[Lisa_seminaires] SOCS Colloquium This Friday -- Dr. Nicholas Roy (MIT)

Dumitru Erhan erhandum at iro.umontreal.ca
Jeu 2 Avr 13:55:57 EDT 2009


See below for the abstract.

The talk is taking place this Friday (April 3rd) at McGill in the
McConnell building, room 13 between 15:30 - 16:30


---------- Forwarded message ----------
From: Joelle Pineau <jpineau at cs.mcgill.ca>
Date: Tue, Mar 31, 2009 at 10:16 PM
Subject: SOCS Colloquium This Friday -- Dr. Nicholas Roy (MIT)
To: aaron.courville at gmail.com


Dear All,

This Friday, Dr. Nicholas Roy, from MIT, will be
giving the weekly SOCS colloquium. You are all invited to attend.
Following the talk there will be refreshments in the SOCS lounge.

For an appointment with the speaker, please contact me directly:
jpineau at cs.mcgill.ca

Hope to see you there!

Best regards,

 Joelle


--------------------------------------------------------------------------------------
2009/04/03, MC13, 15:30 - 16:30

Planning and Learning in Information Space
Nicholas Roy, MIT

Abstract:

Decision making with imperfect knowledge is an essential capability for
unmanned vehicles operating in populated, dynamic domains. For example,
a UAV flying autonomously indoors will not be able to rely on GPS for
position estimation, but instead use on-board sensors to track its
position and map the obstacles in its environment. The planned
trajectories for such a vehicle must therefore incorporate sensor
limitations to avoid collisions and to ensure accurate state estimation
for stable flight -- that is, the planner must be be able to predict and
avoid uncertainty in the state, in the dynamics and in the model of the
world. Incorporating uncertainty requires planning in information space,
which leads to substantial computational cost but allows our unmanned
vehicles to plan deliberate sensing actions that can not only improve
the state estimate, but even improve the vehicle's model of the world
and how people interact with the vehicle.

I will discuss recent results from my group in planning in information
space; our algorithms allow robots to generate plans that are robust to
state and model uncertainty, while planning to learn more about the
world. I will describe the navigation system for a quadrotor helicopter
flying autonomously without GPS using laser range-finding, and will show
how these results extend to autonomous mapping and human-robot interaction.

Bio:

Nicholas Roy is the Boeing Assistant Professor in the Department of
Aeronautics & Astronautics at the Massachusetts Institute of Technology
and a member of the Computer Science and Artificial Intelligence
Laboratory (CSAIL) at MIT. He received his B.Sc. and M.Sc. from McGill
University, and his Ph. D. in Robotics from Carnegie Mellon University
in 2003. His research interests include autonomous systems, mobile
robotics, human-computer interaction, decision-making under uncertainty
and machine learning.


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