公开(公告)号：US20250144795A1

公开(公告)日：2025-05-08

申请号：US19008421

申请日：2025-01-02

Applicant: Google LLC

Inventor： Peter Raymond Florence ,  Danny Michael Driess ,  Igor Mordatch ,  Andy Zeng ,  Seyed Mohammad Mehdi Sajjadi ,  Klaus Greff

IPC: B25J9/16

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling an agent interacting with an environment. In one aspect, a method comprises: receiving one or more observations of an environment; receiving an input text sequence that describes a task to be performed by a robot in the environment; generating an encoded representation of the input text sequence in an embedding space; generating a corresponding encoded representation of each of the one or more observations in the embedding space; generating a sequence of input tokens that comprises the encoded representation of the input text sequence and the corresponding encoded representation of each observation; processing the sequence of input tokens using a language model neural network to generate an output text sequence that comprises high-level natural language instructions; and determining, from the high-level natural language instructions, one or more actions to be performed by the robot.

公开(公告)号：US20230256597A1

公开(公告)日：2023-08-17

申请号：US18011561

申请日：2020-10-15

Applicant: Google LLC

Inventor： Andy Zeng

IPC: B25J9/16 ,  B25J19/02

CPC classification number: B25J9/163 ,  B25J9/161 ,  B25J9/1697 ,  B25J19/022

Abstract: A transporter network for determining robot actions based on sensor feedback can afford robots with efficient autonomous movement. The transporter network may exploit spatial symmetries and may not need assumptions of objectness to provide accurate instructions on object manipulation. The machine-learned model of the transporter network may also allow for learning various tasks with less training examples than other machinelearned models. The machine-learned model of the transporter network may intake observation data as input and may output actions in response to the processed observation data.