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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-12576516-B2, on 17 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-2026-000001868

Human skill based path generation

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Permanent URL
Classification
Robotics & Automation › Robot Architectures
Inventors
KATO TETSUAKI, WANG KAIMENG, ZHAO YU
Assignee
FANUC CORP
Original source
US-12576516-B2, the United States Patent and Trademark Office, 17 March 2026
Document SHA-256
9e3e62f78d57ee275fd07dae9735ba25d5e2b297bb05ff01b4fea86f10e6690c

Abstract

A method for robot path planning using skills extracted from human-taught motion programs applied to a new obstacle environment. A three-dimensional convolutional neural network is used to extract features characterizing an obstacle environment, where the feature vector representation of the obstacles overcomes problems encountered when using point cloud obstacle data. The obstacle feature data and robot path start and goal points are provided to an encoder/decoder neural network system which is trained to extract skills from a database of human-generated motion programs. The encoder/decoder neural network system produces a distribution of waypoints for the current obstacle environment and start/goal points. The distribution of waypoints is used to perform a final collision-free path generation using either a rapidly-exploring random tree (RRT) technique or an optimization-based technique.

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OpenTechnical Publication OT-2026-000001868, “Human skill based path generation,” published September 15, 2026 at 19:09:10 UTC, https://opentechnical.org/p/OT-2026-000001868.

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