Table of Contents
Lectures 2025
Lectures take place every Monday from 11:00-12:30 in KN:E-107.
| Week | Date | Lecturer | Block | Topics | Presentations |
|---|---|---|---|---|---|
| 1 | 17.02.2025 | KZ | INTRO | Introduction: course organization, prerequisites and problem definition | 00_aro_outline.pdf 01_problem_definition.pdf lecture_01_recording |
| 2 | 24.02.2025 | KZ | PERCEPTION MODELING | How to fuse almost anything: MAP, MLE, LS, 1D SLAM and factor graphs | 00_1d_mle.pdf lecture_02_recording lecture notes |
| 3 | 03.03.2025 | KZ | PERCEPION MODELING | Where the hell am I, and where is the stuff around me? SLAM in SE(2) with (i) measurement models of 2D/3D marker detectors, UWB, GPS/GNSS, odometry, and (ii) differential drive motion model | 00_1d_mle.pdf 00_2d_mle.pdf lecture_03_recording |
| 4 | 10.03.2025 | KZ | PERCEPTION MODELING | Can I build a map without markers? SLAM with lidar and camera and its efficient optimization on SE(2)/SE(3) manifolds (Absolute orientation, Camera localization/calibration, Levenberg-Marquardt) | monoforce_2025.pdf 00_absolute_orientation.pdf 01_icp.pdf lecture_04_recording |
| 5 | 17.03.2025 | KZ | PERCEPTION OPTIMIZATION | Optimization: Gauss_newton, Levenberg-Marquardt, Trust region methods, RANSAC | 00_optimization_se2.pdf 01_ransac_simplified.pdf lecture_05_recording |
| 6 | 24.03.2025 | KZ | PERCEPTION OPTIMIZATION | Filtering: Bayes and (Extended) Kalman filter | 00_kf.pdf 01_ekf.pdf lecture_06_recording |
| 7 | 31.03.2025 | KZ | PERCEPTION OPTIMIZATION | Beyond normal distributions: Non-parametric pdfs with Discrete Bayes filter and Particle Filter | 00_bayes_filter.pdf 01_partical_filter.pdf 02_uncertainty_estimation.pdf |
| 8 | 7.04.2025 | VV | PLANNING | Exploration, world maps | exploration.pdf Lecture_08_recording |
| 9 | 14.04.2025 | VV | PLANNING | Introduction to motion planning, Combinatorial motion planning | motivation.pdf, basics.pdf Lecture_09_recording |
| 10 | 21.04.2025 | - | —- Easter holidays —- | ||
| 11 | 28.04.2025 | VV | PLANNING | Combinatorial and Sampling-based motion planning I | combinatorial.pdf, sampling1.pdf Lecture notes , Lecture_11_recording |
| 12 | 05.05.2025 | VV | PLANNING | Sampling-based motion planning II | sampling2.pdf, Lecture_12_recording , Lecture notes |
| 13 | 12.05.2025 | VV | PLANNING | Sampling-based motion planning III | sampling3.pdf, Lecture_13_recording |
| 14 | 19.05.2025 | VV | PLANNING | Data structures for motion planning | sampling-datastructures.pdf, sampling-mppi.pdf Lecture_14_recording |
Recordings of particular lectures are available here.
Playlist for planning videos (selected animations from the slides): Videos
OLD Lectures 2024
Lectures take place every Monday from 11:00-12:30 in KN:E-107.
| Week | Date | Lecturer | Topics | Presentations |
|---|---|---|---|---|
| 1 | 19.02.2024 | KZ | Introduction: course organization, prerequisites and problem definition | 00_aro_outline.pdf 01_problem_definition.pdf  lecture_01_recording |
| 2 | 26.02.2024 | KZ | How to fuse almost anything: Localization and factor graphs | 00_localization_mle.pdf lecture_02_recording ☆lecture_notes_02 |
| 3 | 04.03.2024 | KZ | Where the hell am I, and where is the stuff around me? SLAM in SE(2) with (i) measurement models of 2D/3D marker detectors, UWB, GPS/GNSS, odometry, and (ii) differential drive motion model | 00_localization_se2.pdf lect_03_recording |
| 4 | 11.03.2024 | KZ | How can I find myself without markers? SLAM with lidar and camera and its efficient optimization on SE(2)/SE(3) manifolds (Absolute orientation, Camera localization/calibration, Levenberg-Marquardt) | 00_absolute_orientation.pdf 01_icp.pdf lect_04_recording |
| 5 | 18.03.2024 | KZ | Do I really need to remember all that stuff forever? Kalman filter | 00_kf.pdflect_05_recording ☆ lecture_notes_05_06 |
| 6 | 25.03.2024 | KZ | Maximum aposteriori estimate in real-time: Extended Kalman filter, Gauss_newton, Levenberg-Marquardt, Trust region methods | 01_ekf.pdf 00_optimization_se2.pdf lec_06_recording |
| 7 | 01.04.2024 | - | —- Easter holidays —- | |
| 8 | 8.04.2024 | VV | Exploration, introduction to motion planning | 2024-exploration.pdf, 2024-planning-basics.pdf, Videos |
| 9 | 15.04.2024 | KZ | Beyond normal distributions: Robust regression + RANSAC, Non-parametric pdfs with Bayes filter Learning in robotics: Advanced optional lecture that assumes prior knowledge of deep-learning concepts. | 00_bayes_filter.pdf 01_partical_filter.pdf 02_ransac_simplified.pdf lec_09_recording☆ lecture_notes_09 |
| 10 | 22.04.2024 | VV | Combinatorial motion planning | 2024-planning-combinatorial.pdf Videos |
| 11 | 29.05.2024 | VV | Sampling-based motion planning I | 2024-planning-samplingi.pdf |
| 12 | 06.05.2024 | VV | Sampling-based motion planning II | 2024-planning-samplingii.pdf |
| 13 | 13.05.2024 | VV | Sampling-based motion planning III | 2024-planning-samplingiii.pdf, 2024-planning-mppi.pdf |
| 14 | 20.05.2024 | VV | Data structures for motion planning | 2024-planning-datastructures.pdf |
Recordings of particular lectures are available here.
Lecturers
Karel Zimmermann (KZ) is the main lecturer and associate professor at the Czech Technical University in Prague. He worked as postdoctoral researcher with the Katholieke Universiteit Leuven (2008-2009) in the group of prof Luc van Gool. His current H-index is 13 (google-scholar) and he serves as a reviewer for major journals such as TPAMI or IJCV and conferences such as CVPR, ICCV, IROS. He received the best lecturer award in 2018, the best reviewer award at CVPR 2011 and the best PhD work award in 2008. His journal paper has been selected among 14 best research works representing Czech Technical University in the government evaluation process (RIV). Since 2010 he has been chair of Antonin Svoboda Award (http://svobodovacena.cz). He was also with the Technological Education Institute of Crete (2001), with the Technical University of Delft (2002), with the University of Surrey (2006). His current research interests include learnable methods for robotics.
Vojta Vonásek (VV) is the second lecturer and PostDoc researcher at the Department of Cybernetics.
He spent one year at Karlsruhe Institute of Technology (KIT) at the institut IAR/IPR. He was a post-doc researcher at the Institut für Werkzeugmaschinen und Fabrikbetrieb, Technische Universität Berlin, Berlin, Germany within German Academic Exchange Service (DAAD) post-doc programme in 2017. He serves as the reviewer for robotic journals (Autonomous Robots, IEEE Robotics and Automation Letters, International Journal of Automation and Computing, Robotics and Autonomous Systems, ..) and many conferences. His research interests include path and motion planning, automatic learning of locomotion gaits of modular robots and application of motion planning techniques in computational biochemistry.