This course aims at providing the students with the necessary mathematical background and the practical guidelines to tackle complex problems in state estimation and model identification for robots. At the end of this course the student will possess the necessary background to approach fundamental problems in robotics including, but not limited to localization, simultaneous localization and mapping (SLAM), calibration, tracking.
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Every Wednesday: 14.00-17.00
Despite this course in the "manifesto" is scheduled for the first year of the MARR/AIRO studies, it requires reasonably solid notions of Linear Algebra, Robotics 1 (or their italian versions Geometria and Robotica 1) and Autonomous and Mobile Robotics. For this reason, we recommend the students to sustain the exam on the second year.
When: first semester (about 12 weeks)
Wednesday 16:00-19:00, Room A6
Thursday 14:00-16:00, Room A6
Where: Dip. Informatica e Sistemistica, Sapienza University of Rome.
Via Ariosto 25, I-00185, Rome, Italy.
ECTS Credits: 6
How to complete the credits for this module: After attending classes, students should:
IMPORTANT NOTE: from this academic year it will NOT be possible to sustain Probabilistic Robotics as 2 modules of Elective in AI or Elective in Robotics.
Next Exams
Week 1: Intro, Sensors, Mobile Platforms, Probability
Week 2: Manipulating PDF
Week 3: Dynamic Systems, Filtering, Discrete Filters
Week 4: Kalman Filters
Week 5: Gaussian Filters
Week 6: Wrapup on Filtering and Applictions: Localization and SLAM
Week 7: Least Squares Estimation
Week 7: Least Squares Estimation, Applications: Calibration, Sensor Registration
Week 8: Sparse Least Squares
Week 9: Applications of Sparse Least Squares: Graph-SLAM
Week 10: Data Association
Week 11: Wrapup and Applications