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Popis předmětu - BE3M33MKR

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BE3M33MKR Mobile and Collective Robotics Rozsah výuky:2p+2l
Garanti:Přeučil L. Role:PO,PV Zakončení:Z,ZK
Vyučující:Kulich M., Přeučil L.
Zodpovědná katedra:13133 Kreditů:6 Semestr:Z

Anotace:

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 implement some fundamental algorithms and study their properties on real data.

Osnovy přednášek:

1. Taxonomy of the localization problem. Continuous localization.
2. Probabilistic methods of localization 1 - Bayes filter
3. Probabilistic methods of localization 2 - KF, EKF, particle filter
4. Simultaneous localization and mapping (SLAM): EKF, PF, Rao-Blackwell
5. Graph SLAM.
6. Sensors used in mobile robotics.
7. Environment representation and modeling for mobile robotics (fundamental approaches, space decomposition, graph-based and hierarchical representations, occupancy grids)
8. Environment representation and path planning (overview, selection of an appropriate model and planning method, hierarchical planning, configuration space)
9. Probabilistic and special planning approaches (RRT, potential fields)
10. Planning under uncertainty (MDP, POMDP)
11. Multi-robot systems, aspects of their design, cooperation, coordination, communication.
12. Localization in multi-robot teams.
13. Processing of 3D information.
14. Current problems and challenges in mobile robotics.

Osnovy cvičení:

1. Labs organization, transformations
2. Iterative Closest Point (ICP)
3. Individual work (ICP) and consultation.
4. Individual work (ICP) and consultation.
5. Kalman filter (KF+EKF)
6. Individual work (KF+EKF) and consultation.
7. Particle filter (PF) and consultation
8. Individual work (PF) and consultation.
9. Individual work (PF) and consultation.
10. Individual work (PF) and consultation.
11. Rapidly Exploring Random Trees (RRT)
12. Individual work (RRT) and consultation.
13. Individual work (RRT) and consultation.
14. Individual work (RRT), grading.

Literatura:

R. Siegwart, I.R.Nourbakhsh, D.scaramuzza: Introduction to Autonomous Mobile Robots, MIT press, 2011.
S. Thrun, W.Burgard, D. Fox: Probabilistic Robotics. MIT press, 2005.
S. M.LaValle: Planning Algorithms. Cambridge University Press, 2006.
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.

Požadavky:

B3M33ARO/BE3M33ARO (Autonomní robotika)

Webová stránka:

http://cw.fel.cvut.cz/wiki/courses/ae3m33mkr/start

Klíčová slova:

mobilní robot, systémy více robotů, SLAM

Předmět je zahrnut do těchto studijních plánů:

Plán Obor Role Dop. semestr
MEKYR5_2016 Kybernetika a robotika PV 3
MEKYR2_2016 Senzory a přístrojová technika PV 3
MEKYR1_2016 Robotika PO 2
MEKYR4_2016 Letecké a kosmické systémy PV 3
MEKYR3_2016 Systémy a řízení PV 3


Stránka vytvořena 26.9.2017 05:47:18, semestry: L/2016-7, Z,L/2017-8, Z/2018-9, připomínky k informační náplni zasílejte správci studijních plánů Návrh a realizace: I. Halaška (K336), J. Novák (K336)
Za obsah odpovídá: doc. Ing. Ivan Jelínek, CSc.