公开(公告)号：US20230154160A1

公开(公告)日：2023-05-18

申请号：US17986428

申请日：2022-11-14

Applicant: X Development LLC

Inventor： Mohi Khansari ,  Daniel Ho ,  Eric Jang ,  Yu Qing Du

IPC: G06V10/774 ,  G06T5/50

CPC classification number: G06V10/774 ,  G06T5/50 ,  G06T2207/20081

Abstract: Implementations disclosed herein relate to mitigating the reality gap through feature-level domain adaptation in training of a vision-based robotic action machine learning (ML) model. Implementations mitigate the reality gap through utilization of embedding consistency losses and/or action consistency losses during training of the action ML model.

公开(公告)号：US20220134546A1

公开(公告)日：2022-05-05

申请号：US17515490

申请日：2021-10-31

Applicant: X Development LLC

Inventor： Zhuo Xu ,  Wenhao Yu ,  Alexander Herzog ,  Wenlong Lu ,  Chuyuan Fu ,  Yunfei Bai ,  C. Karen Liu ,  Daniel Ho

IPC: B25J9/16 ,  B25J13/08 ,  B25J19/02

Abstract: Utilization of past dynamics sample(s), that reflect past contact physics information, in training and/or utilizing a neural network model. The neural network model represents a learned value function (e.g., a Q-value function) and that, when trained, can be used in selecting a sequence of robotic actions to implement in robotic manipulation (e.g., pushing) of an object by a robot. In various implementations, a past dynamics sample for an episode of robotic manipulation can include at least two past images from the episode, as well as one or more past force sensor readings that temporally correspond to the past images from the episode.