
Mapping at Aurora - lasryaric
https://medium.com/aurora-blog/the-atlas-our-hd-mapping-system-262e7b0fadd1
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dtran
I don't have much background knowledge in mapping or self-driving, so I
thought this was well-written in a way that anyone could understand! Re:
breaking down the data framework into world geometry vs. semantic annotations—
that makes sense, but how often would you need to update the annotations? Just
running and biking around San Francisco, I feel like there's no shortage of
construction that create changes to lanes/stop signs/lights and rules of
traffic flow. How do you account for these, or would world geometry data be
enough here?

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gregcoombe
I think you've hit upon one of the most challenging aspects of mapping, which
is that the real world is incredibly dynamic. And it's not just the things
that we think of as dynamic (bicyclists, pedestrians, other vehicles), it's
also the geometry itself (lane lines, vegetation, building construction). So
this requires some form of updating (either semantic, geometric, or both). And
as you pointed out this is not uniform: dense city maps can change from week-
to-week, whereas rural maps require less frequent updates. So first you need
to build an on-board/offline system that can first detect these changes, then
configure the pipeline so that the proper data is collected and updates can be
compact and fast. As mentioned in the article, we have a git-like structure
for Atlas updates which allows us to track small changes. And the fact that
the Atlas is only locally consistent means that any update is contained just
to the detected area.

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Scobleizer
Is there a way to know the "freshness" of the data? Obviously if I'm driving
and a car in front of me just imaged the road I can be much more reasonably
certain that there isn't any debris on the road surface, or new potholes that
have opened up.

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gregcoombe
I think that there is grey-area between data that is sufficiently static to
represent in a map (buildings, lane lines) and data that is dynamic and must
be handled by on-board perception systems (pedestrians, road debris). A good
way to think of this is that the map is encoding priors about the environment
for use by the perception system. It may be possible in the future to do all
of this on-board (like humans do!) but the computational constraints would be
quite high.

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gregcoombe
To add to this: it's not just computational complexity, but it's also about
safety. There is a human review process for every element of the map, which
enforces a level of quality and safety that is extremely difficult to ensure
from a fully on-the-fly system.

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gregcoombe
Hi all! I'm Greg and I work on the Mapping Team at Aurora. I'd be happy to
answer any questions about the article and mapping for self-driving.

