公开(公告)号：US20170334066A1

公开(公告)日：2017-11-23

申请号：US15596103

申请日：2017-05-16

Applicant: Google Inc.

Inventor： Sergey Levine ,  Chelsea Finn ,  Ian Goodfellow

IPC: B25J9/16

CPC classification number: B25J9/161 ,  B25J9/1656 ,  B25J9/1697 ,  G05B13/027 ,  G05B2219/39289 ,  G06K9/00 ,  G06K9/00335 ,  G06K9/4628 ,  G06N3/008 ,  G06N3/0454 ,  G06N3/084 ,  G06T7/74 ,  G06T2207/10024 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30164

Abstract: Some implementations of this specification are directed generally to deep machine learning methods and apparatus related to predicting motion(s) (if any) that will occur to object(s) in an environment of a robot in response to particular movement of the robot in the environment. Some implementations are directed to training a deep neural network model to predict at least one transformation (if any), of an image of a robot's environment, that will occur as a result of implementing at least a portion of a particular movement of the robot in the environment. The trained deep neural network model may predict the transformation based on input that includes the image and a group of robot movement parameters that define the portion of the particular movement.

公开(公告)号：US11173599B2

公开(公告)日：2021-11-16

申请号：US15596103

申请日：2017-05-16

Applicant: Google Inc.

Inventor： Sergey Levine ,  Chelsea Finn ,  Ian Goodfellow

IPC: G06N3/08 ,  G06N3/00 ,  G06N3/04 ,  B25J9/16 ,  G05B13/02 ,  G06K9/46 ,  G06K9/00 ,  G06T7/73

Abstract: Some implementations of this specification are directed generally to deep machine learning methods and apparatus related to predicting motion(s) (if any) that will occur to object(s) in an environment of a robot in response to particular movement of the robot in the environment. Some implementations are directed to training a deep neural network model to predict at least one transformation (if any), of an image of a robot's environment, that will occur as a result of implementing at least a portion of a particular movement of the robot in the environment. The trained deep neural network model may predict the transformation based on input that includes the image and a group of robot movement parameters that define the portion of the particular movement.