公开(公告)号：US11341406B1

公开(公告)日：2022-05-24

申请号：US16133409

申请日：2018-09-17

Applicant: X Development LLC

Inventor： Joseph Redmon ,  Anelia Angelova

IPC: G06N3/08 ,  G06N3/04 ,  B25J9/16

Abstract: Methods and apparatus related to training and/or utilizing a convolutional neural network to generate grasping parameters for an object. The grasping parameters can be used by a robot control system to enable the robot control system to position a robot grasping end effector to grasp the object. The trained convolutional neural network provides a direct regression from image data to grasping parameters. For example, the convolutional neural network may be trained to enable generation of grasping parameters in a single regression through the convolutional neural network. In some implementations, the grasping parameters may define at least: a “reference point” for positioning the grasping end effector for the grasp; and an orientation of the grasping end effector for the grasp.

公开(公告)号：US10089575B1

公开(公告)日：2018-10-02

申请号：US14723373

申请日：2015-05-27

Applicant: X Development LLC

Inventor： Joseph Redmon ,  Anelia Angelova

IPC: G06N3/08 ,  B25J9/16 ,  G06N3/04

Abstract: Methods and apparatus related to training and/or utilizing a convolutional neural network to generate grasping parameters for an object. The grasping parameters can be used by a robot control system to enable the robot control system to position a robot grasping end effector to grasp the object. The trained convolutional neural network provides a direct regression from image data to grasping parameters. For example, the convolutional neural network may be trained to enable generation of grasping parameters in a single regression through the convolutional neural network. In some implementations, the grasping parameters may define at least: a “reference point” for positioning the grasping end effector for the grasp; and an orientation of the grasping end effector for the grasp.