Course detail

Robotics

FEKT-MPC-RBTAcad. year: 2024/2025

The course builds on BPC-RBM and BPC-PRP, where students were introduced to the fundamental components of stationary and mobile robots and practiced programming them. This course begins with an overview of managing the development process of mobile robots, followed by several lectures covering the use of ROS2 and software simulators. The second half of the course focuses on well-known algorithms used in mobile robotics, particularly for localization, mapping, and navigation. All lecture content is reinforced in laboratory sessions, where students will program the movements of simulated mobile robots. The course concludes with topics such as motor control to achieve desired robot poses, algorithms for autonomous robot behavior, and modern trends in robotics, including AI, LLMs, and reinforcement learning (RL). While completing BPC-RBM and BPC-PRP is not a prerequisite, it is recommended for a more comprehensive understanding of robotics.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

prof. Ing. Luděk Žalud, Ph.D.

Department

Department of Control and Instrumentation (UAMT)

Entry knowledge

Knowledge at the bachelor’s level is required. Completion of BPC-RBM and/or BPC-PRP is an advantage but not necessary for successfully completing this course. Laboratory work is conditional on holding a valid qualification as a "knowledgeable person for independent activity," which students must obtain before the start of the course. Details about this qualification are provided in the Dean’s Directive on Student Familiarization with Safety Regulations.

Rules for evaluation and completion of the course

Structure of Point Evaluation (Total 100 Points):
  • Up to 40 Points – Assessment of laboratory exercises
  • Up to 60 Points – Written exam

Requirements for Course Credit and Exam Eligibility:

  • Attendance at all laboratory exercises (no unexcused absences)*
  • At least half of the points must be obtained for each individual laboratory exercise

Requirements for Passing the Exam:

  • Obtaining course credit
  • Scoring at least 25 points on the written exam (out of a maximum of 60 points)

* = Any absence from a laboratory exercise must be justified and properly excused (e.g., a doctor’s note). The student is then required to make up for the missed session during another time slot covering the same topic. If this is not feasible, the student must undergo an oral examination on the topic of the missed exercise. Up to 10 points can be awarded for this oral examination.

Aims

The course aims to prepare students to design an appropriate robotic platform for a mobile robot equipped with suitable computational units and utilizing the widely known robotic framework ROS2. Upon completion, students should be able to implement basic autonomous behaviors for a mobile robot within this framework, including localization, mapping, and planning. 

Study aids

All study materials are available in the course's e-learning platform. 

Prerequisites and corequisites

Basic literature

Laumond J.P.: Planning Robot Motion. Springer, 1997. (EN)
Russell S.-Norvig P., Artificial Intelligence a Modern Approach, ISBN 978-0-13-604259-4 Russell S.-Norvig P. 0isbn 978-0-13-604259-4 (CS)
Spong, M.-Vydyasagar, M.: Robot Dynamics and Control. J. Willey,1989. (EN)
Šolc,F.,Žalud,L.:"Základy robotiky", (CS)

Recommended reading

Not applicable.

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme MPC-KAM Master's 1 year of study, summer semester, compulsory-optional

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Miloš Cihlář
Ing. Tomáš Lázna, Ph.D.
Ing. Stanislav Svědiroh
prof. Ing. Luděk Žalud, Ph.D.
Ing. Tomáš Horeličan
Ing. Lukáš Kopečný, Ph.D.

Syllabus

P1: Úvod
P2: Stavba robotu
P3: Robot jako projekt
P4: Softwarové koncepce v robotice
P5: Robot Operating System I
P6: Robot Operating System II
P7: Simulátory
P8: Algoritmy lokalizace
P9: Reprezentace map a plánování tras
P10: Mapování a řízení mobilního robotu
P11: Behavior trees a stavové automaty
P12: Moderní přístupy v robotice 

Laboratory exercise

26 hod., compulsory

Teacher / Lecturer

Ing. Tomáš Lázna, Ph.D.
Ing. Miloš Cihlář
prof. Ing. Luděk Žalud, Ph.D.
Ing. Tomáš Horeličan
Ing. Stanislav Svědiroh
Ing. Lukáš Kopečný, Ph.D.

Syllabus

Cv1: Návrh mobilního robotu
Cv2: Nasazení a udržování robotu v systému Linux
Cv3: Robot Operating System
Cv4: Simulátor Webots
Cv5: Elementární lokalizační algoritmy
Cv6: Plánování tras
Cv7: Řízení mobilního robotu
Cv8: Behavior trees

Elearning

eLearning: currently opened course