Google is using machine learning to teach robots how to grasp random objects
Originally shared by Ward Plunet
Google is using machine learning to teach robots how to grasp random objects
Google is now using these robots to train a deep convolutional neural network (a technique that’s all the rage in machine learning right now) to help its robots predict the outcome of their grasps based on the camera input and motor commands. It’s basically hand-eye coordination for robots. The team says that it took about 3,000 hours of practice (and 800,000 grasp attempts) before it saw “the beginnings of intelligent reactive behaviors.” “The robot observes its own gripper and corrects its motions in real time. It also exhibits interesting pre-grasp behaviors, like isolating a single object from a group,” the team writes. “All of these behaviors emerged naturally from learning, rather than being programmed into the system.”
http://techcrunch.com/2016/03/08/what-could-go-wrong/?ncid=rss
Google is using machine learning to teach robots how to grasp random objects
Google is now using these robots to train a deep convolutional neural network (a technique that’s all the rage in machine learning right now) to help its robots predict the outcome of their grasps based on the camera input and motor commands. It’s basically hand-eye coordination for robots. The team says that it took about 3,000 hours of practice (and 800,000 grasp attempts) before it saw “the beginnings of intelligent reactive behaviors.” “The robot observes its own gripper and corrects its motions in real time. It also exhibits interesting pre-grasp behaviors, like isolating a single object from a group,” the team writes. “All of these behaviors emerged naturally from learning, rather than being programmed into the system.”
http://techcrunch.com/2016/03/08/what-could-go-wrong/?ncid=rss
Comments
Post a Comment