Course detail
Advanced Methods for Mapping and Self-localization in Robotics
FEKT-MPC-MAPAcad. year: 2023/2024
The concept of self-localization, navigation, mapping. Reference systems. Number of degrees of freedom. Self-localization and navigation - Odometry, inertial self-localization, global satellite navigation systems, navigation with proximity sensors - ultrasound sensors, lidars. Self-localization and navigation without map and with known map.
2D mapping - Robot evidence grids. Vectorization. Geometry maps. Indoor and outdoor 3D mapping. Multispectral mapping. Environmental mapping.
SLAM - simultaneous localization and mapping. 2D and 3D approach, problems, state-of-the-art.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Entry knowledge
Rules for evaluation and completion of the course
Aims
Succesful student of the course should be able to:
- Terms self-localization, navigation and mapping.
- Instrumentations and methods for indoor and outdoor localization and navigation.
- Methods for 2D and 3D map building, including multispectral and environmental maps.
- Basics of SLAM (Simultaneous localization and mapping) methods.
Study aids
Prerequisites and corequisites
- recommended prerequisite
Robotics
Basic literature
Recommended reading
Classification of course in study plans
- Programme MPC-KAM Master's 2 year of study, summer semester, compulsory-optional
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Pravděpodobnost, model senzoru a mapování.
3. Řízení pohybu a kinematika.
4. Částicový filtr.
5. Kalmánův filtr.
6. Plánování trajektorie.
7. SLAM – Simultánní lokalizace a mapování.
Laboratory exercise
Teacher / Lecturer
Syllabus
2. Model senzoru.
3. Řízení pohybu.
4. Částicový filtr.
5. Kalmánův filtr.
6. Plánování trajektorie.
7. Samostatná práce na projektu.