AIC Seminar Series
Autonomous Sensor and Action Model Learning for Mobile Robots
|Daniel Stronger||University of Texas at Austin||[Home Page]|
Notice: hosted by Charlie Ortiz
Date: 2008-04-22 at 16:00
Location: EJ228 (SRI E building) (Directions)
In order for a mobile robot to accurately interpret its sensations and
predict the effects of its decisions, it must have accurate models of its
sensors and actions. These models are typically tuned manually, a brittle
and laborious process. Autonomous model learning is a promising
alternative to manual calibration, but previous work has assumed the
presence of an accurate action or sensor model in order to train the other
model. This talk presents a novel methodology to enable mobile robots to
learn both their action and sensor models, starting without an accurate
version of either. This methodology is based on an adaptation of the
Expectation-Maximization (EM) algorithm, where the learned parameters are
the action and sensor models. The resulting technique is validated
experimentally on a Sony Aibo ERS-7 robot.
Please arrive at least 10 minutes early as you will need to sign in by
following instructions by the lobby phone at Building E. SRI is located
at 333 Ravenswood Avenue in Menlo Park. Visitors may park in the parking
lots off Fourth Street. Detailed directions to SRI, as well as maps, are
available from the Visiting AIC web page.
There are two entrances to SRI International located on Ravenswood Ave.
Please check the Builing E entrance signage.
©2014 SRI International 333 Ravenswood Avenue, Menlo Park, CA 94025-3493