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  \textbf{\Large{\textsc{STANFORD UNIVERSITY}}}\\[5pt]
  \textbf{\Large{\textsc{DEPARTMENT OF STATISTICS}}}\\[5pt]
  \Large{\textsc{DEPARTMENTAL SEMINAR}}
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4:15 p.m., Tuesday, October 23, 2007 \\ 
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  Sequoia Hall Room 200\\
  (Cookies at 3:45 in 1st Floor Lounge)
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  \textsl{Andrew Y. Ng} \\
  Computer Science Department \\
  Stanford University 
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  \subsection*{STAIR: The STanford Artificial Intelligence Robot project}
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\noindent

This talk will describe the STAIR home assistant robot project, and
several satellite projects that led to key STAIR components such as (i)
robotic grasping of previously unknown objects, (ii) depth perception from
a single still image, and (iii) apprenticeship learning for control.

Since its birth in 1956, the AI dream has been to build systems that
exhibit broad-spectrum competence and intelligence.  STAIR revisits this
dream, and seeks to integrate onto a single robot platform tools drawn
from all areas of AI including learning, vision, navigation, manipulation,
planning, and speech/NLP.  This is in distinct contrast to, and also
represents an attempt to reverse, the 30 year old trend of working on
fragmented AI sub-fields.  STAIR's goal is a useful home assistant robot,
and over the long term, we envision a single robot that can perform tasks
such as tidying up a room, using a dishwasher, fetching and delivering
items, and preparing meals.

STAIR is still a young project, and in this talk I'll report on our
progress so far on having STAIR fetch items from around the office.
Specifically, I'll describe: (i) learning to grasp previously unseen
objects (including its application to unloading items from a dishwasher);
(ii) probabilistic multi-resolution maps, which enable the robot to
open/use doors; (iii) a robotic foveal+peripheral vision system for object
recognition and tracking.  I'll also outline some of the main technical
ideas---such as learning 3-d reconstructions from a single still image,
and reinforcement learning algorithms for robotic control---that played
key roles in enabling these STAIR components.  In describing these
satellite projects, I'll also show our latest results on aerobatic
helicopter flight control and quadruped obstacle negotiation.


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