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Course, academic year 2018/2019
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Practical Course in Robotics - NAIL110
Title in English: Praktikum z robotiky
Guaranteed by: Department of Theoretical Computer Science and Mathematical Logic (32-KTIML)
Faculty: Faculty of Mathematics and Physics
Actual: from 2015
Semester: summer
E-Credits: 6
Hours per week, examination: summer s.:1/3 MC [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Guarantor: Ing. Libor Přeučil, CSc.
RNDr. Miroslav Kulich, Ph.D.
Annotation -
Last update: T_KTI (07.05.2015)
The course focuses on acquiring practical experience with real robots and sensors. The aim is to mediate students with practical skills in design and engineering of an intelligent mobile robot solution in a complex task – problems like design of SW control architecture, sensor data fusion and processing, robot navigation, world model building, planning, and intelligent decision making will be introduced in an attractive form. Students are expected to solve a given complex task in a simulation environment as well as to port their solution onto a real mobile robot (UGV, UAV,...).
Aim of the course -
Last update: RNDr. Miroslav Kulich, Ph.D. (12.06.2019)

To acquaint students with practical aspects of the design of autonomous mobile robots.

Course completion requirements -
Last update: RNDr. Miroslav Kulich, Ph.D. (12.06.2019)

Presentation of the semestral work.

Literature -
Last update: T_KTI (07.05.2015)

[1] R. Siegwart, I. R. Nourbakhsh, D. Scaramuzza. Introduction to autonomous mobile robots, MIT press, 2011

[2] S. Thrun, W. Burgard, and D. Fox. Probabilistic Robotics. MIT Press, Cambridge, MA, 2005.

[3] S. M. LaValle, Planning Algorithms, Cambridge University Press, 2006.

[4] A. Kelly. Mobile Robotics: Mathematics, Models, and Methods, Cambridge University Press, 2014

Syllabus -
Last update: T_KTI (07.05.2015)

The course focuses on acquiring practical experience with real robots and sensors. The aim is to mediate students with practical skills in design and engineering of an intelligent mobile robot solution in a complex task - problems like design of SW control architecture, sensor data fusion and processing, robot navigation, world model building, planning, and intelligent decision making will be introduced in an attractive form.

Students are expected to solve a given complex task in a simulation environment as well as to port their solution onto a real mobile robot (UGV, UAV, or based on individual arrangement). Students will be provided with enough time for hands-on experimentation with the system and practical evaluation of the introduced solutions. The course targets gaining the practical experience why/when the elaborated approaches work and what are the principal constrains.

1. Task definition and assignment, its relationship to the context of mobile robotics

2. Planning on a binary grid

3. Robot control, obstacle avoidance

4. Mapping

5. Mobile robot localization

6. Action planning

 
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