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DTSTART:20141026T030000
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RDATE:20151025T030000
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DTSTART:20150329T020000
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UID:calendar.7031.field_data.0@www.u-gov-ricerca.uniroma1.it
DTSTAMP:20260405T115532Z
CREATED:20150414T111535Z
DESCRIPTION:Who doesn't love a beautiful\, accurate\, and detailed 3D model
  built by a robot? And who doesn't love the challenge of planning and foll
 owing trajectories through high dimensional state spaces\, a challenge ena
 bled by these maps? The result of these approaches--- far too often-- is a
  slow\, brittle\, error-prone robot. For example: a data association error
  can cause the map to fail catastrophically\; planning in high-dimensional
  state spaces is very slow (best illustrated\, perhaps\, by the now-ubiqui
 tous '10x' speedup used in so many demonstration videos!)\; incorrectly es
 timating the shape of a translucent bottle leads to a failed grasp. In man
 y common cases\, contemporary systems can't compete with simple heuristics
 \; for example\, the easiest and most reliable way to get to the kitchen m
 ight be to follow the wall on the left until the robot reaches the second 
 door\; a grasp can often be achieved reliably by visual servoing and closi
 ng a gripper until a specified resistance is encountered. In this talk\, I
 'll describe how we're trying to build reliable\, simple\, and fast robots
 .  We don't abandon our modern methods--- in difficult cases\, a high-dime
 nsional planner operating on a 3D detailed model is the best way. Instead\
 , we see the problem as one of introspection: can the robot determine *whe
 n* it should use a simple method versus a more complex one? We'll elaborat
 e on these ideas and our initial efforts and results.Biography http://apri
 l.eecs.umich.edu/people/ebolson/ Edwin Olson is an Associate Professor of 
 Computer Science and Engineering at the University of Michigan. He is the 
 director of the APRIL robotics lab\, which studies Autonomy\, Perception\,
  Robotics\, Interfaces\, and Learning. His active research projects includ
 e applications to explosive ordinance disposal\, search and rescue\, multi
 -robot communication\, railway safety\, and automobile autonomy and safety
 .In 2010\, he led the winning team in the MAGIC 2010 competition by develo
 ping a team of 14 robots that semi-autonomously explored and mapped a larg
 e-scale urban environment. For winning\, the U.S. Department of Defense aw
 arded him $750\,000. He was named one of Popular Science's 'Brilliant Ten'
  in September\, 2012. In 2013\, he was awarded a DARPA Young Faculty Award
 .He received a PhD from the Massachusetts Institute of Technology in 2008 
 for his work in robust robot mapping. During his time as a PhD student\, h
 e was a core member of their DARPA Urban Challenge Teamwhich finished the 
 race in 4th place. His work on autonomous cars continues in cooperation wi
 th Ford Motor Company on the Next Generation Vehicle project.He is active 
 in the open source software community as one of the original developers of
  the message-passing system LCM\, and the creator of the OrcBoard robotics
  controller. Much of his current software is available under open source l
 icenses.Headshot: http://april.eecs.umich.edu/people/ebolson/headshots/DSC
 _6746.JPG
DTSTART;TZID=Europe/Paris:20150421T100000
DTEND;TZID=Europe/Paris:20150421T100000
LAST-MODIFIED:20150420T080459Z
LOCATION:Aula A3\, Via Ariosto 25
SUMMARY:Confessions from the SLAMmer - Edwin Olson\, University of Michigan
URL;TYPE=URI:http://www.u-gov-ricerca.uniroma1.it/node/7031
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