2.166 Probabilistic Techniques for Mobile Robotics
Theory and application of probabilistic techniques for autonomous mobile robotics. Topics include probabilistic state estimation and decision making for mobile robots; stochastic representations of the environment; dynamic models and sensor models for mobile robots; algorithms for mapping and localization; planning and control in the presence of uncertainty; cooperative operation of multiple mobile robots; mobile sensor networks; application to autonomous marine (underwater and floating), ground, and air vehicles.
This class has 6.041 as a prerequisite.
2.166 will not be offered this semester. It will be available in the Spring semester, and will be instructed by J. J. Leonard.
Lecture occurs 3:00 PM to 5:00 PM on Mondays and Wednesdays in 35-308.
This class counts for a total of 12 credits.
© Copyright 2015 Yasyf Mohamedali