Course detail

Robotics (in English)

FIT-ROBaAcad. year: 2019/2020

Basic components of the stationary industrial robots. Kinematic chains. Kinematics. Solution of the inverse kinematic task. Singularities. Dynamics. Equations of motion. Path planning. Robot control. Elements and structure of the mobile robots. Models and control of mobile robots. Sensoric systems of mobile robots. Localization and navigation. Environment maps. Man-machine interface, telepresence. AI in robotics. Microrobotics.

Language of instruction

English

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

Ing. Jaroslav Rozman, Ph.D.

Department

Department of Intelligent Systems (UITS)

Offered to foreign students

Of all faculties

Learning outcomes of the course unit

The students acquire knowledge of current state and trends in robotics. Also, they acquire practical knowledge from construction and use of robots.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  1. Graded laboratories.
  2. Mid-term written test.
  3. Evaluated project with a defence.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To inform students about current state and future of robotics. Also, to inform students about peculiarities of robotic systems and prepare them for introduction of robotic systems to industry.

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

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2019, ISBN 9780262038485 (EN)

Recommended literature

Not applicable.

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MMI , 0 year of study, winter semester, elective
    branch MBI , 0 year of study, winter semester, elective

  • Programme IT-MGR-1H Master's

    branch MGH , 0 year of study, winter semester, recommended course

  • Programme IT-MSC-2 Master's

    branch MSK , 0 year of study, winter semester, elective
    branch MMM , 0 year of study, winter semester, elective
    branch MBS , 0 year of study, winter semester, elective
    branch MPV , 0 year of study, winter semester, elective
    branch MIS , 0 year of study, winter semester, elective
    branch MIN , 0 year of study, winter semester, compulsory-optional
    branch MGM , 0 year of study, winter semester, elective

  • Programme IT-MSC-2 Master's

    branch MGMe , 0 year of study, winter semester, compulsory-optional

  • Programme MITAI Master's

    specialization NIDE , 0 year of study, winter semester, compulsory
    specialization NBIO , 0 year of study, winter semester, elective
    specialization NSEN , 0 year of study, winter semester, elective
    specialization NVIZ , 0 year of study, winter semester, elective
    specialization NGRI , 0 year of study, winter semester, elective
    specialization NISD , 0 year of study, winter semester, elective
    specialization NSEC , 0 year of study, winter semester, elective
    specialization NCPS , 0 year of study, winter semester, elective
    specialization NHPC , 0 year of study, winter semester, elective
    specialization NNET , 0 year of study, winter semester, elective
    specialization NMAL , 0 year of study, winter semester, elective
    specialization NVER , 0 year of study, winter semester, elective
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NSPE , 0 year of study, winter semester, elective
    specialization NADE , 0 year of study, winter semester, elective
    specialization NMAT , 0 year of study, winter semester, elective
    specialization NISY , 0 year of study, winter semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Jaroslav Rozman, Ph.D.

Syllabus

  1. History, evolution, and current trends in robotics. Introduction to robotics. Robotic applications. Robotic competitions.
  2. Kinematics and statics. Direct and inverse task of kinematics.
  3. Path planning in the cartesian coordinate system.
  4. Effectors,sensors and power supply of robots. Applications of the cameras, laser distance meters, and sonars.
  5. Midterm test.
  6. Basic parameters of the mobile robots. Model and control of the wheel mobile robots.
  7. Robotic middleware. Robot Operating System (ROS), philosophy of ROS, nodes and communication among them.
  8. Maps - configuration space and 3D models. Probability in robotics. Introduction. Bayesian filtering, Kalman and particle filters. Model of robot movements and measurement model.
  9. Methods of the global and local localization. GPS based localization, Monte Carlo method.
  10. Map building. Algorithms for simultaneous localization and mapping (SLAM).
  11. Trajectory planning in known and unknown environment. Bug algorithm, potential fields, visibility graphs and probabilistic methods.
  12. Introduction to control and regulation.
  13. Multicopters, principle, control, properties, usage. Human - robot collaboration.

Laboratory exercise

6 hod., compulsory

Teacher / Lecturer

Ing. Daniel Bambušek

Syllabus

  1. Lego Mindstorms
  2. Basics of ROS, sensor reading
  3. Advanced work in ROS

Project

20 hod., compulsory

Teacher / Lecturer

Ing. Daniel Bambušek

Syllabus

Project implemented on some of the robots from FIT.