公开(公告)号：US20230405812A1

公开(公告)日：2023-12-21

申请号：US18239735

申请日：2023-08-29

Applicant: GOOGLE LLC

Inventor： Nicolas Hudson ,  Devesh Yamparala

IPC: B25J9/16 ,  G05B13/02 ,  G06N3/084 ,  G06N3/008 ,  G06N3/045

CPC classification number: B25J9/161 ,  B25J9/163 ,  G05B13/027 ,  B25J9/1656 ,  B25J9/1602 ,  B25J9/1697 ,  G06N3/084 ,  G06N3/008 ,  G06N3/045 ,  G05B2219/33036 ,  G05B2219/33037

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).

公开(公告)号：US12064876B2

公开(公告)日：2024-08-20

申请号：US18239735

申请日：2023-08-29

Applicant: GOOGLE LLC

Inventor： Nicolas Hudson ,  Devesh Yamparala

IPC: B25J13/08 ,  B25J9/16 ,  G05B13/02 ,  G06N3/008 ,  G06N3/045 ,  G06N3/084

CPC classification number: B25J9/161 ,  B25J9/1602 ,  B25J9/163 ,  B25J9/1656 ,  B25J9/1697 ,  G05B13/027 ,  G06N3/008 ,  G06N3/045 ,  G06N3/084 ,  G05B2219/33036 ,  G05B2219/33037

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).

公开(公告)号：US11780083B2

公开(公告)日：2023-10-10

申请号：US17520175

申请日：2021-11-05

Applicant: GOOGLE LLC

Inventor： Nicolas Hudson ,  Devesh Yamparala

IPC: B25J13/08 ,  B25J9/16 ,  G05B13/02 ,  G06N3/084 ,  G06N3/008 ,  G06N3/045

CPC classification number: B25J9/161 ,  B25J9/1602 ,  B25J9/163 ,  B25J9/1656 ,  B25J9/1697 ,  G05B13/027 ,  G06N3/008 ,  G06N3/045 ,  G06N3/084 ,  G05B2219/33036 ,  G05B2219/33037

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.

公开(公告)号：US20240367313A1

公开(公告)日：2024-11-07

申请号：US18776203

申请日：2024-07-17

Applicant: GOOGLE LLC

Inventor： Nicolas Hudson ,  Devesh Yamparala

IPC: B25J9/16 ,  G05B13/02 ,  G06N3/008 ,  G06N3/045 ,  G06N3/084

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).