Intro Motivation Magnify 360 screenshots proably not the Facebook Screenshots

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2008-2009 Magnify360 Computer Science
ClinicOptimizing Individual Web Experiences
Magnify 360 logo
User Experience
Treating visitors as individuals
Evaluation
Underlying System
These robots were shown with Mapping for All, an
exhibit at AAAI 2008. At left is the One Robot
Per Child project, where an OLPC provides control
and sensing.
Intro / Motivation / Magnify 360 screenshots
(proably not the Facebook Screenshots down to
here
Because of the markers' format, color dominates
the visual processing in our system. The vision
software allows for quick recalibration of the
color definitions that distinguish one object
from another. Once defined, the colors provide
distinct patches from which connected components
are extracted. Vertically aligned components form
markers.
One of the sensitivity graphs
the table
Caption
Caption for the three screenshots and labels,
above
These robots were shown with Mapping for All, an
exhibit at AAAI 2008. At left is the One Robot
Per Child project, where an OLPC provides control
and sensing.
caption
Explanation robot combines several partial
behaviors, e.g., for wall-following, marker
detection and approach, and recovery from
unexpected obstacle bumps. A finite state machine
arbitrates among these behaviors based on the
current sensory input and current goals.
Feedback is available to observers through the
laptop's voice synthesizer and/or network access
from a second machine.

• Explain stuff
• bullet list 1
• bullet list 2
• bullet list 3

Results
From clickstream data Profiles
caption
An unusual feature of our robot, Import
Antigravity, is that its computation comes from
an ordinary Mac laptop held by a custom-designed
platform. The advantage of using off-the-shelf
computation is that networking, the development
environment, and interface with ordinary
peripherals requires no additional setup. For
example, the Create itself is simply a serial
peripheral of the Mac it is carrying.
Clustering Users
Classification and Testing
caption
caption
Explanation robot combines several partial
behaviors, e.g., for wall-following, marker
detection and approach, and recovery from
unexpected obstacle bumps. A finite state machine
arbitrates among these behaviors based on the
current sensory input and
The range sensors available on the simulated
robot were lasers with 1 degree of angular
resolution. with that much data, it is possible
to recognize locations, for example, through the
range signatures of each of the four corners of
the room.
Caption
Explanation robot combines several partial
behaviors, e.g., for wall-following, marker
detection and approach, and recovery from
unexpected obstacle bumps. A finite state machine
arbitrates among these behaviors based on the
current sensory input and
These robots were shown with Mapping for All, an
exhibit at AAAI 2008. At left is the One Robot
Per Child project, where an OLPC provides control
and sensing. and here
caption
Acknowledgments
Caption for the table and profile graphics and
labels, above
Magnify360 Liaisons David Lapayowker '09 Marissa
Quitt '09 Elaine Shaver '09 (PM) Devin Smith '09
Team Members David Lapayowker '09 Marissa Quitt
'09 Elaine Shaver '09 (PM) Devin Smith '09
Explanation robot combines several partial
behaviors, e.g., for wall-following, marker
detection and approach, and recovery from
unexpected obstacle bumps. A finite state machine
arbitrates among these behaviors based on the
current sensory input and
An unusual feature of our robot, Import
Antigravity, is that its computation comes from
an ordinary Mac laptop held by a custom-designed
platform. The advantage of using
Faculty Advisor Zachary Dodds
Caption