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公开(公告)号:US20220143819A1
公开(公告)日:2022-05-12
申请号:US17094521
申请日:2020-11-10
Applicant: Google LLC
Inventor: Jie Tan , Sehoon Ha , Peng Xu , Sergey Levine , Zhenyu Tan
Abstract: Techniques are disclosed that enable training a plurality of policy networks, each policy network corresponding to a disparate robotic training task, using a mobile robot in a real world workspace. Various implementations include selecting a training task based on comparing a pose of the mobile robot to at least one parameter of a real world training workspace. For example, the training task can be selected based on the position of a landmark, within the workspace, relative to the pose. For instance, the training task can be selected such that the selected training task moves the mobile robot towards the landmark.
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公开(公告)号:US20190018843A1
公开(公告)日:2019-01-17
申请号:US16116833
申请日:2018-08-29
Applicant: Google LLC
Inventor: Franz Josef Och , Jeffrey Dean , Thorsten Brants , Alexander Mark Franz , Jay Ponte , Peng Xu , Sha-Mayn Teh , Jeffrey Chin , Ignacio E. Thayer , Anton Carver , Daniel Rosart , John S. Hawkins , Karel Driesen
IPC: G06F17/28
Abstract: Systems, methods, and apparatus for accessing distributed models in automated machine processing, including using large language models in machine translation, speech recognition and other applications.
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公开(公告)号:US10089304B2
公开(公告)日:2018-10-02
申请号:US15480722
申请日:2017-04-06
Applicant: Google LLC
Inventor: Franz Josef Och , Jeffrey Dean , Thorsten Brants , Alexander Mark Franz , Jay Ponte , Peng Xu , Sha-Mayn Teh , Jeffrey Chin , Ignacio E. Thayer , Anton Carver , Daniel Rosart , John S. Hawkins , Karel Driesen
IPC: G06F17/28
Abstract: Systems, methods, and apparatus for accessing distributed models in automated machine processing, including using large language models in machine translation, speech recognition and other applications.
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公开(公告)号:US10885285B2
公开(公告)日:2021-01-05
申请号:US16116833
申请日:2018-08-29
Applicant: Google LLC
Inventor: Franz Josef Och , Jeffrey Dean , Thorsten Brants , Alexander Mark Franz , Jay Ponte , Peng Xu , Sha-Mayn Teh , Jeffrey Chin , Ignacio E. Thayer , Anton Carver , Daniel Rosart , John S. Hawkins , Karel Driesen
Abstract: Systems, methods, and apparatus for accessing distributed models in automated machine processing, including using large language models in machine translation, speech recognition and other applications.
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公开(公告)号:US11992945B2
公开(公告)日:2024-05-28
申请号:US17094521
申请日:2020-11-10
Applicant: Google LLC
Inventor: Jie Tan , Sehoon Ha , Peng Xu , Sergey Levine , Zhenyu Tan
CPC classification number: B25J9/163 , B25J9/162 , B25J9/1689 , B25J13/089 , G05D1/02 , G06N3/08
Abstract: Techniques are disclosed that enable training a plurality of policy networks, each policy network corresponding to a disparate robotic training task, using a mobile robot in a real world workspace. Various implementations include selecting a training task based on comparing a pose of the mobile robot to at least one parameter of a real world training workspace. For example, the training task can be selected based on the position of a landmark, within the workspace, relative to the pose. For instance, the training task can be selected such that the selected training task moves the mobile robot towards the landmark.
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