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US Patent 11780083 Determining and utilizing corrections to robot actions

Patent 11780083 was granted and assigned to Google on October, 2023 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Google
Google
Current Assignee
Google
Google
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11780083
Patent Inventor Names
Devesh Yamparala
Nicolas Hudson
Date of Patent
October 10, 2023
Patent Application Number
17520175
Date Filed
November 5, 2021
Patent Citations
‌
US Patent 11198217 Determining and utilizing corrections to robot actions
‌
US Patent 11173602 Training robotic manipulators
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US Patent 8731276 Motion space presentation device and motion space presentation method
‌
US Patent 9785866 Optimizing multi-class multimedia data classification using negative data
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US Patent 10228680 Autonomous performance optimization in robotic assembly process
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US Patent 10360531 Robot implemented item manipulation
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US Patent 10562181 Determining and utilizing corrections to robot actions
Patent Primary Examiner
‌
Dalena Tran
CPC Code
‌
G05B 19/423
‌
G05B 2219/40116
‌
B25J 9/1671
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B25J 11/0005
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B25J 9/163
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B25J 9/1607
Patent abstract

Methods, apparatus, and computer-readable media for determining and utilizing human corrections to robot actions. In some implementations, in response to determining a human correction of a robot action, a correction instance is generated that includes sensor data, captured by one or more sensors of the robot, that is relevant to the corrected action. The correction instance can further include determined incorrect parameter(s) utilized in performing the robot action and/or correction information that is based on the human correction. The correction instance can be utilized to generate training example(s) for training one or model(s), such as neural network model(s), corresponding to those used in determining the incorrect parameter(s). In various implementations, the training is based on correction instances from multiple robots. After a revised version of a model is generated, the revised version can thereafter be utilized by one or more of the multiple robots.

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