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1. (WO2017151206) DEEP MACHINE LEARNING METHODS AND APPARATUS FOR ROBOTIC GRASPING

Pub. No.:    WO/2017/151206    International Application No.:    PCT/US2016/066393
Publication Date: Sat Sep 09 01:59:59 CEST 2017 International Filing Date: Wed Dec 14 00:59:59 CET 2016
IPC: G06N 3/04
G05B 13/00
G05B 13/02
G06N 3/08
Applicants: GOOGLE LLC
Inventors: LEVINE, Sergey
PASTOR SAMPEDRO, Peter
KRIZHEVSKY, Alex
Title: DEEP MACHINE LEARNING METHODS AND APPARATUS FOR ROBOTIC GRASPING
Abstract:
Deep machine learning methods and apparatus related to manipulation of an object by an end effector of a robot. Some implementations relate to training a deep neural network to predict a measure that candidate motion data for an end effector of a robot will result in a successful grasp of one or more objects by the end effector. Some implementations are directed to utilization of the trained deep neural network to servo a grasping end effector of a robot to achieve a successful grasp of an object by the grasping end effector. For example, the trained deep neural network may be utilized in the iterative updating of motion control commands for one or more actuators of a robot that control the pose of a grasping end effector of the robot, and to determine when to generate grasping control commands to effectuate an attempted grasp by the grasping end effector.