The course gives an introduction to Bayes Filtering, and presents an application of Extended Kalman Filtering to vision-based geometric modeling of a scene (a.k.a. SLAM), e.g., for mobile robotics applications. The EKF vision-based SLAM part will be given in consecutive days, so to allow students already skilled in Bayes Filtering to take only this part.
Foundations of Robotics
This course introduces to autonomous (mobile) robotics. Beginning in 2009 (source: International Federation of Robotics) the business of service robotics overcame the industrial robotics one. A further strong increase is expected in the next years for this field, which is characterized by specific competencies.
This course deals with interfacing devices to microcontrollers as well as their programming. See the course website for more details; the website for the course given in 2011/12: Informatica Industriale / Informatics for Industrial Applications 2011/12.
Computer Vision is relevant for many areas, e.g., video-surveillance (ambient intelligence, vehicle and/or pedestrian traffic monitoring), industrial robotics, autonomous robotics, etc. The course, given the limited amount of time, aims at introducing to some basic techniques of computer vision: projection modeling, 3D reconstruction from stereo and motion (tracking).
The Soft Computing course presents a set of techniques for the determination of approximate solutions to optimization problems, in situations of imperfection, un-accurateness or un-completeness of the available information. The presented techniques refer to evolutive algorithms, to neural networks (in the parts non covered by the mandatory courses of the 1st year of the laurea magistrale) and to fuzzy systems.
This course deals with representation of roto-translations, a prerequisite for living in robotics, the a few relevant issues in robotics are introduced: kinematics of articulated series of bodies, control of articulated series of bodies, sensors for robotics, robot programming.