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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-2026048511-A1, on 19 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-2026-000002748

Particle filtering for learning object physics from robot interaction videos

Published
Permanent URL
Classification
Robotics & Automation › Robot Architectures
Inventors
AMBRUS RARES A, KITANI KRIS, LIU KATHERINE, NAN JUNYU, ZAKHAROV SERGEY
Assignee
TOYOTA MOTOR CO LTD, TOYOTA RES INST INC, UNIV CARNEGIE MELLON
Original source
US-2026048511-A1, the United States Patent and Trademark Office, 19 February 2026
Document SHA-256
2ef8fc5f5e753ca71762c42a9370aabf45e77dba012eadab0bc88cac1484fadc

Abstract

A method may include receiving training data comprising a plurality of RGB-D images of an object at a plurality of time steps, and a plurality of robot actions associated with the object at the plurality of time steps; and optimizing, using the training data, a dynamics function to predict a future state of the object based on a current state of the object and a robot action. A state of the object is estimated as a plurality of particles comprising 3D Gaussians using particle filtering.

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Citation

OpenTechnical Publication OT-2026-000002748, “Particle filtering for learning object physics from robot interaction videos,” published September 15, 2026 at 19:15:05 UTC, https://opentechnical.org/p/OT-2026-000002748.

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