Autonomous object learning by robots triggered by remote operators

    公开(公告)号:US11584004B2

    公开(公告)日:2023-02-21

    申请号:US16716874

    申请日:2019-12-17

    Abstract: A method includes receiving, by a control system of a robotic device, data about an object in an environment from a remote computing device, where the data comprises at least location data and identifier data. The method further includes, based on the location data, causing at least one appendage of the robotic device to move through a predetermined learning motion path. The method additionally includes, while the at least one appendage moves through the predetermined learning motion path, causing one or more visual sensors to capture a plurality of images for potential association with the identifier data. The method further includes sending, to the remote computing device, the plurality of captured images to be displayed on a display interface of the remote computing device.

    EVALUATING ROBOT LEARNING
    12.
    发明申请

    公开(公告)号:US20210256424A1

    公开(公告)日:2021-08-19

    申请号:US17307507

    申请日:2021-05-04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for evaluating robot learning. In some implementations, a system receives classification examples from a plurality of remote devices over a communication network. The classification examples can include (i) a data representation generated by a remote device based on sensor data captured by the remote device and (ii) a classification corresponding to the data representation. The system assigns quality scores to the classification examples based on a level of similarity of the data representations with other data representations. The system selects a subset of the classification examples based on the quality scores assigned to the classification examples. The system trains a machine learning model using the selected subset of the classification examples.

    ENHANCING ROBOT LEARNING
    13.
    发明申请

    公开(公告)号:US20210220991A1

    公开(公告)日:2021-07-22

    申请号:US17222496

    申请日:2021-04-05

    Abstract: Methods, systems, and apparatus, including computer-readable media storing executable instructions, for enhancing robot learning. In some implementations, a robot stores first embeddings generated using a first machine learning model, and the first embeddings include one or more first private embeddings that are not shared with other robots. The robot receives a second machine learning model from a server system over a communication network. The robot generates a second private embedding for each of the one or more first private embeddings using the second machine learning model. The robot adds the second private embeddings to the cache of the robot and removes the one or more first private embeddings from the cache of the robot.

    Enhancing robot learning
    14.
    发明授权

    公开(公告)号:US10730181B1

    公开(公告)日:2020-08-04

    申请号:US15855393

    申请日:2017-12-27

    Abstract: Methods, systems, and apparatus, including computer-readable media storing executable instructions, for enhancing robot learning. In some implementations, a robot stores first embeddings generated using a first machine learning model, and the first embeddings include one or more first private embeddings that are not shared with other robots. The robot receives a second machine learning model from a server system over a communication network. The robot generates a second private embedding for each of the one or more first private embeddings using the second machine learning model. The robot adds the second private embeddings to the cache of the robot and removes the one or more first private embeddings from the cache of the robot.

Patent Agency Ranking