Patent Publication Number: US-2022229760-A1

Title: Long running workflows for robotic process automation

Description:
This application is a continuation of U.S. patent application Ser. No. 16/716,860, filed Dec. 17, 2019, which is based upon and claims benefit of priority from Indian Patent Application Serial No. 201911041916, filed Oct. 16, 2019, the entire contents of both are incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     The present invention relates generally to robotic process automation, and more particularly to long running workflows for robotic process automation. 
     BACKGROUND 
     Robotic process automation (RPA) is a form of process automation that uses software robots to automate workflows. Typically, RPA is implemented for automating repetitive workflows that are completed within a relatively short period of time. Such workflows typically represent fragmented portions of a larger process. Often times, completion of a workflow depends on an external event, such as completion of another workflow, input from a user, a predetermined time delay, etc. Conventionally, in such a scenario, the robot executing the workflow must wait for the external event in order to complete the workflow, and is unable to perform other tasks until the workflow is completed. This conventional approach results in wastage of resources in the form of licensing cost per robot, power requirements, and computational resources. 
     In one example, completion of a workflow may depend on input from a user for handling, e.g., exceptions, validations, approvals, etc. A robot executing such a workflow must wait an uncertain period of time for the user input. The uncertain dependency on user intervention negatively impacts the performance and efficiency of robots. 
     BRIEF SUMMARY OF THE INVENTION 
     In accordance with one or more embodiments, systems and methods for executing a robotic process automation (RPA) workflow are provided. An RPA workflow being executed by a first robot may be suspended by the first robot and resumed by a second robot based on a triggering condition. The first and second robots may be the same or different robots. 
     In one embodiment, the triggering condition includes completion of another RPA workflow. 
     In one embodiment, the RPA workflow includes a robot activity and a human activity. A user request requesting user input for the user activity is generated and the user request is transmitted to a user. The triggering condition may include receipt of the user input for the user activity from the user. A notification indicating that user input for the user activity is requested may also be transmitted to the user. The user activity may include a validation activity or an approval activity. 
     In one embodiment, suspending the execution of the RPA workflow by the first robot includes serializing a current context of the RPA workflow at a time of the suspending and storing the current context of the RPA workflow, and resuming the execution of the RPA workflow by a second robot includes retrieving the current context of the RPA workflow. 
     In one embodiment, a log that records states of the RPA workflow is maintained. 
     These and other advantages of the invention will be apparent to those of ordinary skill in the art by reference to the following detailed description and the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an architectural diagram illustrating a robotic process automation system, according to an embodiment of the invention; 
         FIG. 2  is an architectural diagram illustrating an example of a deployed robotic process automation system, according to an embodiment of the invention; 
         FIG. 3  is an architectural diagram illustrating a simplified deployment example of a robotic process automation system, according to an embodiment of the invention; 
         FIG. 4A  shows a long running workflow for generating and dispatching quotes, according to an embodiment of the invention; 
         FIG. 4B  shows a long running workflow requiring user intervention for generating and dispatching a quote, according to an embodiment of the invention; 
         FIG. 5  shows a flowchart of a method for executing a long running workflow, according to an embodiment of the invention; 
         FIG. 6  shows a flowchart of a method for executing a long running workflow requiring user intervention, according to an embodiment of the invention; and 
         FIG. 7  is a block diagram of a computing system according to an embodiment of the invention. 
     
    
    
     DETAILED DESCRIPTION 
     Robotic process automation (RPA) is used for automating workflows.  FIG. 1  is an architectural diagram of an RPA system  100 , in accordance with one or more embodiments. As shown in  FIG. 1 , RPA system  100  includes a designer  102  to allow a developer to design automation processes using workflows. More specifically, designer  102  facilitates the development and deployment of workflows and robots for performing activities in the workflows. Designer  102  may provide a solution for application integration, as well as automating third-party applications, administrative Information Technology (IT) tasks, and business processes for contact center operations. One commercial example of an embodiment of designer  102  is UiPath Studio™. 
     In designing the automation of rule-based processes, the developer controls the execution order and the relationship between a custom set of steps developed in a workflow, defined herein as “activities.” Each activity may include an action, such as clicking a button, reading a file, writing to a log panel, etc. In some embodiments, workflows may be nested or embedded. 
     Some types of workflows may include, but are not limited to, sequences, flowcharts, Finite State Machines (FSMs), and/or global exception handlers. Sequences may be particularly suitable for linear processes, enabling flow from one activity to another without cluttering a workflow. Flowcharts may be particularly suitable to more complex business logic, enabling integration of decisions and connection of activities in a more diverse manner through multiple branching logic operators. FSMs may be particularly suitable for large workflows. FSMs may use a finite number of states in their execution, which are triggered by a condition (i.e., transition) or an activity. Global exception handlers may be particularly suitable for determining workflow behavior when encountering an execution error and for debugging processes. 
     Once a workflow is developed in designer  102 , execution of business processes is orchestrated by a conductor  104 , which orchestrates one or more robots  106  that execute the workflows developed in designer  102 . One commercial example of an embodiment of conductor  104  is UiPath Orchestrator™. Conductor  220  facilitates management of the creation, monitoring, and deployment of resources in an RPA environment. In one example, conductor  104  is a web application. Conductor  104  may also function as an integration point with third-party solutions and applications. 
     Conductor  104  may manage a fleet of robots  106  by connecting and executing robots  106  from a centralized point. Conductor  104  may have various capabilities including, but not limited to, provisioning, deployment, configuration, queueing, monitoring, logging, and/or providing interconnectivity. Provisioning may include creation and maintenance of connections between robots  106  and conductor  104  (e.g., a web application). Deployment may include assuring the correct delivery of package versions to assigned robots  106  for execution. Configuration may include maintenance and delivery of robot environments and process configurations. Queueing may include providing management of queues and queue items. Monitoring may include keeping track of robot identification data and maintaining user permissions. Logging may include storing and indexing logs to a database (e.g., an SQL database) and/or another storage mechanism (e.g., ElasticSearch®, which provides the ability to store and quickly query large datasets). Conductor  104  may provide interconnectivity by acting as the centralized point of communication for third-party solutions and/or applications. 
     Robots  106  are execution agents that run workflows built in designer  102 . One commercial example of some embodiments of robots  106  is UiPath Robots™. Types of robots  106  may include, but are not limited to, attended robots  108  and unattended robots  110 . Attended robots  108  are triggered by a user or user events and operate alongside a human user on the same computing system. Attended robots  108  may help the human user accomplish various tasks, and may be triggered directly by the human user and/or by user events. In the case of attended robots, conductor  104  may provide centralized process deployment and a logging medium. In certain embodiments, attended robots  108  can only be started from a “robot tray” or from a command prompt in a web application. Unattended robots  110  operate in an unattended mode in virtual environments and can be used for automating many processes, e.g., for high-volume, back-end processes and so on. Unattended robots  110  may be responsible for remote execution, monitoring, scheduling, and providing support for work queues. Both attended and unattended robots may automate various systems and applications including, but not limited to, mainframes, web applications, VMs, enterprise applications (e.g., those produced by SAP®, SalesForce®, Oracle®, etc.), and computing system applications (e.g., desktop and laptop applications, mobile device applications, wearable computer applications, etc.). 
     In some embodiments, robots  106  install the Microsoft Windows° Service Control Manager (SCM)-managed service by default. As a result, such robots  106  can open interactive Windows° sessions under the local system account, and have the rights of a Windows° service. In some embodiments, robots  106  can be installed in a user mode with the same rights as the user under which a given robot  106  has been installed. 
     Robots  106  in some embodiments are split into several components, each being dedicated to a particular task. Robot components in some embodiments include, but are not limited to, SCM-managed robot services, user mode robot services, executors, agents, and command line. SCM-managed robot services manage and monitor Windows° sessions and act as a proxy between conductor  104  and the execution hosts (i.e., the computing systems on which robots  106  are executed). These services are trusted with and manage the credentials for robots  106 . A console application is launched by the SCM under the local system. User mode robot services in some embodiments manage and monitor Windows° sessions and act as a proxy between conductor  104  and the execution hosts. User mode robot services may be trusted with and manage the credentials for robots  106 . A Windows° application may automatically be launched if the SCM-managed robot service is not installed. Executors may run given jobs under a Windows° session (e.g., they may execute workflows) and they may be aware of per-monitor dots per inch (DPI) settings. Agents may be Windows° Presentation Foundation (WPF) applications that display the available jobs in the system tray window. Agents may be a client of the service. Agents may request to start or stop jobs and change settings. Command line is a client of the service and is a console application that can request to start jobs and waits for their output. Splitting robot components can help developers, support users, and enable computing systems to more easily run, identify, and track what each robot component is executing. For example, special behaviors may be configured per robot component, such as setting up different firewall rules for the executor and the service. As a further example, an executor may be aware of DPI settings per monitor in some embodiments and, as a result, workflows may be executed at any DPI regardless of the configuration of the computing system on which they were created. 
       FIG. 2  shows an RPA system  200 , in accordance with one or more embodiments. RPA system  200  may be, or may be part of, RPA system  100  of  FIG. 1 . It should be noted that the “client side”, the “server side”, or both, may include any desired number of computing systems without deviating from the scope of the invention. 
     As shown on the client side in this embodiment, computing system  202  includes one or more executors  204 , agent  206 , and designer  208 . In other embodiments, designer  208  may not be running on the same computing system  202 . An executor  204  (which may be a robot component as described above) runs a process and, in some embodiments, multiple business processes may run simultaneously. In this example, agent  206  (e.g., a Windows° service) is the single point of contact for managing executors  204 . 
     In some embodiments, a robot represents an association between a machine name and a username. A robot may manage multiple executors at the same time. On computing systems that support multiple interactive sessions running simultaneously (e.g., Windows° Server  2012 ), multiple robots may be running at the same time (e.g., a high density (HD) environment), each in a separate Windows° session using a unique username. 
     Agent  206  is also responsible for sending the status of the robot (e.g., periodically sending a “heartbeat” message indicating that the robot is still functioning) and downloading the required version of the package to be executed. The communication between agent  206  and conductor  212  is initiated by agent  206  in some embodiments. In the example of a notification scenario, agent  206  may open a WebSocket channel that is later used by conductor  212  to send commands to the robot (e.g., start, stop, etc.). 
     As shown on the server side in this embodiment, a presentation layer comprises web application  214 , Open Data Protocol (OData) Representative State Transfer (REST) Application Programming Interface (API) endpoints  216  and notification and monitoring API  218 . A service layer on the server side includes API implementation/business logic  220 . A persistence layer on the server side includes database server  222  and indexer server  224 . Conductor  212  includes web application  214 , OData REST API endpoints  216 , notification and monitoring API  218 , and API implementation/business logic  220 . 
     In various embodiments, most actions that a user performs in the interface of conductor  212  (e.g., via browser  210 ) are performed by calling various APIs. Such actions may include, but are not limited to, starting jobs on robots, adding/removing data in queues, scheduling jobs to run unattended, and so on. Web application  214  is the visual layer of the server platform. In this embodiment, web application  214  uses Hypertext Markup Language (HTML) and JavaScript (JS). However, any desired markup languages, script languages, or any other formats may be used without deviating from the scope of the invention. The user interacts with web pages from web application  214  via browser  210  in this embodiment in order to perform various actions to control conductor  212 . For instance, the user may create robot groups, assign packages to the robots, analyze logs per robot and/or per process, start and stop robots, etc. 
     In addition to web application  214 , conductor  212  also includes a service layer that exposes OData REST API endpoints  216  (or other endpoints may be implemented without deviating from the scope of the invention). The REST API is consumed by both web application  214  and agent  206 . Agent  206  is the supervisor of one or more robots on the client computer in this exemplary configuration. 
     The REST API in this embodiment covers configuration, logging, monitoring, and queueing functionality. The configuration REST endpoints may be used to define and configure application users, permissions, robots, assets, releases, and environments in some embodiments. Logging REST endpoints may be useful for logging different information, such as errors, explicit messages sent by the robots, and other environment-specific information, for example. Deployment REST endpoints may be used by the robots to query the package version that should be executed if the start job command is used in conductor  212 . Queueing REST endpoints may be responsible for queues and queue item management, such as adding data to a queue, obtaining a transaction from the queue, setting the status of a transaction, etc. Monitoring REST endpoints monitor web application  214  and agent  206 . Notification and monitoring API  218  may be REST endpoints that are used for registering agent  206 , delivering configuration settings to agent  206 , and for sending/receiving notifications from the server and agent  206 . Notification and monitoring API  218  may also use WebSocket communication in some embodiments. 
     The persistence layer on the server side includes a pair of servers in this illustrative embodiment—database server  222  (e.g., a SQL server) and indexer server  224 . Database server  222  in this embodiment stores the configurations of the robots, robot groups, associated processes, users, roles, schedules, etc. This information is managed through web application  214  in some embodiments. Database server  222  may also manage queues and queue items. In some embodiments, database server  222  may store messages logged by the robots (in addition to or in lieu of indexer server  224 ). Indexer server  224 , which is optional in some embodiments, stores and indexes the information logged by the robots. In certain embodiments, indexer server  224  may be disabled through configuration settings. In some embodiments, indexer server  224  uses ElasticSearch®, which is an open source project full-text search engine. Messages logged by robots (e.g., using activities like log message or write line) may be sent through the logging REST endpoint(s) to indexer server  224 , where they are indexed for future utilization. 
       FIG. 3  is an architectural diagram illustrating a simplified deployment example of RPA system  300 , in accordance with one or more embodiments. In some embodiments, RPA system  300  may be, or may include RPA systems  100  and/or  200  of  FIGS. 1 and 2 , respective. RPA system  300  includes multiple client computing systems  302  running robots. Computing systems  302  are able to communicate with a conductor computing system  304  via a web application running thereon. Conductor computing system  304 , in turn, communicates with database server  306  and an optional indexer server  308 . With respect to  FIGS. 2 and 3 , it should be noted that while a web application is used in these embodiments, any suitable client/server software may be used without deviating from the scope of the invention. For instance, the conductor may run a server-side application that communicates with non-web-based client software applications on the client computing systems. 
     In one embodiment, RPA system  300  may be implemented to execute long running workflows. As used herein, long running workflows are workflows that include one or more activities that depend on an occurrence of an external event in order to complete the activity. An external event of a particular long running workflow is any event that does not result from execution of the particular long running workflow. The external event may include, for example, a completion of another workflow, receiving input from a user, a predetermined period of time, or any other suitable event. Long running workflows are performed over a relatively long period of time (e.g., hours or days) and may be suspended and resumed at any point in time to wait for the occurrence of the external event, thereby providing long running behavior to the workflow. In contrast, activities of non-long running workflows are executed in a continuous manner without waiting for external events. 
       FIG. 4A  shows an exemplary long running workflow  400  for generating and dispatching quotes, in accordance with one or more embodiments. Long running workflow  400  comprises robot activities  402 - 412 . Activity  402  defines a robot requesting a quote. Activity  404  defines a robot fetching product line item details. Activity  406  defines a robot applying country rules to devise a discount. Activity  408  defines a robot generating a quote based on the discount. Activity  410  defines a robot waiting for the generation of any additional quotes. Activity  412  defines a robot dispatches the quotes. 
     In long running workflow  400 , activity  410  depends on the occurrence of the external event of generating additional quotes, which is performed by other workflows. Execution of long running workflow  400  may be suspended while waiting for the generation of the additional quotes and may be resumed once the additional quotes are generated. The robot executing long running workflow  400  may be assigned to execute another workflow when execution of long running workflow  400  is suspended, thereby optimizing resources. Execution of long running workflow  400  may be resumed at activity  412  upon completion of activity  410  with a same or a different robot. 
       FIG. 4B  shows an exemplary long running workflow  450  requiring user intervention for generating and dispatching a quote, in accordance with one or more embodiments. Long running workflow  450  comprises robot activities  452 ,  454 ,  456 , and  460  and user activities  458 -A and  458 -B. User activities refer to activities of a workflow performed by a user. 
     Activity  452  defines a robot requesting a quote. Activity  454  defines a robot fetching product line item details. Activity  456  defines a robot applying country rules to devise a discount. If the discount is greater than 10%, long running workflow  450  proceeds to activities  458 -A and  458 -B for receiving approval from end users (e.g., approver 1 and approver 2, respectively) for the discount. If the discount is approved for activities  458 -A and  458 -B or if the discount is not greater than 10% (such that the discount is auto approved) at activity  456 , a quote is generated and dispatched at activity  460 . 
     In long running workflow  450 , activities  458 -A and  458 -B depend on the occurrence of the external event of receiving approval, which is performed by users. Execution of long running workflow  450  may be suspended while waiting for user intervention approving the discount and may be resumed once the discount has been approved. The robot executing long running workflow  450  may be assigned to execute another workflow when execution of long running workflow  450  is suspended, thereby optimizing resources. Execution of long running workflow  450  may be resumed at activity  460  upon completion of activities  458 -A and  458 -B with a same or a different robot. 
     Long running workflows, such as, e.g., long running workflow  400  of  FIG. 4A  and long running workflow  450  of  FIG. 4B , may be created by a user (e.g., an RPA developer) using, e.g., designer  102  of  FIG. 1  or designer  208  of  FIG. 2 . For example, the user may interact with designer  102  or designer  208  to stitch together multiple fragmented activities (including fragmented shorter running workflows) to create a long running workflow. In one embodiment, the user creates the long running workflow by creating a new project (e.g., in designer  102  of  FIG. 1  or designer  208  of  FIG. 2 ) and selecting (e.g., dragging and dropping from a set of available activities and/or workflows) activities. 
       FIG. 5  shows a method  500  for executing a long running RPA workflow, in accordance with one or more embodiments. The steps of method  500  may be performed by one or more robots (e.g., attended robot  108  or unattended robot  110  of  FIG. 1  or robots  302  of  FIG. 3 ) running on a computing device (e.g., computing system  700  of  FIG. 7 ). Method  500  is for executing a long running workflow that does not include a user activity, such as, e.g., long running workflow  400  of  FIG. 4A . 
     At step  502 , the long running workflow is executed by a first robot. In one embodiment, one or more robot activities of the long running workflow are executed by the first robot at step  502 . For example, robot activities of steps  402 - 408  of long running workflow  400  of  FIG. 4A  may be executed by the first robot. 
     At step  504 , the execution of the long running workflow is suspended by the first robot. In one embodiment, execution of the long running workflow may be suspended to wait for an external event. In one example, the external event may be waiting for the completion of a robot activity, such as, e.g., completion of another workflow by another robot. For instance, the external event may be waiting for completion of the robot activity  410  of long running workflow  400  of  FIG. 4A . In another example, the external event may be based on a time, such as, e.g., waiting for a certain time of the day or waiting for a predetermined period of time. Execution of the long running workflow may be suspended at any time during the long running workflow, such as, e.g., during performance of an activity of the long running workflow or between activities of the long running workflow. In one embodiment, suspension of the long running workflow is defined by the activity of the long running workflow that the first robot is executing. The long running workflow may be suspended by setting the state of the long running workflow to idle. 
     In one example, one or more activities of the long running workflow may indicate to wait for the completion of one or more other workflows. In this example, a first activity of the long running workflow may instruct an executing robot to transmit a triggering instruction to an orchestrator (e.g., conductor  104  of  FIG. 1 , conductor  212  of  FIG. 2 , or conductor  304  of  FIG. 3 ) coordinating execution of workflows to trigger the one or more other workflows and to retrieve a job ID (e.g., Job 10) associated with the one or more other workflows from the orchestrator. A second activity may instruct the executing robot to suspend the long running workflow and record a triggering condition defining when the long running workflow is to be resumed (e.g., upon completion of Job  10 ). The executing robot will transmit the triggering condition to the orchestrator. 
     In another example, an activity of the long running workflow may indicate to wait for a predetermined period of time. In this example, the activity may instruct an executing robot to suspend the long running workflow and record a triggering condition defining when the long running workflow is to be resumed (e.g., the time at which the long running workflow is to be resumed). The executing robot will transmit the triggering condition to the orchestrator. 
     At step  506 , the execution of the long running workflow is resumed by a second robot based on a triggering condition. For example, the execution of the long running workflow  400  of  FIG. 4A  may be resumed by executing the robot activity of step  412 . The triggering condition may be any suitable triggering condition for resuming the long running workflow. The triggering condition may be based on the conditions that caused the long running workflow to be suspended. For example, where the long running workflow was suspended to wait for the completion of a robot activity (at step  504 ), the triggering condition may be the completion of the robot activity (e.g., robot activity  410  of  FIG. 4A ). In another example, where the long running workflow was suspended to wait for a predetermined period of time (at step  504 ), the triggering condition may be that the predetermined period of time is reached. 
       FIG. 6  shows a method  600  for executing a long running workflow requiring user intervention, in accordance with one or more embodiments. Such a long running workflow comprises one or more robot activities stitched together with one or more user activities. The user activity inserts user intervention into the long running workflow. The steps of method  600  may be performed by one or more robots (e.g., attended robot  108  or unattended robot  110  of  FIG. 1  or robots  302  of  FIG. 3 ) running on a computing device (e.g., computing system  700  of  FIG. 7 ). Method  600  will be described with reference to long running workflow  450  of  FIG. 4B . 
     At step  602 , the long running workflow is executed by a first robot. In one embodiment, one or more robot activities of the long running workflow are executed by the first robot at step  602 . For example, long running workflow  450  of  FIG. 4B  may be executed by executing robot activities  452 ,  454 , and  546 . 
     At step  604 , the execution of the long running workflow is suspended by the first robot. The suspension may be in response to one or more user activities. For example, execution of long running workflow  450  of  FIG. 4B  may be suspended in response to user activities  458 -A and  458 -B in  FIG. 4B . An exemplary user activity includes approval and validation of a document processing activity by an end user. 
     At step  606 , a user request requesting user input for a user activity of the long running workflow is generated. In one embodiment, the user request may be a visualization of the user activity. The visualization may be generated by the first robot as a user interface enabling an end user to provide user input (e.g., approve or disapprove). The visualization may be customized via forms to provide a different visualization for different workflows and for different user activities within the workflow. The forms are generated at the time of creating the workflow. In particular, a user creating the workflow may define a title and priority for the workflow, as well as map workflow variables to be passed to activities of the workflow as data. A form defining visualizations (e.g., layout of data) may be defined using the mapped workflow variables. The form may be customized based on the activity of the workflow. The form will be rendered for each task to generate the visualization. 
     In one embodiment, a notification indicating that user input for the user activity is requested is also transmitted to the end user. The notification may include a link, or otherwise direct the end user to, the visualization to enable the end user to provide user input. The notification may be a mobile device notification, text message, email, etc. 
     At step  608 , the user request is transmitted to an end user. In one embodiment, the end user receives a notification upon receiving the user request. As such, the end user no longer has to monitor the status of the long running workflow. 
     At step  610 , the execution of the long running workflow is resumed by a second robot based on the user input received from the end user. For example, the long running workflow  450  of  FIG. 4B  may be resumed by the second robot executing robot activity  460  based on user input from Approver  1  and Approver  2  (e.g., approving the discount). 
     With reference to method  500  of  FIG. 5  and method  600  of  FIG. 6 , the first robot and the second robot may be any suitable robot for executing RPA workflows. In one embodiment, the first robot and the second robot are unattended robots. The first robot and the second robot may be the same robot or different robots. In one embodiment, the second robot is the first available robot in a robot pool associated with the long running workflow. The activities of the long running workflow may include any suitable activity for RPA that is serializable. The activities may be invoked in an asynchronous non-blocking manner. In one embodiment, the activities include non-UI activities that may be invoked in a synchronous blocking manner or in an asynchronous blocking manner. Non-UI activities may include, for example, calls to external systems (e.g., an API call to an SAP (Systems Applications and Products) system to retrieve data). The calls may be executed in an asynchronous manner, meaning that the call to the API is performed and the handling of the returned data is defined at the same time, and the thread proceeds with other logic. A synchronous call, on the other hand, executes the call, waits and blocks the thread until the data is received, and then proceeds with the data handling. 
     To suspend the execution of the long running workflow at step  504  of method  500  and step  604  of method  600 , the current context of the long running workflow at the time of suspension is serialized. Serialization of the current context of the long running workflow refers to the process of translating the current state of the long running workflow (data variables and their values) into a format that can be stored and later reconstructed. The current context of the long running workflow is stored in a central persistent storage, such as, e.g., database server  222  of  FIG. 2  or database server  306  of  FIG. 3 . Execution of the long running workflow is resumed at step  506  of method  500  and step  610  of method  600  by retrieving the current context of the long running workflow from the central persistent storage (e.g., database server  222  of  FIG. 2  or database server  306  of  FIG. 3 ). Accordingly, even if the long running workflow was later updated or modified (e.g., after suspension of the execution of the long running workflow), execution of the long running workflow is resumed using the workflow state (data variables and their values) at the time of suspension, which was stored in the central persistent storage. 
     The long running workflows may be suspended any number of instances. Accordingly, method  500  may iterate by returning to step  504  and method  600  may iterate by returning to step  604  each time the resumed long running workflow is suspended until execution of the long running workflow is complete. 
     While the steps of methods  500  and  600  may be performed by one or more robots, coordination of those steps are managed by an orchestrator, such as, e.g., conductor  104  of  FIG. 1 , conductor  212  of  FIG. 2 , or conductor  304  of  FIG. 3 . Specifically, with respect to method  500 , the orchestrator transmits an indication to execute the long running workflow to the first robot to perform step  502 , transmits an indication to suspend the execution of the long running workflow to the first robot to perform step  504 , determines whether the triggering condition is satisfied, and if the triggering condition is satisfied, transmits an indication to resume the execution of the long running workflow to the second robot. In one embodiment, the orchestrator determines whether the triggering condition is satisfied by receiving call backs from activities and/or workflows indicating that the activity and/or workflow is complete. With respect to method  600 , the orchestrator transmits an indication to execute the long running workflow to the first robot to perform step  602 , transmits an indication to suspend the execution of the long running workflow to the first robot to perform step  604 , receives the generated user request from the robot and transmits the generated user request to the end user, receives user input from the end user in response to the user request, and transmits an indication to resume the execution of the long running workflow to the second robot. Accordingly, the long running workflow is coordinated in a centralized manner by the orchestrator but may be executed in a decentralized manner by different robots. 
     To enable long running behavior of the long running workflow described with respect to methods  500  and  600 , the orchestrator maintains a log of the long running workflow recording states of the long running workflow as the long running workflow is executed from start to completion. The states may include, for example, suspension and resumption of the execution of the long running workflow, the reason for suspension of the execution of the long running workflow, triggering conditions that are satisfied to resume the execution of the long running workflow, and any other suitable information. The log of the long running workflow is maintained using a job identifier (ID) to track with the long running workflow. 
     Advantageously, the suspending and resuming of long running workflows allows for optimal resource allocation for performing the long running workflows without the need for continuous monitoring or waiting by a robot. 
       FIG. 7  is a block diagram illustrating a computing system  700  configured to execute the methods described in reference to  FIG. 4 , according to an embodiment of the present invention. In some embodiments, computing system  700  may be one or more of the computing systems depicted and/or described herein. Computing system  700  includes a bus  702  or other communication mechanism for communicating information, and processor(s)  704  coupled to bus  702  for processing information. Processor(s)  704  may be any type of general or specific purpose processor, including a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Graphics Processing Unit (GPU), multiple instances thereof, and/or any combination thereof. Processor(s)  704  may also have multiple processing cores, and at least some of the cores may be configured to perform specific functions. Multi-parallel processing may be used in some embodiments. 
     Computing system  700  further includes a memory  706  for storing information and instructions to be executed by processor(s)  704 . Memory  706  can be comprised of any combination of Random Access Memory (RAM), Read Only Memory (ROM), flash memory, cache, static storage such as a magnetic or optical disk, or any other types of non-transitory computer-readable media or combinations thereof. Non-transitory computer-readable media may be any available media that can be accessed by processor(s)  704  and may include volatile media, non-volatile media, or both. The media may also be removable, non-removable, or both. 
     Additionally, computing system  700  includes a communication device  708 , such as a transceiver, to provide access to a communications network via a wireless and/or wired connection according to any currently existing or future-implemented communications standard and/or protocol. 
     Processor(s)  704  are further coupled via bus  702  to a display  710  that is suitable for displaying information to a user. Display  710  may also be configured as a touch display and/or any suitable haptic I/O device. 
     A keyboard  712  and a cursor control device  714 , such as a computer mouse, a touchpad, etc., are further coupled to bus  702  to enable a user to interface with computing system. However, in certain embodiments, a physical keyboard and mouse may not be present, and the user may interact with the device solely through display  710  and/or a touchpad (not shown). Any type and combination of input devices may be used as a matter of design choice. In certain embodiments, no physical input device and/or display is present. For instance, the user may interact with computing system  700  remotely via another computing system in communication therewith, or computing system  700  may operate autonomously. 
     Memory  706  stores software modules that provide functionality when executed by processor(s)  704 . The modules include an operating system  716  for computing system  700  and one or more additional functional modules  718  configured to perform all or part of the processes described herein or derivatives thereof. 
     One skilled in the art will appreciate that a “system” could be embodied as a server, an embedded computing system, a personal computer, a console, a personal digital assistant (PDA), a cell phone, a tablet computing device, a quantum computing system, or any other suitable computing device, or combination of devices without deviating from the scope of the invention. Presenting the above-described functions as being performed by a “system” is not intended to limit the scope of the present invention in any way, but is intended to provide one example of the many embodiments of the present invention. Indeed, methods, systems, and apparatuses disclosed herein may be implemented in localized and distributed forms consistent with computing technology, including cloud computing systems. 
     It should be noted that some of the system features described in this specification have been presented as modules, in order to more particularly emphasize their implementation independence. For example, a module may be implemented as a hardware circuit comprising custom very large scale integration (VLSI) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A module may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices, graphics processing units, or the like. A module may also be at least partially implemented in software for execution by various types of processors. An identified unit of executable code may, for instance, include one or more physical or logical blocks of computer instructions that may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified module need not be physically located together, but may include disparate instructions stored in different locations that, when joined logically together, comprise the module and achieve the stated purpose for the module. Further, modules may be stored on a computer-readable medium, which may be, for instance, a hard disk drive, flash device, RAM, tape, and/or any other such non-transitory computer-readable medium used to store data without deviating from the scope of the invention. Indeed, a module of executable code could be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within modules, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network. 
     The foregoing merely illustrates the principles of the disclosure. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described or shown herein, embody the principles of the disclosure and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to be only for pedagogical purposes to aid the reader in understanding the principles of the disclosure and the concepts contributed by the inventor to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the disclosure, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future.