Course detail

Mobile Robots

FSI-0MRAcad. year: 2020/2021

The course explains basic techniques for the development of mobile robots. It addresses all necessary steps from initial design through simulation verification to the realization of an autonomous mobile robot. It is also intended for students who want to understand the basics principles of algorithms while solving simple engineering problems. The course consists of creating simple robotic projects in workgroups. Students are encouraged to intuitive approach while solving problems in the field of mobile robotics.

Language of instruction


Number of ECTS credits


Mode of study

Not applicable.

Learning outcomes of the course unit

Practical experiments are realized with support of commonly used hardware in mobile robotics and automotive (embedded systems, parking assistance sensors, etc.). The course is primarily designed for students interested in mobile robotics.


The course is intended for enthusiastic students with interests in mobile robotics. Some programming skills are welcomed as well as any knowlege about microcontrollers, sensors etc ... however, not required.


Not applicable.

Planned learning activities and teaching methods

Practical experiments are underway with support of commonly used hardware in mobile robotics and automotive (embedded systems, parking assistance sensors, etc.). The course is designed primarily for students interested in mobile robotics.

Assesment methods and criteria linked to learning outcomes

Credit requirements: active participation in laboratories and successful implementation of a group project in cooperation with the teacher. The project is defended by presenting in front of other students and ended with a practical demonstration of the implemented project. The evaluation is fully in competence of a tutor according to the valid directives of BUT.

Course curriculum

Not applicable.

Work placements

Not applicable.


The main objective of the course is to look behind the methods relating to mobile robots during practical realization of sample projects:

* explaining a relation of mobile robotics to the automotive industry

* deploying principles of embedded systems in mobile robotics (using the automotive HW, parking assistance, etc.)

* understanding the principles of programming using the Python programming language and embedded C.

Specification of controlled education, way of implementation and compensation for absences

Participation in laboratories is desirable in the case to fulfill the credits requirements. Teaching is divided according to weekly schedules. The form of compensation for missed seminars is fully at the discretion of the teacher.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Thrun, S., Burgard, W., Fox, D. (2005). Probabilistic robotics (Vol. 1). Cambridge: MIT press. (EN)
LaValle, S. M., "Planning Algorithms", Cambridge University Press (2006) (EN)

Recommended reading

Not applicable.


Classification of course in study plans

  • Programme B3S-P Bachelor's

    branch B-AIŘ , 2. year of study, summer semester, elective

  • Programme IT-BC-3 Bachelor's

    branch BIT , 2. year of study, summer semester, elective

  • Programme BIT Bachelor's, 2. year of study, summer semester, elective
  • Programme N-MET-P Master's, 1. year of study, summer semester, compulsory-optional

Type of course unit


Laboratory exercise

39 hours, compulsory

Teacher / Lecturer


1. Introduction to Mobile Robotics, currently solved problems.
2. Suitable platforms, used engineering tools.
3 Hardware peripherals, ultrasonic and infrared distance sensors.
4. Basic tasks for sensor processing, motion control methods, servo control.
5. Software tools suitable for the development of methods for intelligent mobile robot behavior.
6. Creation of simulation models of the robot and its environmental sensors.
7. Navigation methods of mobile robots.
8. Basic methods of localization, motion planning of the mobile robot.
9. Reaction to obstacles - detection and obstacle avoidance problem.
10. Path planning methods from the group of so-called. "Bug" algorithms.
11. Fundamentals of image processing methods from standard (web)cams.
12. Image processing devices with Android OS support.
13. Practical implementation of given autonomous mobile robots in laboratory conditions.