, tube, container, etc. holding or otherwise containing a sample). The analyzers 120 are configured to perform any suitable analysis (e.g., immunoassay, glucose measurement, lactate measurement, plasma measurement, etc.) on the samples.

[0091] The one or more robotic transport 150 is configured as a collaborative robot that conforms to, for example, International Organization for Standardization Technical Specification (ISO / TS) 15066:2016 that specifies the safety requirements for collaborative industrial robot system in a collaborative work environment, where the collaborative work environment is an environment in which the robotic transport 150 operates alongside a human 160 (see FIG. 1) in a shared workspace. Suitable examples of robotic transports that may be employed with the aspects of the present disclosure include, but are not limited to, the PreciseFlex™ family of collaborative robots available from Brooks Automation US, LLC and those described in United States provisional patent application number 63 / 597,957 filed on November 11, 2023 and titled “Robotic TransportSystem and Method Therefor” having attorney docket number 390P017112-US (-#1) and United States provisional patent application number 63 / 580,598 filed on September 5, 2023 and titled “Method for Single Imager Stereoscopic Calibration and Processing Apparatus Including the Single Imager” having attorney docket number 390P017089-US (-#1), the disclosures of which are incorporated herein by reference in their entireties. As illustrated in FIG. 1, the one or more robotic transport 150 may be stationary (i.e., a base of the robotic transport 150 is disposed at a fixed location, such as fixed to the floor or a workbench) or mobile (i.e., the base 311 of the robotic transport 150 is configured in any suitable manner to traverse at least a portion of the floor). For example, the robotic transports 150B include a base 311 that may be coupled to a workbench 130 (or in some aspects the floor) in a fixed predetermined location, while the base 311 of robotic transport 150M may be movably mounted to a track 300 (see Figs. 3 A and 3B) so as to reciprocate or otherwise move along the track 300 under impetus of any suitable drive 313DT of the drive section 313D. In other aspects, mobility of the robotic transport 150M along the floor may be provided in any suitable manner.

[0092] Regardless of whether the base 311 is fixed or mobile, referring also to Figs. 3A and 3B, the robotic transport 150 includes the base 311; an articulated robot frame or arm 312 mounted to the base 311 and having an end effector 340 with a gripper 340G configured to grip and hold an object 350 (e.g., sample, sample container, labware, etc.), and a drive section 313D with at least one motor 313 connected to the articulated robot frame 312 so as to move the end effector 340, relative to the base 311 via articulation of the articulated robot frame 312, with at least one degree of freedom to and from at least one object holding station (such as of one or more of the process stations 115, analyzers 120 and laboratory modules 110), and a machine vision system 320V with an imaging sensor 320 connected to the end effector 340 in predetermined relation to the gripper 340G, and disposed to locate, via motion of the end effector 340, and determine a pose of the at least one object holding station (such as of one or more of the process stations 115, analyzers 120 and laboratory modules 110) in a manner substantially similar to that described in United States provisional patent application numbers 63 / 597,957 and 63 / 580,598, previously incorporatedherein by reference in their entireties. The base 311 may include a mast 31 IM along which the arm 312 traverses in the Z direction under impetus of any suitable motor / drive of the drive section 313D.

[0093] Referring to Figs. 1, 2, 3A and 3B, the automated laboratory system 100S includes three or more laboratory modules 110. The three or more laboratory modules 110 are selectable from a number of different interchangeable laboratory modules 110DILM (inclusive of but not limited to those modules 110A-110G described herein). The three or more laboratory modules 110 are selectable for installation to form the automated laboratory system 100S. It is noted that while three laboratory modules 110A-100C are illustrated in FIG. 1 there may be more or less than three laboratory modules 110. For example, FIG. 3 A illustrates a portion of the collaborative process facility 100 including four laboratory modules 110A-100D while FIG. 3B illustrates another portion of the collaborative process facility 100 including six laboratory modules 110A, I IOC- 110G.

[0094] Each of the laboratory modules 110 has a frame or enclosure 110FR that is self standing (e.g., self supporting). The enclosure 110FR provides for placement of the respective laboratory module 110 on a workbench 130, on the floor, or clustered on or adjacent another laboratory module 110.

[0095] Each of the laboratory modules 110 has a respective predetermined function characteristic (such as, but not limited to, those described herein) disposed so as to effect a respective predetermined sample process. It is noted that the predetermined function characteristic of at least one of the different laboratory modules 110, 110A-110G, 110DILM is different from another predetermined function characteristic of another of the different laboratory modules 110, 110A- 110G, 110DILM (generally referred to herein a laboratory module(s) 110). The enclosure 110FR forms closed bounds around (e.g., the predetermined sample process) so the respective sample process is compartmentalized therein (e.g., within the enclosure 110FR) with a sample loading and unloading opening 111 (in the example illustrated in FIG. 2 there are four sample loading andunloading openings 111 A- H ID disposed on the lateral sides LSD and longitudinal sides LSG of the enclosure 110FR however, in other aspects there may be more or less than four sample loading and unloading openings disposed on any suitable side (inclusive of top and bottom) of the enclosure 110FR).

[0096] The enclosure 110FR houses one or more of at least one object holding location 360, at least one robotic transport 370 (which may be a collaborative robotic transport), and at least one processing device 380 (e.g., automated pipettor, decapper, sealer, holding location, etc., which may be configured for operation in a collaborative environment) that at least in part define the predetermined function characteristic of the respective laboratory module 110.

[0097] Each of the at least one object holding location 360 is configured to hold at least one object 350 and may be configured with predetermined holding stations for holding respective objects 350 at a known location or an undeterministic support surface on which the objects are placed in variable positions (e.g., where the vision system 320V determines the pose and location of the objects 350 on the undeterministic support surface in a manner similar to that described in United States provisional patent application numbers 63 / 597,957 and 63 / 580,598, previously incorporated herein by reference in their entireties).

[0098] The at least one robotic transport 370 may be any suitable robotic transport including, but not limited to, robotic arms 370RA (similar to robotic transport 150) and gantries . The at least one robotic transport 370 is configured with a gripper 370G (see FIG. 8) so as to transport objects 350 such as sample containers 350C (e.g., tubes, vials, slides, well trays, etc.) and trays or racks 350T that hold the sample containers 350C. For example, the sample containers 350C may be transferred between other objects 350 (such as trays or racks 350T) and / or between trays or racks 350T and process stations 350P and / or between process stations 350P, in which case the robotic transport may be robotic transport 150 or 370. The trays or racks 350T may be transferred between the object holding location 360 and a process station 350P and / or between different object holding locations 360. The robotic transport 150 or 370 is configured to transfer the objects 350, 350C,350T within a respective laboratory module 110 and / or between adjacent laboratory modules along one or more of the process axes PX, PY, PZ. As an example, referring to FIG. 8, the at least one robotic transport 370 includes a frame 370F movably coupled to the enclosure 110FR of the respective laboratory module 110. A drive section 370D of the at least one robotic transport 370 is coupled to the frame 370F (and disposed at least partially on the enclosure 110FR of the laboratory module 110) so as to move the robotic transport 370 along the lateral and longitudinal directions LTD, LGD (relative to the enclosure 110FR) and in rotational direction RD about an axis of rotation AX of the at least one robotic transport (e.g., for changing a facing direction of a gripper 370G of the at least one robotic transport). The gripper 370G is movable in a Z direction by the drive section for picking and placing objects 350 where the gripper 370G may be actuable to grip and release the objects or pick and place operations. Here, the gripper 370G (and objects 350 carried thereby) are movable along one or more of the process axes PX, PY, PZ (see FIG. 2) of the respective laboratory module 110. The at least one robotic transport 370 may also include a machine vision system 370V substantially similar to machine vision system 320V so that the at least one robotic transport 370 or 150 is configured to determine the pose and location of object holding locations (e.g., of trays 350T, of other laboratory modules 110, or at any other suitable container 350C / tray 150T holding location), and in some aspects sample / container / tray identification, to effect picking and placing of the objects 350.

[0099] Referring to Figs. 1, 2, 3 A and 3B, each of the different laboratory modules 110 has a modular interface 110INT formed by the respective enclosure 110FR. The modular interface 110INT is configured to interface and connect three or more laboratory modules 110, selected for installation (e.g., so as to form the automated laboratory system 100S) to at least one other laboratory module 110 of the different and interchangeable laboratory modules 110DILM, so that the modular interface 110INT at least one of couples the three or more laboratory modules 110 and the at least one other laboratory module 110 to each other, and communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules 110 and the at least one other laboratory module 110 with each other. Coupling the threeor more laboratory modules 110 and the at least one other laboratory module 110 to each other provides for the formation of a cluster CL1, CL1’, CL2 (see FIG. 9) of laboratory modules 110. Communicating the compartmentalized predetermined sample process respective to the three or more laboratory modules 110 and the at least one other laboratory module 110 with each other provides for the passage of objects 350 between laboratory modules 110.

[0100] As an example, the modular interface 110INT is inclusive of (or at least formed in part by) one or more of a process path (e.g., along one or more process axes PX, PY, PZ) within, through, and / or between laboratory modules and at least one sample loading and unloading opening 111 of a laboratory module 110. For example, the modular interface 110INT includes at one or more of at least one sample loading and unloading opening 111 of the enclosure 110FR and one or more sides (e.g., one or more of a lateral side LSD, a longitudinal side LSG, a top side LST, and a bottom side LBT) of the enclosure 110FR. As can be seen in, at least, Figs. 3A and 3B, the top sides LST and / or bottom sides LBT of the laboratory modules 110A-110C and 110E-110G form respective modular interfaces that provide for the stacking (Z axis coupling or clustering) of the laboratory module 110A-100C and HOE- HOG enclosures 110FR in the exemplary manner illustrated in Figs. 3A and 3B. One or more of the lateral sides LSD and longitudinal sides LSG of the laboratory modules HOB, HOC, 110E, 110F, HOG form respective modular interfaces that provide for the end to end (e.g., longitudinal) coupling or clustering of the laboratory module 110B, HOC, 110E, 110F, HOG enclosures 110FR in the exemplary manner illustrated in Figs. 3A and 3B. See also FIG. 6, where the lateral sides LSD of three or more laboratory modules provide for lateral coupling or clustering of the laboratory module 110C, 110E-110G enclosures 110FR in the exemplary manner illustrated in Figs. 3A and 3B. It should be understood that the laboratory modules 110 may be clustered in / along one or more of the Z-axis, longitudinal, and lateral directions.

[0101] As can also be seen in, at least, Figs. 3A and 3B, the one or more sample loading and unloading opening 111 of the enclosure 110FR provides for communication of the compartmentalized predetermined sample process of one or more respective laboratory modules110 with one or more other laboratory modules 110. For example, with reference to Figs. 2 and 3A, the sample loading and unloading openings 111A, 111C (see FIG. 2) of laboratory modules HOB, HOC (see FIG. 3 A) provide for the communication of the compartmentalized predetermined sample process of laboratory module HOC with the compartmentalized predetermined sample process of laboratory module HOB along one or more of the process axes PX, PY, PZ, and vice versa such that objects 350 can be passed substantially directly (e.g., an internal transfer) between the laboratory modules 110B, 110C with automation of the (e.g., robotic transport 370) of one or more of the laboratory modules 110B, 110C. As may be realized, the respective sample loading and unloading openings 11 IB of the laboratory modules 110A-110D (see FIG. 3A) provide for the communication of the compartmentalized predetermined sample process of one or laboratory modules 110A-110D with the compartmentalized predetermined sample process of any other one or more of laboratory module 110A-110D, and vice versa such that objects 350 can be passed between the laboratory modules HOB, 110C along one or more of the process axes PX, PY, PZ by, for example, an automated (e.g., robotic transport 150) transfer and / or a human 160 (FIG. 1) transfer.

[0102] The modular interface 110INT of each laboratory module 110 may include any suitable wired or wireless couplings that communicably couples a module controller MC of a respective laboratory module 110 to one or more of: a respective module controller MC of one or more other laboratory modules 110 of the automated laboratory system 100S, one or more robotic transports 150 of the automated laboratory system 100S, analyzers 120, process stations 115, and a laboratory controller LC. It is noted that each modular interface 110INT is configured such that upon installation of a respective laboratory module 110 in the automated laboratory system 100S, the necessary communication connections (e.g., wired or wireless) between the module controllers MC, between the modular controllers MC and a common user interface UMC, between module controller MC and laboratory controller LC, etc. are substantially automatically established such that each laboratory module 110 is a plug-and-play module of the automated laboratory system 100S (i.e., each laboratory module 110 (and the components thereof) are automatically recognizedwithin the automated laboratory system 100S without the need for physical device configuration or user intervention in resolving resource (e.g., computing) conflicts). Communication between the module controllers MC and / or the robotic transports 150 may facilitate object 350 handoff between the laboratory modules 110 and / or between the laboratory modules 110 and one or more of the process stations 115 and analyzers 120, such that signals are sent between the module controllers MC, analyzers 120, and / or the robotic transports 150 where the signals embody an end of process that triggers the start of a next process, transfer of the object 350 between laboratory modules 150, and / or transfer of the object 350 between a laboratory module 150 and one or more of a process station 115 and analyzer 120.

[0103] As can be seen best in FIG. 1, each laboratory module 110 includes a respective module controller MC; however, in other aspects three or more laboratory modules 110 may share a common module controller MC. In some aspects, each laboratory module 110 includes a user interface UMC that provides a human-to-machine interface between the respective laboratory module 110 and the human 160 (see FIG. 1); however, in other aspects (such as illustrated in Figs. 4 and 5) three or more laboratory modules 110 may share a common user interface UMC. Each module controller MC is programmed (e.g., with any suitable non-transitory computer program code) so as to effect a respective predetermined function characteristic of the respective laboratory module 110.

[0104] One or more of the laboratory controller LC and the module controller MC may include any suitable control software 114 that employs, for example, a state machine configured to inform the human 160 (or other user, e.g., through a respective user interface ULC, UMC) of a process status and location of an object 350 within the respective laboratory module 110, and / or through communication with other module controllers MC of other laboratory modules 110, analyzers 120 and / or process stations 115, a process status and location of an object 350 within the automated laboratory system 100S. In some aspects, the state machine is similar to and is employed to generate a schedule for processing one or more objects 350 in a manner substantially similar to that described in United States patent number 8,473,270 issued on June 25, 2013 and titled“Methods and Systems for Controlling a Semiconductor Fabrication Process,” the disclosure of which is incorporated herein by reference in its entirety. For example, one or more of the laboratory controller LC and the module controller MC includes an object centric database DB, a real-time scheduler using a neural network NNS, and a graphical user interface ULC, UMC displaying a simulated operation of the automated laboratory system 100S. These features may be employed alone or in combination to offer improved usability and computational efficiency for real time control and monitoring of the processes performed by the components of the automated laboratory system 100S in the manner substantially similar to that described in United States patent number 8,473,270.

[0105] The control software 114 performs a variety of tasks associated with processing of objects within the automated laboratory system 100S (and the collaborative process facility 100). By way of example and not limitation, the control software 114 (e.g., of the laboratory controller LC) may control operation of one or more of the laboratory modules 110, the robotic transports 150, the process stations 115, the analyzers 120 and any other suitable processing equipment of the automated laboratory system(s) 100S of the collaborative process facility 100 (it is noted the module controller MC may include similar control software that controls the respective components of the laboratory module 110 in a manner similar to that described herein). Each of these hardware items may have any suitable control interface, and the control software 114 may also, or instead, manage communications with these hardware items, such as by interpreting data from the hardware or providing control signals to the hardware in a plug-and-play manner. At a more abstract level, the control software 114 may coordinate the various components of the automated laboratory system 100S to schedule processing of one or more objects, such as by coordinating and controlling operations of the laboratory modules 110, the robotic transports 150, the process stations 115, the analyzers 120 and any other suitable processing equipment of the automated laboratory system(s) 100S. The control software 114 may also provide an external programmatic interface (e.g., through the user interface ULC) for controlling the entire automated laboratory system 100S, and may also, or instead, provide information to a laboratory -widecomputer infrastructure, such as event logs, status information, and the like. As noted above, and described further herein, the control software 114 may employ a neural network to calculate weights for a finite state machine that controls process scheduling. The control software 114 may use data from or provide data to an object-centric database DB. The control software 114 may also provide a graphical user interface ULC for user interaction with the automated laboratory system 100S and related process data. More generally, the control software 114 may support any software functions associated with status, monitoring, maintenance, evaluation, programming, control, and / or operation of the automated laboratory system 100S, whether with respect to particular devices, the automated laboratory system 100S, or the collaborative process facility 100 of which the automated laboratory system 100 forms a part.

[0106] FIG. 10 shows a high-level software architecture for controlling operation of an automated laboratory system 100S. In general, the software 10200 (which is representative of control software 114) may include a number of laboratory module interfaces 10202, other hardware interfaces 10210 (such as of the analyzers 120, process stations 115, robotic transports 150, etc.), a controller 10220 including a hardware interface 10210 for integrating communications with the foregoing, a user interface component 10222, a scheduling / control component 10224, a diagnostics component 10226, and a laboratory facility interface 10230, and one or more databases maintained for facility-wide use, such as an object database 10242, and a records database 10244. It will be appreciated that the foregoing software components and the arrangement thereof as depicted in FIG. 10 has been generalized to facilitate discussion of the more specific systems described below, and that numerous variations are possible.

[0107] The laboratory module interfaces 10202 and the other hardware interfaces 10204 may be physical interfaces or programmatic interfaces resident on respective ones of the laboratory modules and other hardware. The interfaces 10202, 10204 may be wired or wireless and, as described herein, configured for plug-and-play connectivity.

[0108] The controller 10220 (which may form laboratory controller LC) may be an integrated controller for the automated laboratory system 100S. The controller 10220 may be embodied on a computer or workstation located physically near the system, or may be embodied in a remote computer located in a control room or other computer facility, or may be integrated into a laboratory -wide software system.

[0109] The hardware interface 10210 may provide a consistent internal interface for the controller 10220 to exercise programmatic control over inputs and outputs for the laboratory modules 110 and other hardware described herein.

[0110] Within the controller 10220, the user interface component 10222 may provide the user interface ULC for human 160 control and monitoring of operation of the automated laboratory system 100S. The user interface ULC, may include graphics, animation, simulations, manual control, recipe selection, performance statistics, and any other inputs or outputs useful for human control of the automated laboratory system 100S. It will be appreciated that a wide variety of interface techniques are known and may be usefully employed to provide any suitable graphical user interface, such interface techniques include network-oriented interface technologies such as web server technologies, as well as application-oriented interface technologies. Unless otherwise specified or clear from the context, all such technologies may be suitably employed with the systems and methods described herein.

[0111] The scheduling component 10224 processes recipes (e.g., process steps to be performed) for objects 350 within the automated laboratory system 100S. This may include scheduling movements of the objects 350 among laboratory modules 110, process stations 115, and / or analyzers 120 (and / or any other suitable object processing hardware), as well as processing within particular laboratory modules 110, process stations 115, and / or analyzers 120 (and / or any other suitable object processing hardware). The scheduling component 10224 may receive recipes in any suitable machine-readable form, and may create corresponding control signals for the automated laboratory system 100S. During execution, the control signals may be communicatedto system components through the hardware interface 10210. Recipes and other system control instructions may be received from a remote location such as a central laboratory control system through the collaborative process facility interface 10230, or may be entered locally at a computer device that operates the controller 10220.

[0112] Scheduling may be controlled in a number of different ways. For example, the scheduling component 10224 may employ state machines and neural networks as described herein. However, numerous other scheduling techniques are known in the art for minimizing or reducing processing time and cost, many of which may be usefully employed with the systems and methods described herein. For example, the system may employ rule-based scheduling, route-based scheduling, statebased scheduling, neural network-based scheduling, and so forth.

[0113] In one aspect, the scheduling component 10224 may permit selection of one or more of these various scheduling models to control operation of the automated laboratory system 100S. This may be presented, for example, as a user-selectable option in the user interface ULC. Once a scheduling technique is selected, a user may be prompted for any inputs such as rules, process steps, time constraints, and so forth. In other aspects, the selection of a scheduling technique controlled by the controller 10220 based upon, for example, optimization or other analysis of hardware connected to the hardware interface 10210 and / or any recipes scheduled for execution. Computerized selection of scheduling techniques may employ the creation and / or evaluation of one or more processing metrics such as an estimation of processing resources required, fault tolerance, throughput, or any other useful criteria with which automated selections of scheduling techniques may be objectively compared. In one or more aspects, the scheduling component 10224 may employ multiple scheduling techniques concurrently. While one example of this is the neural-network-weighted state machine described below, it will be appreciated that numerous other combinations may be usefully employed. For example, the scheduling component 10224 may use a state machine to control robotics, while rule-based scheduling is employed to control and optimize use of process equipment (e.g., laboratory modules 110, process stations 115, analyzers 120, etc.). All such variations are intended to fall within the scope of this disclosure.

[0114] The diagnostics component 10226 may monitor operation of the automated laboratory system 100S. This may include tracking scheduled maintenance as well as monitoring operation of the system to identify hardware failures and to determine, where possible, when failures are becoming more likely based upon current operation. One useful hardware diagnostics system is described, for example, in United States patent number 7,890,194 issued on February 15, 2011, the disclosure of which is incorporated by reference herein in its entirety.

[0115] Other components 10228 may include any other useful modules, executable files, routines, processes, or other software components useful in operating the controller 10220, and more generally, in controlling operation of the automated laboratory system 100S. This may include, for example, device drivers for controlling operation of hardware through the hardware interface 10210. This may also include database management software, communications protocols, and any other useful software components.

[0116] The controller 10220 may include a collaborative process facility interface 10230 that may provide an interface to other users within the collaborative process facility 100. This may include a number of different types of interfaces. For example, the collaborative process facility interface 10230 may include a programmatic interface that facilitates remote operation and control of the controller 10220. The collaborative process facility interface 10230 may also, or instead, include a web server for remote, web-based access to programs, data, and status information relating to the automated laboratory system 100S of the collaborative process facility 100. The collaborative process facility interface 10230 may also, or instead, include interfaces to other shared computing resources within the collaborative process facility 100 such as the object database 10242 (which may form the object centric database DB) and the records database 10244.

[0117] The object database 10242 may provide object-specific data that may include any useful data for an object such as location within the automated laboratory system 100S, processes performed, analytical results, etc. While depicted as a shared resource within a facility, it will be understood that the object database 10242 may also, or instead, include a database on the devicehosting the controller 10220. In such cases, the collaborative process facility 100 would preferably include an external interface to object data stored by the controller 10220.

[0118] The records database 10244 may store any information useful outside the scope of the controller 10220. This may include, for example event logs and the like from the controller 10220 as well as maintenance records and schedules (such as for the laboratory modules 110, robotic transports 150, processing stations 115, analyzers, etc.), processing recipes, user manuals, technical specifications, data schemas, programming guides, and any other data relevant to the automated laboratory system 100S of the collaborative process facility 100 or the software 10200.

[0119] As noted above, the foregoing description is generalized to facilitate discussion of more specific software systems disclosed herein. Unless otherwise indicated, the specific software components identified in FIG. 10 may reside in a single device or multiple devices, and may be centralized or distributed. Thus, for example, the laboratory module interfaces 10202 may be programming interfaces resident on associated laboratory modules, and may be accessed through the hardware interface 10210 of the controller 10220 for use in, e.g., scheduling or display. Alternatively, a laboratory module may not provide a programming interface, but may consist of physical connections controlled through one or more drivers in the hardware interface 10210. All such variations that may suitably employed in a software architecture for controlling a semiconductor fabrication facility are intended to fall within the scope of this disclosure.

[0120] FIG. 11 shows a state machine. It will be appreciated that the state machine 11400 of FIG. 11 is a highly simplified state machine, and that state machines used for real time control of an automated laboratory system process would typically be significantly more complex, having significantly more states and transitions than illustrated in FIG. 11.

[0121] The state machine 11400 may include a number of states including a first state 11402, a second state 11404, and a third state 11406. The states may represent, for example, the states of positions of a robotic arm (e.g., location x, y, z, etc.), status of an object holding location, liquidhandling device (e.g., dispensing or not) or any other state or combination of states in an automated laboratory system process. Each change from one state to another state occurs through a transition, such as a first transition 10410. It will be noted that each state may have one or more transitions into and out of that state. This may be, for example, a control signal or a sensor output that triggers a response by an item of hardware to transition to a different state.

[0122] It will be understood that while a simple finite state machine 10400 is depicted in FIG. 11, numerous other techniques can be employed to represent state machines. For example, a state machine may be fully represented by a state table that relates states and conditions in tabular form. In addition, various conceptual state machines use different models. For example, certain state machine models define binary conditions for transitions while others permit more generalized expressions for evaluating state changes. A so-called Moore machine has outputs that depend only on the current state, while a Mealy machine has state outputs that depend on an input and the state. Other commonly used representations for software implementations of state machines include algorithmic state machines, Unified Modeling Eanguage (“UME”) state diagrams, directed graphs, and so forth. These and other state machine modeling techniques may be usefully employed to characterize and control an automated laboratory system process.

[0123] FIG. 12 shows a neural network 500. It will be understood that the neural network 500 depicted in FIG. 12 is a generalized representation, and that the size and depth of a neural network 500 used to control an automated laboratory system process may vary significantly from this depiction.

[0124] The network 500 may include, for example, a three-layer network of objects 502. An input 504 may be applied to one of the objects 502 at the top level of the network 500 (e.g., the “input layer”) and an output 506 may be produced by one of the objects 502 at the output layer. Each of the objects 502 in this network 500 may contain any number of artificial neurons and objects. In general, there may be any number of objects 502 in the input layer, output layer, and middle layer. The number of objects 502 at the input layer 504 may correspond to the number of components508 of the input 504 (which may be a vector or the like) and the number of objects 508 at the output layer 506 may correspond to the number of components 508 in a target value vector, which is an output 506 used to train the network 500. Each component 508 may be a real value. The number of objects 502 in the middle layer may be, for example, the average number of objects 502 in the input and output layers. Each object 502 in one layer of the network may be fully connected to objects 502 of the adjacent layer or layers. In this way, the output from each and every object 502 in the input layer is provided as an input to each and every object 502 in the middle layer. Likewise, the output from each and every object 502 in the output layer of the middle layer is provided as an input to each and every object 502 of the output layer.

[0125] A process for creating the neural network 500 typically involves creating an array of objects 502. Each object 502 may have the ability to clone itself based on any useful process metric or other objective criteria as described in United States patent number 8,473,270, previously incorporated herein by reference. For example, a useful criterion may be derived from a physical and / or theoretical understanding of an environment, such as the processing time required to evaluate an input 504 to the network 500 based upon available processing resources. This criterion may have particular use where the neural network 500 is intended for use in real time control, thus imposing constraints such as completion of processing within 20 milliseconds or some other real time control time increment. In other words, where a system requires action within a known time interval, the network 500 may be configured to automatically add or remove objects (e.g., nodes) in order to ensure completion of any evaluation within the known interval, or alternatively to improve the likelihood of completion within the known interval. Thus where possible, the network 500 may automatically provide finer grained processing to more accurately represent the modeled environment.

[0126] The neural network 500 may be implemented according to an object-oriented programming paradigm. Within this, the objects 502 may be capable of propagating or cloning themselves according to one or more predetermined conditions. These actions may be conducted autonomously, by the individual objects 502. Thus, the neural network 500 may reconfigure itselfwithout manual intervention. In embodiments, the objects 502 may be represented in an array data structure, which may include singly -linked or doubly-linked lists that represent the tree structure or hierarchy of the neural network 500. The neural network 500 may include any number of tiers or layers. The objects 502 may be software objects as expressed in an object-oriented language or any other computer language. More generally, numerous programming techniques are known in the art for designing and implementing neural networks in software, and all such techniques may be suitably adapted to use with the systems and methods described herein, particularly techniques suitable for use in a real time control environment. It will be appreciated that the term “neural network” as used herein may refer to a conventional neural network or to a neural network that employs self-cloning nodes as described in greater detail below.

[0127] FIG. 13 shows a neural network providing weights to a finite state machine. In this control system 13600, handling hardware 13602 includes a plurality of robots 13604 (such as any of the robots described above). In general operation, output from the handling hardware 13602 provides inputs 13608 to a neural network scheduler 13610. The scheduler 13610 in turn calculates weights 13612 for one or more states 13614 of a finite state machine. These states, in turn, provide control signals to the robots 13604 and any other handling hardware 13602.

[0128] The inputs 13608 to the neural network scheduler 13610 may include any data derived from the handling hardware 13602, such as sensor data from optical sensors, pressure gauges, switches, and so forth. The inputs 13608 may also, or instead, include robotic data such as encoder data that indicates positions of a robotic drive or the robotic components attached thereto. The inputs 13608 may also, or instead, include processed sensor data. For example, a switch may detect whether a liquid dispensing pump is on or off, and the switch output signal may be converted into a Boolean representation of the liquid dispensing pump status. For example, an optical sensor and optical source may work together to provide an optical beam that is periodically broken by the passage of an object 350 there between. This data may be processed to capture the time of a transition from object presence to object 350 absence (or, conversely, wafer absence to wafer presence), and the transition type and time may be provided as an input 13608. Similarly, robotencoder data may be provided in raw form to the neural network scheduler 13610, or may be converted into physically meaningful values such as x, y, and z coordinates of an end effector. The inputs 13608 to the neural network scheduler may relate to a wide variety of system information such as a pick time, a device status, an object transition time, and so forth. More generally, the inputs 13608 may be any raw or processed data available from the handling hardware 13602.

[0129] It should be understood that the inputs 13608 may assume many forms. For example, the inputs 13608 may include vectors, real numbers, complex numbers, or the like. The data may be represented as integers, floating-point values, or any other numerical representation suitable for use with the neural network scheduler 13610. The inputs 13608 may be synchronous (i.e., a single vector provided at regular time intervals) or asynchronous 13608 (i.e., with signals arriving at various times from various hardware items within the handling hardware 13602).

[0130] The neural network scheduler 13610 may include any of the neural networks described above. In general, the neural network scheduler 13610 operates to process inputs 13608 and calculate weights 13612 used by a finite state machine. The neural network scheduler 13610 may drive calculations as far down a neural network as possible given a time constraint and a finite computing resource with which to process the neural network. For example, the scheduler 13610 may be dynamically adapted to update consistent with real time scheduling, or may be statically designed to ensure completion of calculations in time for real time control, according to the hardware and software platform supporting the scheduler 13610. Relative to the robots 13604 and the handling hardware 13602, the neural network scheduler 13610 may work off-line, updating the weights 13612 from time to time as the robots 13604 are more or less continuously operating based upon the finite state machine 13616 and transitions therein having the highest weight 13612 at the time.

[0131] The states 13616 of the finite state machine may employ any current value of the weights 13612 to determine whether a transition is appropriate, and generate any suitable control signalsto the robots 13604 and other handling hardware 13602. It will be understood that the state machine may employ multiple concurrent states, or the system 13600 may include multiple state machines (i.e., one state machine for each item of hardware, or for discrete groups of hardware), or the system may employ states with multiple outputs. While state machine modeling techniques are generally conceived to permit full description of any system, certain techniques may be more convenient for describing the handling hardware 13602 described herein. Thus, it will be appreciated that while any state machine design and programming techniques may be used, certain techniques may be advantageously employed in the context of real time control of automated laboratory systems 100S and the object handling / process systems thereof. The use of state machines to control automated laboratory systems 100S, and more generally the use of state machines in industrial control, are well known in the art.

[0132] FIG. 14 shows a process for controlling an automated laboratory system 100S with a finite state machine and a neural network.

[0133] A neural network 14710 receives data from the automated laboratory system 14730 (such as automated laboratory system 100S). These inputs are applied to the neural network 14710 as shown in step 14712. The neural network 14710 then processes nodes as shown in step 14714 to calculate outputs as shown in step 14716. The outputs may be weights for transitions of a state machine 14720. As noted above, a wide array of neural network and corresponding computing techniques may be employed. Where real time control or near real time control is desired, the neural network 14710 may be constrained so that updated outputs are provided within a predetermined time interval, such as every 20 milliseconds.

[0134] A finite state machine 14720 evaluates current states 14722 to determine whether to transition to another state as shown in step 14724, using the weights provided as outputs from the neural network 14710. If a transition is appropriate, the finite state machine 14720 proceeds to a new state as shown in step 14726 and generates corresponding control signals 14728 for output to the system 14730. If a transition is not appropriate, the finite state machine may return to re-evaluate the current state 14722, with corresponding control signals created as outputs to the system 14730. It will be appreciated that in control of the system 14730, states and transitions may each have numerous output control signals associated therewith. In a real time system, the control signals 14728 may be updated at a predetermined time interval such as every 20 milliseconds or less. It will be noted that the state machine 14720 may employ outputs from the neural network as well as physical data output from the system 14730.

[0135] As noted above, numerous state machine architectures may be employed with the systems described herein. For example, the weights may be values for conditional transitions. These weights may represent physical quantities conditionally applied to transitions such as time, position, and so forth. Similarly, the weights may represent Boolean values and / or expressions, as well as sensor data or any other scalar or vector quantities. In other embodiments, the weights may represent values assigned to a number of possible transitions from a state. In such aspects, and for exemplary purposes only, remaining in the current state may have a weight of 0.4, transitioning to another state may have a weight of 0.39, and transitioning to a third state may have a weight of 0.21. In this state, the state machine will remain in the current state indefinitely. However, if the weight of the current state drops to 0.35 and the weight of one of the other states rises to 0.4, then a transition will be initiated in the next processing cycle.

[0136] In other aspects, each state may have a number of possible transitions arranged as, for example, a stack or linked list of items each having one or more conditions for initiating a transition. The neural network 14710 may be employed to reorder the conditions according to an evaluation of the inputs from the system 14730, or to shift the linked list of items, so that one of the conditions is evaluated first. In such a system, the neural network 14710 may also reprioritize each condition independently and / or may add or remove conditions and / or may alter values used to evaluate each condition.

[0137] The automated laboratory system 14730 may receive the control signals created by the state machine 14720 in step 14728. As generally depicted in FIG. 14, the system 14730 mayexecute control signals continuously (step 14734), and may generate data output continuously (step 14732). It will be appreciated that the timing for these steps may be continuous or periodic and synchronous or asynchronous according to the hardware and sensors employed by the system 14730.

[0138] As a significant advantage the general architecture described above can separate processing that re-evaluates or reconfigures the state machine from the actual operation of the state machine. Thus, for example, the state machine may operate without input from the neural network indefinitely, providing conditional and / or unconditional transitions among states according to inputs from the physical system and generating corresponding control signals at any time interval suitable or desirable for controlling the system 14730. At the same time, the neural network 14710 may expend any appropriate amount of processing resources (e.g., by processing the neural network 14710 to any suitable depth) without requiring an update at the same time interval as the state machine 14720. In other words, the neural network 14710 may fully evaluate outputs even where the processing time extends over many time increments of the finite state machine. The neural network 14710 may also, or instead, curtail processing to provide updated outputs at each time increment of the state machine, at every other time increment of the state machine, or at any other suitable interval.

[0139] It will be appreciated that the foregoing description shows a neural network based scheduling system at a high level. It will also be understood that that other techniques may be employed to modify a state machine asynchronously. For example, the state machine may be reconfigured using heuristic techniques, rule -based techniques, look up tables, and / or any other processing techniques provided they do not prevent the state machine from continuing to provide substantially real time control of the system 14730. These and numerous other variations and modifications to the process 14700 will be readily appreciated by one of ordinary skill in the art and are intended to fall within the scope of this disclosure.

[0140] Referring again to Figs. 1, 2, 3A and 3B, the compartmentalized predetermined sample process of the selected three or more laboratory modules 110 (e.g., installed in the automated laboratory system 100S) defines a system sample process (e.g., of the automated laboratory system, that is a closed system process), and upon interface (e.g., of the selected three or more laboratory modules 110) with the at least one other laboratory module 110, the system sample process (e.g., automatically or manually) changes from a closed system process to an open system process. The closed system process is characterized by the compartmentalized predetermined sample process respective to the selected three or more laboratory modules 110. The open system process is characterized by a combination of the compartmentalized predetermined sample process respective to the selected three or more laboratory modules 110 and the at least one other laboratory module 110 interfaced with each other.

[0141] It is noted that the open system process changes upon interface of one or more other laboratory modules 110, from the number of different interchangeable laboratory modules 110DILM, to the selected three or more laboratory modules 110 (e.g., additional laboratory modules 110ADD (see FIG. 9) are added to an existing cluster CL1, CL2 of laboratory modules 110 to form a reconfigured cluster CLF where the interface / integration of the additional laboratory modules 110ADD into the existing cluster CL1, CL2 changes the open system process from a previous / original (before interface / integration of the additional laboratory modules) open system process to a reconfigured (after interface / integration of the additional laboratory modules) open system process that incorporates the respective predetermined function characteristics of the additional laboratory modules 110ADD). Conversely, the open system process changes upon deinterface (e.g., removal) of three or more laboratory modules 110 (i.e., from a cluster such as cluster CLF), from the number of different interchangeable laboratory modules 110DLIM, from the selected three or more laboratory modules 110 (e.g., removal of three or more laboratory modules 110ADD (see FIG. 9) from the cluster CL1’ of laboratory modules 110 forms (e.g., in this example reverts back to) the cluster CL1 where the removal of the additional laboratory modules 110ADD from the cluster CL1’ changes the open system process from, in this example,the reconfigured (here the original) open system process of the cluster CL1’ to, in this example, the original (here the reconfigured) open system process of the reconfigured cluster CL1).

[0142] It is also noted the open system process of a cluster CL1, CL2 of laboratory modules 110 changes upon interchange (e.g., exchanging) of one or more of the selected one or more (e.g., quasi-fungible) laboratory modules (e.g., having a first predetermined function characteristic) with a different one or more (quasi-fungible) laboratory module (e.g., having a second predetermined function characteristic different from the first predetermined function characteristic) from the number of different interchangeable laboratory modules 110DLIM. For example, referring to FIG. 9 and the cluster CL1, CLF, the decapping module 111A may be replaced with a similarly sized (e.g., quasi-fungible) sealer module 110B, thereby changing the open system process of the cluster CL1, CLF.

[0143] Each of the laboratory modules 110 includes at least one processing device 380 that defines the compartmentalized predetermined sample process of the laboratory module 110. For example, the compartmentalized predetermined sample process of the laboratory module 110 is the process performed by the processing device 380. The at least one processing device 380 includes, but is not limited to, one or more of a decapper device 380D (e.g., configured to remove a cap / lid from a sample container 350C), a sealer device 380S (e.g., configured to affix a seal on sample container 350C so as to seal the samples therein), an identification / reader device 3801 (e.g., configured to identify a sample and / or object 350 for effecting sample tracking and processing ), an aliquoting device 380A, a liquid handler 380L, storage device 380ST, a de-sealer device 380DS (e.g., configured to remove a seal from an object 350), a centrifuge / spinner 380C, feed device 380F (e.g., configured to automate the task of sorting, separating and feeding objects (e.g., empty objects 350) to automation), and / or any other suitable processing device configured to perform a pre- analytical operation or post-analytical operation on the sample / object 350.

[0144] Figs. 3B and 4 illustrate a laboratory module 110 configuration arranged for at least one pre-analytical operation where the objects 350 are at least partially prepared for analysis by at leastthe analyzer(s) 120 (FIG. 1). For example, FIG. 4 illustrates what may be referred to as a pre- analytical modular arrangement PRAMA that includes, for example, at least one sorting / transport module 110C and at least one decapper module 110H, 110G (see also FIG. 3B). FIG. 3B illustrates another pre-analytical modular arrangement PRAMA that includes, for example, at least one sorting / transport module HOC, 110F (see also FIG. 7), at least one storage module 110A, HOD, and at least one aliquoting / liquid handling module 110E (see also FIG. 7). It is noted that the pre- analytical modular arrangements PRAMA illustrated in Figs. 3B and 4 are exemplary only and in other aspects, any suitable combination of modules 110 may be grouped to form any suitable pre- analytical modular arrangement.

[0145] Figs. 3A and 5 illustrates a laboratory module 110 configuration arranged for at least one post-analytical operation where the objects 350 are at least partially post processed from analysis by the analyzer(s) 120. For example, FIG. 5 illustrates what may be referred to as a post-analytical modular arrangement PSAMA that includes, for example, at least one sorting / transport module HOC and at least one sealer module HOB. FIG. 3A illustrates another post-analytical modular arrangement PSAMA that includes, for example, at least one sorting / transport module HOC, at least one storage module 110A, HOD, and at least one sealer module HOB. It is noted that the post-analytical modular arrangements PSAMA illustrated in Figs. 3A and 5 are exemplary only and in other aspects, any suitable combination of modules 110 may be grouped to form any suitable post-analytical modular arrangement.

[0146] As noted above, referring to Figs. 3A, 3B, and 6, the laboratory modules 110 are quasi- fungible in terms of the space envelope occupied by the laboratory modules 110 (see for example the space envelope of the cluster CL1 of laboratory modules in FIG. 9). For example, one or more of the lateral dimension, longitudinal dimension, and / or height dimension of the different laboratory modules 110, 110A-110G is such that one or more of the laboratory modules 110 may be removed from post-analytical modular arrangement PSAMA and / or a pre-analytical modular arrangements PRAMA and replaced with one or more different (which alone or when grouped together are similarly dimensioned) laboratory modules 110 substantially without changing a space(e.g., footprint and / or volume) occupied by laboratory modules 110 in the post-analytical modular arrangement PSAMA and / or a pre-analytical modular arrangements PRAMA. Referring to the arrangement of FIG. 3B as an example, the laboratory modules 110 are configured so that, what may be referred to as base modules BM, are provided. Each base module BM may be formed of a single or multiple laboratory modules 110 and has dimensions (length and width) that define a floor space occupied by a cluster or group of laboratory modules 110. For example, the laboratory module 110A in FIG. 3B may be referred to as the base module BM for the group of laboratory modules GRP. Here, the laboratory module 110A has a longitudinal length EON and a lateral width EAT. Other of the laboratory modules 110 that are configured for clustering one on the other, have corresponding lateral widths LAT with varying longitudinal lengths LONB, LONC, LONE, LONF which when disposed longitudinally adjacent one another have the same length as the base module BM. For example, laboratory modules HOE, 110F have respective lengths LONE, LONF such that when the laboratory modules 110E, HOF are disposed longitudinally adjacent one another, the combined lengths LONE, LONF are substantially equal to the length LON of the base module BM. Similarly laboratory modules 110C, 110G have respective lengths LONC, LONB such that when the laboratory modules HOC, HOG are disposed longitudinally adjacent one another, the combined lengths LONC, LONB are substantially equal to the length LON of the base module BM. Here, the laboratory modules 110A, HOC, 110E-110G (and / or other modules of the number of different interchangeable laboratory modules 110DILM) may be stacked relative to one another in any suitable arrangement so long as the combinations of laboratory modules 110 on each stack level have a combined (or individual) length and width dimensions that are substantially the same as the base module BM length and width (e.g., the laboratory modules are quasi-fungible with respect to the space envelope occupied by the laboratory modules such that one or more of the laboratory modules may be removed from the cluster and replaced with a different one or more of the number of different interchangeable laboratory modules 110DILM with the footprint LON x LAT remaining constant).

[0147] As noted above, the base module BM may be defined by single laboratory module 110 (e.g., as illustrated in FIG. 3B) or the base module may be defined by more than one laboratory module 110 (e.g., such as illustrated in FIG. 6). For example, in FIG. 6, there are two rows RA, RB of laboratory modules 110. The modules HOC, HOF, HOC of the two rows RA, RB are arranged such that the combined longitudinal length of the laboratory modules 110 is referred to as the base module length LON and the combined lateral width of the laboratory modules 110 is referred to as the base module width LAT. Other of the number of different interchangeable laboratory modules 110DILM may be clustered in one or more of the two rows RA, RB in any suitable arrangement so that the footprint LON x LAT remains constant. The laboratory modules 110 are sized such that one or more of the laboratory modules may be removed from the cluster and replaced with a different one or more of the number of different interchangeable laboratory modules 110DILM with the footprint LON x LAT remaining constant.

[0148] Referring to Figs. 1, 2, 3A, 3B, 7, and 9, an exemplary method and operation of the automated laboratory system will be described. FIG. 9 illustrates a portion of the automated laboratory system 100S. In FIG. 9 the laboratory modules 110 have an arrangement similar to that illustrated in FIG. 3A (but may have any suitable arrangement such as those illustrated in Figs. 1, 3B or otherwise), where the laboratory controller LC is shown on workbench 130 for effecting control of the automated laboratory system 100S.

[0149] Here, three or more laboratory modules 110 are provided (FIG. 15, Block 1500). As described herein, the three or more laboratory modules 110 are selectable, for installation to form the automated laboratory system 100S, from a number of different and interchangeable laboratory modules 110DILM. Each of the three or more laboratory modules has a respective enclosure 110FR, a respective predetermined function characteristic, and a modular interface 110INT formed by the respective enclosure 110FR, as described herein.

[0150] The three or more laboratory modules 110, selected for installation, is / are interfaced and connected, via a respective modular interface 110INT, to at least one other laboratory module 110,of the different and interchangeable laboratory modules 110DILM (FIG. 15, Block 1510), so that the respective modular interface 110INT at least one of (s described herein): couples the three or more laboratory modules 110 and the at least one other laboratory module 110 to each other, and communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules 110 and the at least one other laboratory module 110 with each other; wherein the compartmentalized predetermined sample process of the selected three or more laboratory modules 110 defines a system sample process, and upon interface with the at least one other laboratory module 110, the system sample process changes from a closed system process to an open system process (as described herein).

[0151] As described herein, each of the laboratory modules 110 has a respective object workflow. The object workflow of each respective laboratory module 110 may be effected or otherwise controlled by system software (e.g., non-transitory computer program code) resident in the respective module controller MC (see FIG. 1). As noted herein, the system software of the module controller MC may be substantially similar to the state machine / neural network described herein, but for control of only the respective hardware components and holding locations of the respective laboratory module 110 for effecting the predetermined function characteristic of the respective laboratory module 110 (e.g., internal processing of objects 350), where an overall object workflow between the different laboratory modules and between the different laboratory modules and the other hardware of the automated laboratory system 100S is effected by the laboratory controller LC. In other aspects, the system software of the module controller MC and / or laboratory controller LC may be any suitable software for effecting processing of the objects 350 through the automated laboratory system 100S.

[0152] Objects 350 may be loaded into or removed from an object holding location 360 a laboratory module 110 (e.g., placed or picked) by one or more of the human 160 and the robotic transport 150. Where the robotic transport 150 is employed for picking and placing operations, the object holding locations 360 and / or the objects 350 include respective targets 9200, where the targets 9200 include at least machine-readable indicia that identifies a respective object holdinglocation 360 or object 350. In some aspects, the targets 9200 may also include human readable indicia that identifies a respective object holding location 360 or object 350.

[0153] As can be seen in Figs. 3A, 3B, 7, and 9, the objects 350 may be arranged within a laboratory module 110 (or on a workbench 130) in one or more of a horizontal array and a vertical array. In other aspects, the objects 350 may not be disposed in an array and may be singularly presented (see FIG. 9, such as an object 350 being placed on a workbench 130 for human 160 processing).

[0154] Referring also to Figs. 16-20, in some aspects, each of the objects 350 includes thereon a respective target 9200 (see FIG. 9); while in other aspects, each object holding location 360 of the laboratory module 110 (or workbench 130) has a respective target 9200 associated therewith (e.g., as illustrated in FIG. 9). The target 9200 may be any suitable target affixed to the object 350 and / or object holding location 360 in any suitable manner or integrally formed (e.g., as a one-piece unit) with the object 350 and / or object holding location 360. The target 9200 is disposed on the object 350 and / or object holding location 360 at a known location (e.g., with respect to a respective object and / or one or more respective holding location(s)) so that with location determination of the target 9200, a location of a pick / gripper interface of the object 350 and / or a location of the object holding location 360 is coincidentally determined. As may be realized, each of the targets 9200 may be individually identifiable, such that identification of the target 9200 may also identify the object 350 and / or object holding location 360 (e.g., for tracking / logging predetermined characteristics (e.g., processes completed, lot number, etc.) of the object 350 in any suitable manner such as with an object lookup table OLT (see FIG. 1, which may be part of the object centric database DB) stored in a memory of or accessible to the laboratory controller LC).

[0155] As described herein, the robotic transport 150 includes the end effector 340 coupled to the arm 312, where the end effector 340 is configured to grip the object 350 for transport of the object 350 from / to a pick location and / or a place location (see Figs. 3A, 3B, and 9). The robotic transport 150 also includes the machine vision system 320V with at least one two-dimensional or three-dimensional imaging sensor or imager 320, which in the examples described herein is coupled to or embedded in the end effector 340, but in other aspects may be coupled to any suitable portion of the arm 312. The at least one imager 320 is fixedly mounted on the end effector 340 in predetermined relation to the gripper 340G of the end effector 340 (e.g., the at least one two- dimensional imaging sensor 320 has a predetermined pose with respect to a predetermined reference datum (e.g., such as to the tool center point TCP) of the end effector 340 - see FIG. 3B). The at least one imager 320 is orientated so as to view (e.g., along a direction of motion described by the at least one degree of freedom - a direction of motion along one or more of the axes BX, BY, BZ, BXR, BYR, BZR - see Figs. 3B and 16) at least one predetermined target 9200 (e.g., on an object holding location, such as those object holding locations 360 described herein or an object 350) of the machine vision system 320V along a direction of motion described by the at least one degree of freedom (e.g., a direction of motion along one or more of the axes BX, BY, BZ, BXR, BYR, BZR). The image sensor or imager 320 may be mounted to the end effector 340 at an angle to the gripper 340G. The angle may be about 180 degrees such that the image sensor or imager 320 can be used whilst carrying a load. In other embodiments the angle may be about 90 degrees (when mounted on the side of the end effector 340, for example) or about 0 degrees (when mounted on the front of the end effector 340). Any other angle between 0 degrees and 360 degrees is contemplated dependent on the spatial relationship between the end effector 340 and image sensor or imager 320. For exemplary purposes, the end effector 340 includes a horizontal imager 320A and a vertical imager 320B as illustrated in FIG. 3B, but in other aspects the imager may have any suitable number of imagers facing any suitable directions arranged along any suitable axis / axes of motion.

[0156] Each of the at least one imager 320 has an imager reference frame CX, CY, CZ (see FIG. 16), and with the at least one imager 320 coupled to the end effector 340, the imager reference frame CX, CY, CZ has a known predetermined spatial relationship with, for example, the tool center point TCP of the end effector 340 (i.e., so as to establish the predetermined relation therebetween - see FIG. 3B). The tool center point TCP (FIG. 3B), as is known in the art, has aknown relationship with the hot (robotic transport) reference frame throughout a working envelope of the robotic transport 150. As such, given the known position of the tool center point TCP and the known predetermined spatial relationship between the imager reference frame and the tool center point TCP, a location of a feature imaged by the at least one imager 320 and identified in the imager reference frame may be translated to the bot reference frame by employing any suitable trigonometric (or other) transformations.

[0157] While the at least one imager 320 is described herein as being coupled to or embedded in the end effector 340, in other aspects, the at least one imager 320 may be disposed at any suitable known location (effecting feature location translation from the imager reference frame to the bot reference frame) of any suitable portion of the robotic transport 150, so long as the at least one imager 320 is able to be moved a predetermined distance for effecting stereo imaging of the target 9200 in a manner similar to that described in United States provisional patent application number 63 / 580,598 filed on September 5, 2023, titled “Method for Single Imager Stereoscopic Calibration and Processing Apparatus Including the Single Imager,” and having attorney docket number 390P017089-US (-#1), the disclosure of which was previously incorporated herein by reference in its entirety.

[0158] The laboratory controller LC is communicably connected to the imager 320, of the machine vision system 320V, in any suitable manner such as through one or more of a wired and wireless connection. The laboratory controller LC (or a vision controller LCV thereof) is programmed with a stereoscopic imager model or calibration correlation map SCM that correlates synthetic stereo image data (e.g. obtained from respective pairs of stereo images obtained by but one (i.e., a single one) of the at least one imager 320), registered on (e.g., obtained by) but one of the at least one imager 320, with a calibrated predetermined three-dimensional pose of a calibration object with calibration array features (e.g., as described in United States provisional patent application number 63 / 580,598 filed on September 5, 2023, the disclosure of which is incorporated herein by reference in its entirety) characterizing the predetermined three-dimensional pose of the calibration object and registered with synthetic stereo image data by the at least one imager 320. The synthetic stereoimage data embodies a three-dimensional (e.g., six degree of freedom TX, TY, TZ, TXR, TYR, TZR) pose of at least one calibration target or at least one target 9200 (see FIG. 16).

[0159] The laboratory controller LC is configured (e.g., as described in United States provisional patent application number 63 / 580,598 filed on September 5, 2023, the disclosure of which is incorporated herein by reference in its entirety) to determine the three-dimensional pose of the at least one predetermined target 9200 from but the calibration correlation map SCM and the synthetic stereo image data of the at least one predetermined target 9200 registered on the but one of the at least one imager 320. The laboratory controller LC is arranged to automatically teach the robotic transport 150 or automated laboratory system 100S (in which the robotic transport 150 resides) a teaching position from the three-dimensional pose, of the at least one predetermined target 9200 (the teach position may be the coordinate origin location and orientation of a target reference frame a respective target 9200), determined from but the synthetic stereo image data registered on the but one imager 320, where (as described in United States provisional patent application number 63 / 580,598) the calibration correlation map SCM is generated with at least one of the at least one imager 320, and the machine vision system 320V and the robotic transport 150 (or automated laboratory system 100S) being one or more of disassociated from and ex-situ the base 311 of the robotic transport 150 (as described herein and in United States provisional patent application number 63 / 580,598 and 63 / 597,957, calibration of the vision system can be effected in a non-production / non-processing workspace disassociated from and ex-situ the base 311).

[0160] Referring to, for example, Figs. 1, 2, 3A, 3B, and 16, the at least one imager 320 may be any suitable imager including but not limited to CCD (charge coupled device) and CMOS (complementary metal oxide semiconductor) imagers. The at least one imager 320 is calibrated for synthetic stereoscopic (e.g., three-dimensional) imaging where the single one of the at least one imager 320 generates a pair of stereo images 16500 containing one or more vision targets (referred to herein as targets) 9200 of the vision system 320V, and identifies (e.g., with a vision controller LCV - which may be a part of the laboratory controller LC) of at least one two-dimensional pixel value in each of the images 16500A, 16500B of the pair of stereo images 16500. In the example illustrated in FIG. 16, the two-dimensional pixel value CXI, CY 1 is obtained (e.g., such as by the vision controller LCV using any suitable image analysis algorithm) from image 16500A and the two-dimensional pixel value CX2, CY2 is obtained (e.g., such as by the vision controller LCV using any suitable image analysis algorithm) from the image 16500B. From the two-dimensional pixel values CXI, CY 1 and CX2, CY2, the vision controller LCV determines the three-dimensional position of the target 9200 as an offset from the tool center point TCP. Here, the laboratory controller LC determines a relationship between the two-dimensional pixel values CXI, CY 1 and CX2, CY2 and the three-dimensional position of the target 9200 as an offset ABX, ABY, ABZ from the imager reference frame (i.e., an origin of the imager reference frame) in the bot reference frame (e.g., in the robotic transport space) for automatically teaching the robotic transport 150 the location of the target(s) 9200 and the locations of the object holding (e.g., pick / place) locations 360 associated with the target(s) 9200. For example, the object holding locations 360 may be disposed on the workbenches 130 and / or laboratory modules 110. As an example, Each (or one or more) of the workbenches 130 and / or laboratory modules 110 includes at least one target 9200 that is disposed in a predetermined spatial relationship with respect to the object holding locations 360 of the respective workbenches 130 and / or laboratory modules 110. The predetermined spatial relationship between the target(s) 9200 and the object holding locations 360 for a workbenches 130 and / or laboratory modules 110 may be stored in a memory of or accessible to the laboratory controller LC so that with the location of the target(s) 9200 known to the laboratory controller LC, the location of the associated object holding locations 360 is / are also known. It is also noted that the targets 9200 of the respective workbenches 130 and / or laboratory modules 110 may also be arranged in unique patterns / locations relative to one another so as to identify the workbenches 130 and / or laboratory modules 110 to which they are coupled. As such, processing of the objects 350 may be tracked by the laboratory controller LC based on, for example, an identity of the workbenches 130, object holding locations 360, and / or laboratory modules 110.

[0161] Each of the one or more targets 9200 may be any suitable target having a two-dimensional pattern configured for determining, with specificity, characteristics of the respective fiducial, where such characteristics include one or more of, but are not limited to, size, corner points, and identity so that when imaged at least one two-dimensional pixel value is obtained from the target 9200, 9200C. Suitable examples of targets 9200, 9200C include, but are not limited to Stag fiducial markers, ArUco fiducial markers, CALTag fiducial markers, Fourier Tags, AprilTag fiducial markers, UPC Code, Code 25, Code 128, Code 39, Code 93, Codebar (Codabar), EAN_8, EAN_13, QR Code, Data Matrix, PDF_417, Aztec, Databar, Patch_Codes, and ARToolKit markers. For purposes of description, and for example only, the target(s) 9200, 9200C are illustrated and described herein as ArUco markers having four corners, the two-dimensional pixel values of which can each be identified using any suitable algorithms such as those provided by OpenCV®.

[0162] Where more than one target 9200 is provided, the targets 9200 may be provided in any suitable array or board 17222, an example of which is illustrated in FIG. 17. The array 17222 is illustrated in FIG. 17 as a 10 x 16 array however; the array 17222 may have any suitable dimensions. For example, the number of rows may be more or less than 10 and the number of columns may be more or less than 16. It is noted, with respect to teaching of one or more locations to the robotic transport 150 or automated laboratory system 100S, increasing the number of targets 9200 increases the number of data points obtained in each image (where using the ArUco for exemplary purposes only, four data points are obtained for each ArUco), where the increased number of data points may speed up the teaching process compared to teaching with fewer data points.

[0163] The array 17222 dimensions and individual target 9200 size may depend on a size of the working range (e.g., workspace, defined by a workbench 130 and / or three or more laboratory modules 110) so that a majority of the targets 9200 are within the imager 320 field of view (i.e., the field of view is filled with the targets 9200) when the at least one imager 320 / robotic transport 150 is within the workspace. As an example, the larger the workspace, the larger the individualtarget size and the smaller the workspace, the smaller the individual target size. Also, the smaller the imager field of view, the smaller the individual target size and the larger the imager field of view, the larger the individual target size. For exemplary purposes, each target 9200 may have a size that is about 50 pixels to about 200 pixels (e.g., with respect to the imager 120 resolution) along any one or more of the axes TX, TY (i.e., referring to FIG. 6, the length LX may be about 50 pixels to about 200 pixels and the length LY may be about 50 pixels to about 200 pixels), although in other aspects, the size of the target 9200, 9200C may be less than about 50 pixels or greater than about 200 pixels along any one or more of the axes TX, TY so as to be commensurate with a desired pose definition.

[0164] The location teaching described herein, may be performed with but a single target 9200 or an array of two or more targets 9200, where the single target 9200 or the array of two or more targets 9200 provide a suitable number of data points (e.g., two or more) for localizing (e.g., location / position and pose / orientation) the target(s) 9200 within the imager reference frame. It is noted that to increase the number of data points obtained from the single target 9200 or the array of two or more targets 9200, the robotic transport 150 may be commanded to move (e.g., closer or further away, laterally, vertically, etc. - so that more or less of the targets and data points are within the imager field of view) the imager 320 relative to the target(s) 9200 where the target(s) 9200 are imaged at each of the imager locations.

[0165] Referring to Figs. 1, 3A, 3B, 9, 16, and 18, to identify an object 350 and the location of the object 350, the object 350 is transported to the workspace of the robotic transport 150 (FIG. 18, Block 18700) manually or with automation. With the object 350 in the workspace, the robotic transport 150 is moved so that object 350 and / or the respective target 9200 is within a field of view of the imager 320 (FIG. 18, Block 18710). The at least one imager 320 is employed to capture one or more stereo images (similar to images 16500A, 16500B of image pair 16500) of the object 350 and / or the respective target 9200 (FIG. 18, Block 18720) in the manner described herein (see FIG. 16). For example, if the at least one imager 320 is not within an optimal workspace area (e.g., such as an area within the workspace where the images are the sharpest), the laboratorycontroller LC commands movement of the end effector 340 of the robotic transport 150 so that the at least one imager 320 is placed at a location where the image of the object 350 and / or target 9200 is the sharpest. Such movement of the end effector 340 may be effected with any suitable known image analysis algorithm (i.e., stored in and configuring the laboratory controller LC or vision controller LCV) that optimizes the sharpness of the captured images. With the at least one imager 320 within the optimal workspace area, a first image 16500 A of the stereo image 16500 is obtained, the robotic transport 150 is moved so that the at least one imager 320 is shifted (e.g., the commensurate move is performed) in, for example the BX-B Y plane or in the BY -BZ plane in a manner similar to that described herein with respect to FIG. 16, and a second image 16500B of the stereo image 16500 is obtained. The two dimensional pixel values CXI, CY 1 and CX2, CY2 (e.g., target pixel values) are obtained from the image pair (i.e., images 16500A, 16500B) of the stereo image 16500 (FIG.18, Block 18730). The laboratory controller LC (or vision controller LCV) employs the stereoscopic imager model SCM to estimate the values for AR, AZ, AT and locate the target 9200 (and the object 350) in the imager reference frame (FIG. 18, Block 18740), such as in a manner similar to that described in United States provisional patent application number 63 / 580,598 filed on September 5, 2023, the disclosure of which was previously incorporated herein by reference in its entirety. The values AR, AZ, AT are the imager 320 extrinsic parameters where, referring also to FIG. 19, the extrinsic parameter AR is the distance between the imager 320 center and the calibration target 9200C in the BX-BY plane defined by the BX and BY axes. The extrinsic parameter AZ is the distance between the imager 320 center and the calibration target 9200C along the BX axis. The extrinsic parameter AT is the planar angle in the BX-BY plane between a line (i.e., that connects the imager 320 center and the calibration target 9200C) and the direction in which the imager 320 is facing. The imager extrinsic parameters AR, AZ, AT are obtained from the known spatial relationship between the imager 320 reference frame and the tool center point TCP (see FIG. 3B) and the known spatial relationship between the tool center point TCP and the calibration targets 9200C. With the values AR, AZ, AT to the target 9200 (and the object 350) known in the imager reference frame, the location of the target 9200 (and object 350) is converted to the bot reference frame (FIG. 18, Block 18750) in any suitable manner such as withany suitable trigonometric transformations. With the location of the target 9200 known in the hot reference frame (and via localization of the target 9200, the location of the object 350 and / or object holding location 360 is coincidentally known), the laboratory controller LC commands movement of the robotic transport 150 to pick the object 350 (given the known spatial relationship between the target 9200 and the gripper interface of the object 350 and / or the object holding location 360, where the gripper interface is any suitable interface of the object 350 (e.g., one or more sides of the object 350, a kinematic gripping feature, a protrusion, a recess, a cap of a sample tube, a cover of a tray, etc.).

[0166] While the above object 350 and object holding location 360 determination is described with respect to the robotic transport 150, it should be understood that the robotic components internal to the laboratory modules 110 (e.g., such as robotic transports 370) may determine the pose and location of objects 350 and object holding locations 360 in a substantially similar manner.

[0167] Referring to Figs. 1, 2, and 7-9, with the robotic transports 150, 370 able to determine the pose and location of the objects 350 and object holding locations 360 (as described above), collaborative processing of the objects 350 in the automated laboratory system 100S may be effected. Objects 350 may be transported to the laboratory modules 110 by the human 160 and / or the robotic transport 150 for effecting one or more of pre-analytical and post-analytical processes (such as those described herein) on the objects 350. To effect the pre-analytical and post-analytical processes the objects 350 may be transported between two or more laboratory modules 110 in the same and / or different cluster CL1, CLF, CL2 of laboratory modules. Here, each laboratory module 110 has a respective workflow axis / axes (e.g., process axes PX, PY, PZ) along which objects 350 move and are processed within the laboratory module 110. The respective modular interface 110INT of the laboratory module 110 forms a multi-axis interface for the input and / or output of objects 150 at one or more sides of the laboratory module 110 for transport of objects between laboratory modules 110 (e.g., each of the selected laboratory modules 110 has the multiaxis interface that is configured to effect transfer of objects 350 between laboratory modules 110by one or more of transferring the objects 350 between the laboratory modules 110 internal to the respective enclosures 110FR and external to the respective enclosures 110FR).

[0168] As described herein, each laboratory module 310 includes sample loading and unloading openings 111A-111D (shown on the vertically orientated sides of the laboratory module for exemplary purposes but in other aspects sample loading and unloading openings may also be provided on the top and / or bottom side of the laboratory module). Where, the modular interface 110INT communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules 110 and the at least one other laboratory module 110 with each other, adjacent openings of adjacent laboratory modules 110 provide for an internal input / output for the respective laboratory module 110 along, for example, one or more process axes PX, PY (and in some aspects PZ, as noted herein) in directions O Y 1 , O Y2, OX 1 , OX2 (and in some aspects OZ1, OZ2, see FIG. 2). For example, as can be seen in Figs. 2, 7, and 8, the laboratory modules 11 OF, HOE are longitudinally interfaced so that the opening 111A of laboratory module 11 OF is adjacent to and communicates with the opening 111C of laboratory module HOE. Here, the robotic transport 370 of laboratory module 11 OF is configured (e.g., for movement in lateral and longitudinal directions LTD, LTG and in rotational direction RD) to extend through the adjacent openings 111 A, 111C for transporting, in this example, containers 350C between holding locations 360 (e.g., wells in the trays 350T) within laboratory module 110F and holding locations 360 (e.g., grippers of rotary table) within laboratory module 110E. As another example, referring to FIG. 6, internal input / output for each laboratory module 110C, 110E, 110G may be longitudinally along a respective row RA, RB (i.e., along process axis PX) and / or laterally between rows RA, RB (i.e., along process axis PY).

[0169] The sample loading and unloading openings 111A-111D of a laboratory module 110 that are not interfaced with an adjacent laboratory module 110 may provide for an external input / output for the respective laboratory module 110 along, for example, one or more process axes PX, PY (and in some aspects PZ, as noted herein) in directions OY1, OY2, OXI, OX2 (see FIG. 2). As can be seen in Figs. 2 and 9, at least the lateral sides LSD of the laboratory modules 110 are notinterfaced with an adjacent laboratory module, so as to allow human 160 and robotic transport 150 external input / output access to the interior of the respective enclosures 110FR through, at least, opening 11 IB of the respective enclosure 110FR along a respective process axis PY (e.g., at least one axis of the multi-axis interface is a collaborative workspace interface). The openings 111A, 111C on the longitudinal ends of the respective cluster of laboratory modules may also provide for external input / output access to the interior of the respective enclosures 110FR along a respective process axis PX. Here, the external input / output provides for human 160 and / or robotic transport 150 transfer of objects 350 between laboratory modules 310 of the same or a different cluster CL1, CL2 of laboratory modules 110 and / or transfer of objects between laboratory modules 310 and one or more of the workbenches 130, process stations 115, analyzers 120, and any other suitable processing equipment of the automated laboratory system 100S

[0170] The following aspects of the present disclosure are provided and may be employed individually, in any combination with each other, and / or in any combination with the features described above.

[0171] In accordance with aspects of the present disclosure an automated laboratory system includes: three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules, each of the three or more laboratory modules has: a respective enclosure that is self-standing, and a respective predetermined function characteristic disposed so as to effect a respective predetermined sample process, the enclosure forming closed bounds around so the respective sample process is compartmentalized therein with a sample loading and unloading opening, wherein the predetermined function characteristic of at least one of the different laboratory modules is different from another predetermined function characteristic of another of the different laboratory modules; and each of the different laboratory modules has a modular interface formed by the respective enclosure, the modular interface being configured to interface and connect the three or more laboratory modules, selected for installation, to at least one other laboratory module, of the different and interchangeable laboratory modules, so that the modular interface at least one of:couples the three or more laboratory modules and the at least one other laboratory module to each other, and communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules and the at least one other laboratory module with each other; wherein the compartmentalized predetermined sample process of the selected three or more laboratory modules defines a system sample process, and upon interface with the at least one other laboratory module, the system sample process changes from a closed system process to an open system process.

[0172] In accordance with aspects of the present disclosure the closed system process is characterized by the compartmentalized predetermined sample process respective to the selected three or more laboratory modules.

[0173] In accordance with aspects of the present disclosure the open system process is characterized by a combination of the compartmentalized predetermined sample process respective to the selected three or more laboratory modules and the at least one other laboratory module interfaced with each other.

[0174] In accordance with aspects of the present disclosure the open system process changes upon interface of one or more other laboratory modules, from the number of different interchangeable laboratory modules, to the selected three or more laboratory modules.

[0175] In accordance with aspects of the present disclosure the open system process changes upon de -interface of three or more laboratory modules, from the number of different interchangeable laboratory modules, from the selected three or more laboratory modules.

[0176] In accordance with aspects of the present disclosure the open system process changes upon interchange of one or more of the selected three or more laboratory modules with a different one or more laboratory module from the number of different interchangeable laboratory modules.

[0177] In accordance with aspects of the present disclosure the selected three or more laboratory modules forms a cluster of laboratory modules having a predetermined spatial footprint, and the number of different and interchangeable laboratory modules are quasi-fungible with respect to the predetermined spatial footprint.

[0178] In accordance with aspects of the present disclosure the selected three or more laboratory modules forms a cluster of laboratory modules, each of the three or more selected laboratory modules having a multi-axis interface configured to effect transfer of objects between laboratory modules by one or more of transferring objects between the laboratory modules internal to the respective enclosures and external to the respective enclosures.

[0179] In accordance with aspects of the present disclosure the automated laboratory system further includes a robotic transport external to the three or more laboratory modules, the robotic transport being configured to interface with each module of the cluster of laboratory modules through the multi-axis interface and effect the external transfer of objects between two or three of the three or more selected laboratory modules and to and from the three or more selected laboratory modules.

[0180] In accordance with aspects of the present disclosure at least one axis of the multi-axis interface is a collaborative workspace interface.

[0181] In accordance with aspects of the present disclosure a method for an automated laboratory system is provided, the method includes: providing three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules, each of the three or more laboratory modules has: a respective enclosure that is self-standing, a respective predetermined function characteristic disposed so as to effect a respective predetermined sample process, the enclosure forming closed bounds around so the respective sample process is compartmentalized therein with a sample loading and unloading opening, and a modular interface formed by the respective enclosure, wherein the predeterminedfunction characteristic of at least one of the different laboratory modules is different from another predetermined function characteristic of another of the different laboratory modules; and interfacing and connecting the three or more laboratory modules selected for installation, via a respective modular interface, to at least one other laboratory module, of the different and interchangeable laboratory modules, so that the respective modular interface at least one of: couples the three or more laboratory modules and the at least one other laboratory module to each other, and communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules and the at least one other laboratory module with each other; wherein the compartmentalized predetermined sample process of the selected three or more laboratory modules defines a system sample process, and upon interface with the at least one other laboratory module, the system sample process changes from a closed system process to an open system process.

[0182] In accordance with aspects of the present disclosure the closed system process is characterized by the compartmentalized predetermined sample process respective to the selected three or more laboratory modules.

[0183] In accordance with aspects of the present disclosure the open system process is characterized by a combination of the compartmentalized predetermined sample process respective to the selected three or more laboratory modules and the at least one other laboratory module interfaced with each other.

[0184] In accordance with aspects of the present disclosure the open system process changes upon interface of one or more other laboratory modules, from the number of different interchangeable laboratory modules, to the selected three or more laboratory modules.

[0185] In accordance with aspects of the present disclosure the open system process changes upon de -interface of three or more laboratory modules, from the number of different interchangeable laboratory modules, from the selected three or more laboratory modules.

[0186] In accordance with aspects of the present disclosure the open system process changes upon interchange of one or more of the selected three or more laboratory modules with a different one or more laboratory module from the number of different interchangeable laboratory modules.

[0187] In accordance with aspects of the present disclosure the selected three or more laboratory modules forms a cluster of laboratory modules having a predetermined spatial footprint, and the number of different and interchangeable laboratory modules are quasi-fungible with respect to the predetermined spatial footprint.

[0188] In accordance with aspects of the present disclosure the selected three or more laboratory modules forms a cluster of laboratory modules, each of the three or more selected laboratory modules having a multi-axis interface configured to effect transfer of objects between laboratory modules by one or more of transferring objects between the laboratory modules internal to the respective enclosures and external to the respective enclosures.

[0189] In accordance with aspects of the present disclosure the method further includes interfacing a robotic transport, disposed external to the three or more laboratory modules, with each module of the cluster of laboratory modules through the multi-axis interface and effecting, with the robotic transport, the external transfer of objects between the two or three of the three or more selected laboratory modules and to and from the three or more selected laboratory modules.

[0190] In accordance with aspects of the present disclosure at least one axis of the multi-axis interface is a collaborative workspace interface.

[0191] It should be understood that the foregoing description is only illustrative of the aspects of the present disclosure. Various alternatives and modifications can be devised by those skilled in the art without departing from the aspects of the present disclosure. Accordingly, the aspects of the present disclosure are intended to embrace all such alternatives, modifications and variances that fall within the scope of any claims appended hereto. Further, the mere fact that different features are recited in mutually different dependent or independent claims does not indicate that acombination of these features cannot be advantageously used, such a combination remaining within the scope of the aspects of the present disclosure.

Claims

CLAIMS:

1. An automated laboratory system comprising: three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules, each of the three or more laboratory modules has: a respective enclosure, and a respective predetermined function characteristic disposed so as to effect a respective predetermined sample process, the predetermined function characteristic of at least one of the three or more laboratory modules being different from another predetermined function characteristic of another of the three or more laboratory modules, wherein each of the respective enclosures forms one or more spaces allowing passage of objects therethrough so as to allow the generally lateral transfer of an object into, out of, or between two of the three or more laboratory modules.

2. The automated laboratory system of claim 1 , wherein the one or more spaces allow passage of objects to and from a space external to the enclosure, the space not being within an enclosure of another of the three or more laboratory modules.

3. The automated laboratory system of claim 1 or claim 2 comprising a robotic transport configured to transfer an object into, out of, or between two of the three or more laboratory modules.

4. The automated laboratory system of claim 3, wherein the one or more spaces allows for the passage of at least a portion the robotic transport therethrough.

5. The automated laboratory system of claim 3 or claim 4, wherein the robotic transport is separate from, or is not contained within, the three or more laboratory modules.

6. The automated laboratory system of any one of claims 3 to 5, wherein the robotic transport comprises a member configured to pass through the one or more spaces so as locate an object alternately internal and external to the respective enclosure.

7. The automated laboratory system of claim 6 wherein the member is part of an articulated or non-articulated arm.

8. The automated laboratory system of any one of claims 3 to 7, wherein the robotic transport is configured to transport an object along one, two or three axes of one, two or three of the three or more laboratory modules.

9. The automated laboratory system of any one of claims 3 to 8, wherein the robotic transport is configured to transport an object along a path that is independent of any axis of one, two or three of the three or more laboratory modules.

10. The automated laboratory system of any one of claims 3 to 9, wherein the robotic transport is configured to transport an object bi-directionally along an axis or a path.

11. The automated laboratory system of any one of claims 3 to 10, wherein the robotic transport has three degrees of freedom12. The automated laboratory system of any one of claims 3 to 11, wherein the robotic transport does not require a belt, a track, or a guide.

13. The automated laboratory system of any one of claims 3 to 12, wherein the robotic transport is configured to be collaborative with a human.

14. The automated laboratory system of any one of claims 1 to 13, wherein the object is a vessel, a sample, a reagent, a rack or a rack carrier.

15. The automated laboratory system of any one of claims 1 to 14, wherein the three or more laboratory modules is four, five, six, seven, eight, nine or ten laboratory modules.

16. The automated laboratory system of any one of claims 1 to 15, wherein the three or more laboratory modules are arranged so as to allow for a generally linear transfer of the object from the first to the second of the three or more laboratory modules, and from the second to the third of the three or more laboratory modules..

17. A method for an automated laboratory system, the method comprising: providing three or more laboratory modules, selectable, for installation to form the automated laboratory system, from a number of different and interchangeable laboratory modules, each of the three or more laboratory modules has: a respective enclosure, a respective predetermined function characteristic disposed so as to effect a respective predetermined sample process, and a modular interface formed by the respective enclosure, wherein the predetermined function characteristic of at least one of the different laboratory modules is different from another predetermined function characteristic of another of the different laboratory modules, and wherein each of the respective enclosures forms one or more spaces allowing passage of objects therethrough so as to allow the generally lateral transfer of an object into, out of, or between the three or more laboratory modules; andinterfacing and connecting the three or more laboratory modules selected for installation, via a respective modular interface, to at least one other laboratory module, of the different and interchangeable laboratory modules, so that the respective modular interface at least one of: couples the three or more laboratory modules and the at least one other laboratory module to each other, and communicates the compartmentalized predetermined sample process respective to the three or more laboratory modules and the at least one other laboratory module with each other; wherein the compartmentalized predetermined sample process of the selected three or more laboratory modules defines a system sample process, and upon interface with the at least one other laboratory module, the system sample process changes from a closed system process to an open system process.

18. The method of claim 17, wherein the selected one or more laboratory modules forms a cluster of laboratory modules, each of the one or more selected laboratory modules having a multi-axis interface configured to effect transfer of objects between laboratory modules by one or more of transferring objects between the laboratory modules internal to the respective enclosures and external to the respective enclosures.

19. The method of claim 18, further comprising interfacing a robotic transport, disposed external to the one or more laboratory modules, with each module of the cluster of laboratory modules through the multi-axis interface and effecting, with the robotic transport, the external transfer of objects between the one or more selected laboratory modules and to and from the one or more selected laboratory modules.

20. The method of claim 18 or claim 19, wherein at least one axis of the multi-axis interface is a collaborative workspace interface.

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