Robots Learn Cooking By Watching Videos - Foreseen In 1943
DARPA’s Mathematics of Sensing, Exploitation and Execution (MSEE) program recently developed a system that enabled robots to process visual data from a series of “how to” cooking videos on YouTube.
(Robot Learning Manipulation Action Plans by “Watching” Unconstrained Videos)
In order to advance action generation and creation in robots
beyond simple learned schemas we need computational tools
that allow us to automatically interpret and represent human
actions. This paper presents a system that learns manipulation
action plans by processing unconstrained videos from
the World Wide Web. Its goal is to robustly generate the sequence
of atomic actions of seen longer actions in video in
order to acquire knowledge for robots.
The lower level of the
system consists of two convolutional neural network (CNN)
based recognition modules, one for classifying the hand grasp
type and the other for object recognition. The higher level
is a probabilistic manipulation action grammar based parsing
module that aims at generating visual sentences for robot
Experiments conducted on a publicly available
unconstrained video dataset show that the system is able
to learn manipulation actions by “watching” unconstrained
videos with high accuracy.
This very process was foreseen in Anthony Boucher's 1943 short story Q.U.R.. Can a robot bartender make a perfect Three Planets drink? Only by watching detailed videos with high accuracy:
Quniby said, "Three Planets," and he [the robot] went into action. He had tentacles, and the motions were exactly like Guzub's...
...I got one of those new electronic cameras - you know, one thousand exposures per second... So we took pictures of Guzub making a Three Planets, and I could construct this one to do it exactly right down to the thousandth of a second. The proper proportion of vuzd, in case you're interested, works out to three-point-six-five-four-seven eight-two-three drops. It's done with a flip of the third joint of the tentacle on the down beat.
(Read more about Boucher's robot bartender)