AE3M33MKR: Mobile and and Collective Robotics (winter term 2016/17)


Wednesday 9:15-10:45, KN:E-128 (K3), Lecturers:


Wednesday 12:45-14:15 KN:E-132, Teachning assistants:

Course description

The course introduces a basic mobile robot structure design together with control methods aimed to achieve autonomous and collective behaviors 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 modeling 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 a real robot HW.



Week Topic Slides
1.Course introductions, Taxonomy of the localization problem, continuous localization. (MK) Slides
2.Probabilistic methods of localization (MK)Slides
4.SLAM. (MK)Slides
5.Localization in multi-robot teams. (MK)Slides
6.Architectures of a mobile robot, sensors used in mobile robotics. (LP)
7.Kinematics of a mobile robot, trajectory control. (LP)
9.World models and their building. (LP) Slides
10.Introduction to planning in mobile robotics. (LP) Slides
11.Planning under uncertainty. (LP) Slides
12.Probabilistic methods to planning (RRT). (LP) Slides
13.Multi-robot systems, aspects of their design, cooperation, coordination, communication. Swarms. (MK) Slides

Slides from the lectures will appear here just before they are presented.

  • 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.

Content of seminars

Týden Téma
1.Labs organization, transformations
2.Iterative Closest Point (ICP)
3.Individual work (ICP)
7.Kalman filter (KF+EKF)
8.Individual work (KF+EKF)
10.Particle filter (PF)
11.Individual work (PF)
14.Individual work (PF), grading.

Organization of labs

See the separate page.

Credit allowance conditions

  • Getting the seminar credit - you will not be allowed to pass the exam without this one.
  • Passing the oral exam.
courses/ae3m33mkr/start.txt · Last modified: 2017/01/30 13:02 by kulich