
Google Wants to Solve Robotic Grasping by Letting Robots Learn for Themselves - Osiris30
http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/google-large-scale-robotic-grasping-project
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ryanjshaw
I always thought this was the only way to build a true AI -- build a 'virtual
baby' that has to go through much the same experiences as a human baby. I'm
sure this idea has been explored somewhere already - anybody have any
pointers?

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jackhack
This is precisely the approach taken at MIT under Prof. Rod Brooks: "Within
our group, Marjanovic, Scassellati & Williamson(1996) applied a similar
bootstrapping technique to enable the robot* to learn to point to a visual
target. " *named Cog, short for "Cognition"

[http://people.csail.mit.edu/brooks/papers/CMAA-
group.pdf](http://people.csail.mit.edu/brooks/papers/CMAA-group.pdf)

If I may paraphase, his model is biologically inspired -- believing
hierarchical layers of behaviours, lack of a central planning model
(distributed processing), and physical and temporal placement in the world
(rather than abstractions of the world, or observe/process/react loops) are
essential to the formation of a truly intelligent machine.

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rm_-rf_slash
I have long believed that we aren't going to get an AI that matches biological
intelligence until it has to fend for itself. Nearly every biological function
is linked to the fundamental need to survive through scarcity in hostile
environments in order to reproduce and pass along genetic material. Without
that need, there would not have been such rigorous evolutionary arcs that
ultimately brought humans to this earth.

The question of course, is, how could we deal with the implications of not
just creating a smarter computer, or new life, but an entirely new and
unprecedented class of life?

For one thing, if they're so great, why bother keeping us around?

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peterwwillis
There are plenty of organisms on the planet that co-exist with more powerful
ones and they don't attempt to wipe out the other. There would need to be such
fierce competition over natural [or unnatural] resources that only one of the
two organisms could exist, and then competition would give rise to a potential
outcome of one extinguishing the other. Your question is simply an irrational
fear, probably on the order of probability much less likely than us being
wiped out by an asteroid.

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JoeAltmaier
Plenty of biological organisms. That have niches in the biosphere. But this
new life is/has neither. It could decide to cannibalize the earth to fuel a
spacefaring civilization for instance. Not an irrational fear.

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rm_-rf_slash
Or perhaps more simply, eradicate humanity to ensure the survival of the
planet. Crude but effective. And final.

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p1mrx
Nothing is final. Even without humans, the Earth will be engulfed by the sun
in a few billion years.

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jing
Are physics engines not yet accurate enough to enable "virtual" pre-training /
full training of the networks, lighting conditions, etc? If they are,
exclusively using physical robots seems somewhat inefficient.

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tgflynn
That's a very interesting question. My guess is that the physics of grabbing
things, especially non-rigid things, is very messy and difficult to simulate.
It would be great if someone here were able to give a detailed answer to this
question though.

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iandanforth
Ok here goes.

1\. The best / most recent attempt at this was for the DARPA robotics
challenge and the Gazebo simulator.

This was still very buggy and prone to hilarious / depressing physics.

2\. Almost all game physics engines start from rigid body and slap on
particles, deformables, etc.

An exciting counter example to this is nVidia Flex which starts with unified
particle simulation (much closer to molecular dynamics simulation used for,
you know, real work).

3\. From the perspective of AI, accurate simulation might not be required.

Intelligence requires complexity and a certain degree of predictability. So as
long as you can build a rich and consistent / learnable world then whatever
simulation you have could be super useful.

From the perspective of transferring that knowledge into a robot though you
need accurate physics.

4\. Natural touch sensors are hard to do in rigid body simulators but are
super important to naturalistic learning.

There's a ton of information that your sense of touch and body position
provide about how the world works, and getting the tens of thousands of soft-
contact touch points simulated you need for this kind of sensing is pretty
challenging today.

Lots of physics engines do all sorts of things to minimize contact points, or
ignore them if there's no motion. You have to work against optimization a lot
if you want mechanoreceptors and proprioception.

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jonnycowboy
I agree with all the points you made but in addition I would add another -
with external cameras for positioning and movement feedback, you don't need to
have accurate geartrains or encoders nor have a rigid robot. Since the
localization is all in software (and software is scalable/free from Google's
standpoint) there are potentials for lots of weight and cost savings on the
hardware side. Kind of like my robot:
[https://github.com/jonnycowboy/YARRM](https://github.com/jonnycowboy/YARRM)

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rboyd
I was hoping to use a robotic arm for a project I'm working on, and wondering
if you guys could answer a question about motors. In my very limited research
it looked like one of the factors that make the industrial (kuka, etc) robots
so expensive was that they use backlash-free motors. What does that even mean?

I also saw a couple startups aimed at sub-$5k robots (like carbon.ai). Are
they solving this problem in some novel way?

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monknomo
Backlash free motors are motors where the output shaft begins moving as soon
as the motor starts moving. In particular, when the motor reverses direction
there is no "slack" to pick up before the output shaft starts to move. The
slack is called backlash when talking about gears and motors and what have
you.

It's important for robots to not have backlash, because as movements are
repeated, each bit of backlash adds up into a potentially big cumulative
error. It could end up with the robot operating outside of the intended design
envelope, which might be a safety problem.

I don't know what the startups are doing.

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tgflynn
Wouldn't that only be a problem with open loop control though ? If you have an
encoder and use feedback would backlash still be an issue ?

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monknomo
We're getting outside of my home hobbyist experience here, but I think you
could guarantee the robot would be in a particular position, but the backlash
might make it hard to say when the robot will get to the particular position.
Using encoders on all the motors would require having inputs for each encoder,
which can get complex.

My guess is you can go pretty far with janky parts if you don't run for long
periods of time and also measure where they are.

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acd
Is this similar to Berkely Brett?
[https://www.youtube.com/watch?v=JeVppkoloXs](https://www.youtube.com/watch?v=JeVppkoloXs)

Brett robot folding clothes.
[https://www.youtube.com/watch?v=Thpjk69h9P8](https://www.youtube.com/watch?v=Thpjk69h9P8)

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Animats
This is the bin-picking problem, which has been worked on since the 1980s. For
objects of known shape, it's more or less solved.[1] The general case is still
a problem. It's good to see Google making progress with this.

[1]
[https://www.youtube.com/watch?v=TU71MtDC-4E](https://www.youtube.com/watch?v=TU71MtDC-4E)

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smegel
That sounds like...machine learning!

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basicplus2
Steve Grand.. this is the man for the Job

I can't recomend his book enough "Growing up with Lucy"

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logicallee
in the future we will fondly remember the simple times of the 2010's, where
you could "solve x" ... by just "letting robots learn for themselves..."

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effry-much
Not a good idea giving some form of level III consciousness to the robots.

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forgotAgain
So how does the robot know it's supposed to pick up the object?

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jonnycowboy
Reinforcement learning (ie: bigger score/reward) the more objects are
correctly grasped.

