Robot fleet management and additive manufacturing for value chain networks

Abstract

This system provides a value chain network automation system for managing value chain network entities. [Solution] The value chain network automation system includes a supply chain robot fleet dataset, which includes a set of state and capability attributes of a set of robot systems in the supply chain for a set of goods; a demand intelligence robot process automation dataset, which includes a set of state attributes of a set of robot process automation systems that undertake the automation of a set of demand forecasting tasks for a set of goods; and a coordination system that provides a set of robot task instructions for the supply chain robot fleet based on processing of the supply chain robot fleet dataset and the demand intelligence robot process automation dataset in order to coordinate the supply and demand for the set of goods.

Claims

1. A robot fleet management platform, It includes a set of one or more processors that execute a set of computer-readable instructions, The set of one or more processors is Receiving a job request that includes descriptive information about the job deliverable and request-specific constraints for providing the said job deliverable, Apply content and structure filters to the content received in relation to the job request to identify parts suitable for automation by robots. Establish a set of robot tasks, each defining at least the type of robot and the task objective, wherein the set of robot tasks is at least partially based on the portion of the job request that is suitable for automation by robots and that satisfies the first fleet objective. Applying a fleet configuration service to the job content and the set of robot tasks to generate a fleet resource configuration data structure for the job request, which associates at least one robot operating unit with each task in the set of tasks, and associates the at least one robot operating unit with robot adaptive instructions for executing the associated tasks. Using a fleet intelligence layer, we recommend robot tasks and related contextual information to facilitate robot selection and task ordering in the robot task workflow. Based on the aforementioned fleet resource configuration data structure and the set of robot tasks, generate the workflow for the robot task. To simulate a digital model of the robot operating unit that executes the task definition digital model, thereby verifying the generated workflow, and to provide the results of a job execution simulation for recursively establishing the set of robot tasks, and A robot fleet management platform characterized by collectively performing the task of generating at least a first portion of the execution plan for robot fleet resources configured in the aforementioned fleet resource configuration data structure.

2. The robot fleet management platform according to claim 1, further comprising the fleet intelligence layer proposing alternative tasks that satisfy a second fleet objective.

3. The robot fleet management platform according to claim 1, further comprising optimizing at least one of the robot type and task objective using the intelligence layer based on the first fleet objective.

4. The robot fleet management platform according to claim 3, characterized in that the first fleet objective includes criteria for the utilization of fleet resources.

5. The robot fleet management platform according to claim 1, characterized in that the task definition system receives a specific robot type from the fleet configuration proxy service for use when executing a robot task.

6. The robot fleet management platform according to claim 5, characterized in that establishing the set of robot tasks is based on the specific robot types provided by the fleet configuration proxy service.

7. The robot fleet management platform according to claim 1, characterized in that establishing a set of robot tasks includes generating a data structure for each task in the task set, which includes a digital twin for at least one of the tasks and a reference to at least one robot operating unit for performing the task, for use by the workflow simulation system.

8. The robot fleet management platform according to claim 1, characterized in that establishing the set of robot tasks includes generating a data structure for each task in the set of tasks that identifies at least one of the type of robot and a robot operating unit for performing the task, and a configuration data structure for configuring a robot for performing the task.

9. The robot fleet management platform according to claim 1, characterized in that establishing the set of robot tasks includes generating a data structure for each task in the set of tasks and storing the data structure in a library of robot tasks, which is indexed by information indicating the job request and at least one identifier of the robot type and the robot operating unit.

10. The robot fleet management platform according to claim 1, wherein establishing the set of robot tasks includes matching the requirements and robot capabilities with the constraints identified in the job request when identifying the type of robot to satisfy the task objectives.

11. The robot fleet management platform according to claim 1, characterized in that establishing the set of robot tasks includes generating multiple robot tasks for multiple different robot types in order to achieve the task objectives.

12. The robot fleet management platform according to claim 1, characterized in that establishing the set of robot tasks includes querying a library of robot tasks for candidate robot tasks that satisfy the task objectives, and interacting with the fleet configuration proxy service to select robot tasks from the candidate robot tasks based on the at least one fleet objective.

13. The robot fleet management platform according to claim 12, characterized in that at least one of the fleet objectives is compatible with available robot operating units.

14. The robot fleet management platform according to claim 1, characterized in that establishing the set of robot tasks includes querying a library of robot tasks for candidate robot tasks that satisfy the task objectives, and interacting with the fleet intelligence layer to select a robot task from the candidate robot tasks based on the suitability of the candidate robot tasks for achieving the task objectives.

15. The robot fleet management platform according to claim 1, characterized in that establishing the set of robot tasks includes referring to descriptive information of a sensor detection package indicating a preferred sequence of sensing tasks when defining the set of tasks.

16. The robot fleet management platform according to claim 1, characterized in that generating the workflow for the robot task includes referring to descriptive information of a sensor detection package indicating a preferred sequence of sensing tasks when defining the workflow for the robot task.

17. The robot fleet management platform according to claim 1, characterized in that generating the workflow of the robot task is based on the dependency of the second task on the first task to satisfy the objective of the second task.

18. The robot fleet management platform according to claim 1, characterized in that simulating a digital model of the robot operating unit includes manipulating a digital twin of the tasks in the set of tasks to determine an optimized workflow sequence for the tasks.

Images