公开(公告)号：US20210078167A1

公开(公告)日：2021-03-18

申请号：US16886545

申请日：2020-05-28

Applicant: X Development LLC

Inventor： Seyed Mohammad Khansari Zadeh ,  Daniel Kappler ,  Jianlan Luo ,  Jeffrey Bingham ,  Mrinal Kalakrishnan

IPC: B25J9/16 ,  B25J15/00 ,  G06T7/70 ,  G06K9/00 ,  G06T7/50 ,  G06T7/90

Abstract: Generating and utilizing action image(s) that represent a candidate pose (e.g., a candidate end effector pose), in determining whether to utilize the candidate pose in performance of a robotic task. The action image(s) and corresponding current image(s) can be processed, using a trained critic network, to generate a value that indicates a probability of success of the robotic task if component(s) of the robot are traversed to the particular pose. When the value satisfies one or more conditions (e.g., satisfies a threshold), the robot can be controlled to cause the component(s) to traverse to the particular pose in performing the robotic task.

公开(公告)号：US20220297303A1

公开(公告)日：2022-09-22

申请号：US17203296

申请日：2021-03-16

Applicant: X Development LLC

Inventor： Seyed Mohammad Khansari Zadeh ,  Eric Jang ,  Daniel Lam ,  Daniel Kappler ,  Matthew Bennice ,  Brent Austin ,  Yunfei Bai ,  Sergey Levine ,  Alexander Irpan ,  Nicolas Sievers ,  Chelsea Finn

IPC: B25J9/16 ,  B25J13/06

Abstract: Implementations described herein relate to training and refining robotic control policies using imitation learning techniques. A robotic control policy can be initially trained based on human demonstrations of various robotic tasks. Further, the robotic control policy can be refined based on human interventions while a robot is performing a robotic task. In some implementations, the robotic control policy may determine whether the robot will fail in performance of the robotic task, and prompt a human to intervene in performance of the robotic task. In additional or alternative implementations, a representation of the sequence of actions can be visually rendered for presentation to the human can proactively intervene in performance of the robotic task.

公开(公告)号：US11607802B2

公开(公告)日：2023-03-21

申请号：US16886545

申请日：2020-05-28

Applicant: X Development LLC

Inventor： Seyed Mohammad Khansari Zadeh ,  Daniel Kappler ,  Jianlan Luo ,  Jeffrey Bingham ,  Mrinal Kalakrishnan

IPC: B25J9/16 ,  B25J15/00 ,  G06T7/70 ,  G06K9/00 ,  G06T7/50 ,  G06T7/90 ,  G06V20/10

Abstract: Generating and utilizing action image(s) that represent a candidate pose (e.g., a candidate end effector pose), in determining whether to utilize the candidate pose in performance of a robotic task. The action image(s) and corresponding current image(s) can be processed, using a trained critic network, to generate a value that indicates a probability of success of the robotic task if component(s) of the robot are traversed to the particular pose. When the value satisfies one or more conditions (e.g., satisfies a threshold), the robot can be controlled to cause the component(s) to traverse to the particular pose in performing the robotic task.