Robot fleet management with workflow simulation for value chain networks

A robot fleet management platform that automatically configures, organizes, deploys, and controls a robot fleet of robot operating units, the robot fleet management platform comprising:

• a set of processors that executes a set of computer-readable instructions, wherein the set of processors collectively executes:
• receiving a job request associated with moving a set of items from a first value chain network entity to a second value chain network entity;
• applying content and structural filters to job content received in association with the job request to identify portions thereof suitable for robot automation;
• generating a digital twin that represents a real-time status of a job being performed by at least one robot operating unit of the robot fleet based on at least one of:
• the job request, the job content received, or the identified portions suitable for robot automation;
• in response to identifying portions of the job content suitable for robot automation, automatically establishing a set of robot tasks that each define at least a type of robot and a task objective by referring to the digital twin of the job, the set of robot tasks are based, at least in part, on the portions of the job request that are suitable for robot automation and meet a fleet objective;
• in response to establishing the set of robot tasks, automatically applying fleet configuration services to the job content and the set of robot tasks to produce (i) a fleet resource configuration data structure for the job request that associates the at least one robot operating unit of the robot fleet with each task in the set of robot tasks, and (ii) based on the at least one robot operating unit, robot adaptation instructions for performing an associated task;
• in response to producing the fleet resource configuration data structure and the robot adaptation instructions, automatically recommending a robot task and associated contextual information that facilitates robot selection and task ordering in a workflow of the set of robot tasks with a fleet intelligence layer;
• triggering generation of the workflow based on the fleet resource configuration data structure and the set of robot tasks;
• in response to the generation of the workflow, optimizing the workflow by executing a set of simulations using the digital twin of the job, wherein the executing the set of simulations includes performing a set of stress tests associated with the moving the set of items from the first value chain network entity to the second value chain network entity;
• in response to the optimizing the workflow, triggering generation of at least a portion of an execution plan associated with the set of robot tasks;
• in response to the generation of the at least the portion of the execution plan, triggering performance of the execution plan by controlling the at least one robot operating unit to execute the set of robot tasks, wherein the at least one robot operating unit is configured to operate fully autonomously in executing the set of robot tasks;
• in response to the triggering of the performance of the execution plan, providing, via the digital twin of the job, the real-time status of the job being performed by the at least one robot operating unit;
• and
• in response to completing the execution plan, optimizing the set of robot tasks by:
• receiving feedback associated with the performance of the at least one robot operating unit, and
• updating the set of robot tasks based on the feedback,
• wherein the real-time status of the job includes a job completion status that indicates progress of the job being performed by the at least one robot operating unit,
• wherein the real-time status of the job includes a real-time status of the at least one robot operating unit including a battery life status and an energy source availability status,
• wherein the feedback includes a job completion data set, and
• wherein the optimizing the set of robot tasks includes:
• identifying a count of repetitions of robot functions based on the job completion data set, and
• in response to the count exceeding a threshold, removing at least one repeated robot function.