Course detail

Mobile Robots

FSI-0MRAcad. year: 2023/2024

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

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. Ing. Radomil Matoušek, Ph.D.

Department

Institute of Automation and Computer Science (ÚAI)

Entry knowledge

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.

Rules for evaluation and completion of the course

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.
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.

Aims

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.

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.

Study aids

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 B-STR-P Bachelor's

    specialization AIŘ , 2. year of study, summer semester, elective

  • Programme BIT Bachelor's, 2. year of study, summer semester, elective
  • Programme BIT Bachelor's, 2. year of study, summer semester, elective

  • Programme IT-BC-3 Bachelor's

    branch BIT , 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

Ing. Tomáš Holoubek
Ing. Tomáš Hůlka
Ing. Martin Juříček
Ing. Tomáš Nevoral

Syllabus

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.