Robots!

Robots!

Zach Dodds June 16, 2010

Cheap Robots

expense

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automation...

... vs. autonomy

Autonomous robotics ~ Brazil

autonomous vehicles

DARPA grand challenge

iRobot Roomba ~ 2002

wide-audience robots?

4,000,000+ vacuums 3,000+ PackBots

iRobot Roomba ~ 2002 Rodney Brooks

another iRobot founder

4,000,000+ vacuums 3,000+ PackBots

similar revenue!

Today's capabilities

~~personal robots

personal computers

next-generation applications

Key challenge:

spatial reasoning

but local, not global

the 2000's saw almost all of our progress in robot mapping and navigation

CMU's Boss

Primary sensor: the laser

Personal lasers?

Spatial reasoning today

one view or

two?

Laser Range Scanners

$2000 - $10000 and up $200 - $10 and down

Webcameras

Laser vs. Pixels

Laser Range Scanners

$2000 - $10000 and up $200 - $10 and down

Webcameras

Laser vs. Pixels: Data

Laser Range Scanners

$2000 - $10000 and up

Laser vs. Pixels: Data

Laser Range Scanners

$2000 - $10000 and up $200 - $10 and down

WebcamerasBeautifu

l Data!

More data -- but

more "tangled."

Untangling pixels: 3d from 2d

Where does the additional information come from?

Untangling pixelsIdeas for extracting 3d data from 2d

images?

Untangling pixelsIdeas for extracting 3d data from 2d

images?

via multiple images via image context

image 1 image 2

(x,y,)Nearby

Far off

feature matches

K. Wnuk, '05

+ texturepoint cloud

Microsoft's Photosynt

h

Is anything missing from these 3d reconstructions?see links...

Doing less with less!

Strategy for robots:

a visual compass from 1d image matching: Devin S., 2008

frame 470 frame 485

Where's the ground in front of

me?

intensity profiles did not work

Trickier than it may seem!

Where's the ground in front of

me?

Trickier than it may seem!

Artist Julian Beever

Texture-based 3d: Make3d

textures ~ 524 components

Not feeling so bad... the platform

depth!

Texture-based 3d: Make3dSaxena and Ng 2006

RC car control!

C. Plagemann et al., 2008

Laser-scan data from images?

robot platform "omnicam" images errors...

Best algorithm ~ 1 meter error

Laser-scan data from images?

robot platform "omnicam" images errors...

Our investigation in 2009

Image-patches estimating dense ranges

100 hand-labeled imageslearned textures

travers

able

untr

avers

able

Our approach: 2009

deep belief networkfeedforward net

with backpropagation

Results of groundplane learning

where/why would feature-matching reconstruction fail in these examples...?

Segmentation

Image height ~ distances?

automatic (blue) vs. “correct” (red and green) segmentations

How do these

relate?

What will be the effects of

mis-segmenting?

good news and bad news?

Accuracy

automatic (blue) vs. “correct” (red and green) segmentations

9-image trial setMedian error < 10cmMean error > 500cm!

Opportunity!

"drop outs" and "drop ins"

PixelLaser True scan

I <3 Cheap Robots!

• research challenges

• fun projects!• broad application reach

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audience

Preview of coming sensor attractions

will it work...?will it replace vision...?

The future is small... ?DARPA will be ready if it's true.

See obstacles around them

Powerslide

another...

Fly through windows

A. Amert, N. M'Tarrah, D. Halloran '10

class projects

camera?

class projects

M. Badger and C. Gaudet '10

B. Green, K. Burgers, S. Lakhani '11

in core Biology/CS: M. Morabe and T. Luke '13

Please don't eat the wheels. You don't know where they've been.

The name "Nutty" derives from our original plan to use peanut butter cookies as wheels. However, we were too grossed out by the smell of

day-old peanut butter cookies, so we opted for other types...

Autonomous Vehicles : Fall

2010

student-run FIRST

scrimmage

energy autonomy

3d from 2d

laser range finder

camera

More is possible! How...

3d from 2d

laser range finder

camera

More is possible! How...

packbot parts