Course detail

Robotics

FIT-ROBaAcad. year: 2017/2018

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

Mode of study

Not applicable.

Guarantor

Ing. Filip Orság, 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

There are no prerequisites

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Course curriculum

    Syllabus of lectures:
    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. Models and control of the stationary robots.
    5. Effectors,sensors and power supply of robots. Applications of the cameras, laser distance meters, and sonars.
    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.
    9. Probability in robotics. Introduction. Bayesian filtering, Kalman and particle filters. Model of robot movements and measurement model.
    10. Methods of the global and local localization. GPS based localization, Monte Carlo method.
    11. Map building. Algorithms for simultaneous localization and mapping (SLAM).
    12. Trajectory planning in known and unknown environment. Bug algorithm, potential fields, visibility graphs and probabilistic methods.
    13. Introduction to control and regulation.

    Syllabus of laboratory exercises:
    1. Lego Mindstorms
    2. Basics of ROS, sensor reading
    3. Advanced work in ROS

    Syllabus - others, projects and individual work of students:
    Project implemented on some of the robots from FIT.

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

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

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

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
    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-MGR-1H Master's

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