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Course, academic year 2022/2023
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Probabilistic Robotics - NAIX101
Title: Pravděpodobnostní robotika
Guaranteed by: Student Affairs Department (32-STUD)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: summer
E-Credits: 6
Hours per week, examination: summer s.:2/2, C+Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Is provided by: NAIL101
Additional information: http://ktiml.mff.cuni.cz/~obdrzalek/vyuka/NAIL101/
Guarantor: RNDr. David Obdržálek, Ph.D.
Class: Informatika Mgr. - volitelný
Classification: Informatics > Software Engineering
Pre-requisite : {NXXX038, NXXX039, NXXX040, NXXX067, NXXX069}
Incompatibility : NAIL101
Interchangeability : NAIL101
Annotation -
Last update: T_KSI (13.05.2010)
During its life a robot deals with many problems: It wakes up - without knowing where it is. It is going - without knowing how and where. It is doing - without knowing what and why. These difficulties come from an inaccuracy of sensors and from a complexity of the real world, which cannot be accurately captured by a simple model. Our goal for this class is to familiarize ourselves with various algorithmic methods, which help us with dealing with the uncertainty originating from our and robot's ignorance.
Aim of the course -
Last update: RNDr. Jan Hric (07.06.2019)

TBA

Course completion requirements -
Last update: RNDr. Jan Hric (07.06.2019)

TBA

Literature - Czech
Last update: T_KSI (13.05.2010)

S. Thrun, W. Burgard, D. Fox: Probabilistic Robotics, MIT Press, 2005

S. Russel, P. Norvig: Artificial Intelligence: A Modern Approach, 3. vydání, Prentice Hall, 2009 (vybrané kapitoly)

Syllabus -
Last update: T_KSI (13.05.2010)
  • A reminder of probability theory
  • Kalman filters and their variants
  • Particle filters
  • Probabilistic localization and mapping
  • Decisioning and planning under uncertainty

 
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