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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-2026077489-A1, on 19 March 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-2026-000001714

Robot learning through retrieval and self improvement

Published
Permanent URL
Classification
Robotics & Automation › Robot Architectures
Inventors
ABEYRUWAN SAMINDA WISHWAJITH, AMOR HENI BEN, D'AMBROSIO DAVID B, GRAESSER LAURA HARDING, ISCEN ATIL, SANKETI PANNAG R
Assignee
GDM HOLDING LLC
Original source
US-2026077489-A1, the United States Patent and Trademark Office, 19 March 2026
Document SHA-256
50b796c69a224a84f35d8b693fc105994f814d231b6eecc41e68f5b67d74c1d1

Abstract

Implementations are provided for an interactive machine learning methodology that allows non-expert users to use natural language to teach new skills, particularly to robots, through language grounding and understanding. In various implementations, a plurality of natural language summaries may be retrieved. Each of the natural language summaries may describe details of robotic performance of a task, and may include, or be usable to retrieve, a corresponding set of reference modulation values. A set of modulation values corresponding to a natural language request may be generated based on the plurality of natural language summaries. The natural language request may specify one or more constraints on robotic performance of the task. A robot control signal may be generated based on the generated set of modulation values.

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Citation

OpenTechnical Publication OT-2026-000001714, “Robot learning through retrieval and self improvement,” published September 15, 2026 at 19:07:52 UTC, https://opentechnical.org/p/OT-2026-000001714.

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