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This is a record of a document published elsewhere, first published by the United States Patent and Trademark Office, as US-12561659-B2, on 24 February 2026. OpenTechnical did not first disclose it. The identifier, hashes and timestamps below record what this library served and when, not when the material became public. View the original.

OT-2026-000002585

Machine-learned robot fleet management for value chain networks

Published
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Classification
Sensors, Controls & Machine Vision › Industrial Control
Inventors
CELLA CHARLES H, EL-TAHRY TEYMOUR S, FORTIN JR LEON
Assignee
STRONG FORCE VCN PORTFOLIO 2019 LLC
Original source
US-12561659-B2, the United States Patent and Trademark Office, 24 February 2026
Document SHA-256
9ed66f5712f45a55aae39010d236b8a682452257c72b80c50b38141fa6d3491c

Abstract

A system includes a fleet resources data store that maintains a fleet resource inventory indicating fleet resources that can be assigned to perform tasks. For each fleet resource, the inventory indicates features of each fleet resource and a respective status. A set of task definitions is accessible to an intelligence layer to facilitate improving task definition based on feedback from task-specific outcomes. The system receives a job request for a robotic fleet to perform a job and determines a job definition data structure indicating a set of tasks to be performed for the job. The system applies an outcome of performing a task by a resource assigned to perform the task to a machine learning system of the intelligence layer that facilitates improving, based on the outcome, the set of task definitions. The system updates the set of task definitions based on a result of applying the machine learning system.

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Citation

OpenTechnical Publication OT-2026-000002585, “Machine-learned robot fleet management for value chain networks,” published September 15, 2026 at 19:14:01 UTC, https://opentechnical.org/p/OT-2026-000002585.

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This record reproduces a document published elsewhere and is provided for reference and study. Rights in the original remain with its owner. See the publication policy.