
The Future of Real-Time SLAM and “Deep Learning vs. SLAM” - ksashikumar
http://www.computervisionblog.com/2016/01/why-slam-matters-future-of-real-time.html
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irremediable
There's going to be a growing overlap between the two. I studied a bit[1] with
one of the big SLAM research groups in the UK, and even several years ago,
they were trying to combine SLAM and neural nets in various ways. A lot of
their PhD students went on to ride the crest of the "deep learning" wave, and
made a lot of money.

[1] Only an undergrad project a few years ago; I didn't do anything especially
cool there.

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andreyk
I think it's likely SLAM is one of those things (like Motion Planning) that
will continue to be done with more formally well understood algorithms, but
indeed will be integrated with Deep Learning for feature extraction/scene
understanding/many other things.

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vectored
I work in the intersection of these, though primarily from SLAM background.
The overlap between these communities has been increasing in the past two
years. While I think this is great, I also see that a lot of people working in
the field try to take Deep Learning as a 'one-stop' approach to solving SLAM.
This is worrying. Any particular methodology, if embraced without
understanding pros/cons, can lead to stagnation and local maxima. It was CRFs
before that, and Factor Graphs, Particle Filters, or EKF Slam before that.

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dannylowney
This is interesting for 2016.

