21.9.2020 News: Due to the covid-19 situation, the lectures as well as labs will be given online, via MS Teams (Team-Predmet-B201-B3M33MKR+BE3M33MKR) until further notice.

Wednesday 11:00-12:30, KN:E-126 Lecturers:

• Ing. Libor Přeučil, CSc. (LP) preucil@ciirc.cvut.cz
• RNDr. Miroslav Kulich, Ph.D. (MK), kulich@ciirc.cvut.cz

Wednesday 12:45-14:15 KN:E-230 (taught primarily in Czech)

Wednesday 14:30-16:00 KN:E-230 (taught in English)

Teaching assistants:

• Ing. Karel Košnar, Ph.D., karel.kosnar@cvut.cz
• Dr. Gaël Écorchard, gael.ecorchard@cvut.cz

The course introduces a basic mobile robot structure design together with control methods aimed to achieve autonomous and collective behaviours for robots. Methods and tool s for data acquisition and processing are presented herein with the overall goal to resolve the task of autonomous navigation for mobile robots comprising the tasks of sensor fusion, environmental modelling including Simultaneous Localization And Mapping (SLAM) approaches. Besides sensor-processing related tasks, methods for robot trajectory planning will be introduced. The central topic of the course stands in specific usage of the afore methods capable of execution with groups of robots and taking the advantage of their cooperation and coordination in groups. Labs and seminars are organized in a form of an Open Laboratory whereas the students will resolve the given problem in simulated environments as well as with real robot hardware.

• S. Thrun, W. Burgard, and D. Fox: Probabilistic Robotics. MIT Press, Cambridge, MA, 2005.
• A. Kelly: Mobile Robotics: Mathematics, Models, and Methods. Cambridge University Press, 2013.
• H. Choset, K. M. Lynch, S. Hutchinson, G. A. Kantor, W. Burgard, L. E. Kavraki, S. Thrun: Principles of Robot Motion: Theory, Algorithms, and Implementations (Intelligent Robotics and Autonomous Agents series), MIT Press, 2005.
• Borenstein, J., Everett, B., and Feng, L.: Navigating Mobile Robots: Systems and Techniques A. K. Peters, Ltd., Wellesley, MA, ISBN 1-56881-058-X, 1996.
• Dudek, G., Jenkin, M.: Computation Principles of Mobile Robotics, Cambridge University, Press, SBN 0521560217, 2000.

See the separate page.

• Getting the seminar credit - you will not be allowed to pass the exam without this one.
• Passing the oral exam.

• Continuous localization, ICP and its derivatives, Correlative Scan Matching
• Bayes filter and its derivation, KF & EKF, Particle filter, motion model, sensor model
• SLAM, online x offline SLAM, EKF SLAM, Fast SLAM, Rao-Blackwellization
• Multi-robot systems – taxonomy, taxonomy of task assignment, planning for MRS
• Multi-robot localization – maximum-likelihood estimation, particle filter, EKF