Course detail

Robotics (in English)

FIT-ROBaAcad. year: 2022/2023

Basic components of the stationary industrial robots. Kinematics. Solution of the inverse kinematic task. Equations of motion. Path planning. Elements and structure of the mobile robots. Models and control of mobile robots. Sensoric systems of mobile robots. Localization and navigation. Environment maps. Robot control.

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, programs 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.

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, creation and maintaining of robotic systems into practice.

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

There are compulsory projects and laboratories that follow on from the projects.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Siegwart, R. a Nourbakhsh, I. R.: Introduction to Autonomous Mobile Robots. MIT Press, 2011. ISBN-13: 978-0262015356 

(EN)

Thrun, S., Burgard, W. a Fox, D.: Probabilistic Robotics. MIT Press, 2005. ISBN 0-262-201623 

(EN)

Choset, H., Lynch, K. M., Hutchinson, S. et al.: Principles of Robot Motion. MIT, Press, 2005. ISBN 0-262-03327-5. 

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

Šolc, F.: Robotické systémy, VUT v Brně, 1990 

(CS)

Recommended reading

George A. Bekey: Autonomous Robots: From Biological Inspiration to Implementation and Control, 2005, Bradford Book, ISBN-13 978-0262025782

Ronald C. Arkin: Behavior-Based Robotics, Bradford Books, 1998, ISBN-13 ‏ : ‎ 978-0262529204


John M. Holland: Designing Autonomous Mobile Robots: Inside the Mind of an Intelligent Machine, 2003, Newnes,  ISBN-13 ‏ 978-0750676830 

Alex Ellery: Planetary Rovers: Robotic Exploration of the Solar System, Springer, 2016, ISBN-13 ‏978-3642032585


Gary Bradsky and Adrian Kaehler: LearningOpenCV, O'Reilly, 2008, ISBN 978-0-596-51613-0


Grewal, Andrews and Bartone: Global Navigation Satellite Systems, Inertial Navigation, and Integration, Wiley, 2013, ISBN-13 ‎ 978-1118447000


Kaplan and Hegarty: Understanding GPS/GNSS: Principles and Applications, Artech House, 2017, ISBN-13 ‎ 978-1630810580


Hassan K. Khalil: Nonlinear Systems, Pearson, ISBN-13 ‎ 978-0130673893


Dorf and Bishop: Modern Control Systems, Pearson Hall, 2011, ISBN-13 ‎ 978-0136024583


Ogata: Modern Control Engineering, Pearson, 2009, ISBN-13 ‎ 978-0136156734


Franklin, Powel and Emami-Naeini: Feedback Control of Dynamic Systems, Pearson, ISBN13 978-0-13-349659-8


Beard and McLain: Small Unmanned Aircraft: Theory and Practice, Princeton, 2021, ISBN-13 ‎ 978-0691149219


Sayed: Fundamentals of Adaptive Filtering, Wiley, 2003, ISBN-13 ‏978-0471461265


Russel and Norvig: Artificial Intelligence: A Modern Approach, Pearson, 2009, ISBN-13 ‏978-0136042594


eLearning

eLearning: currently opened course

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MBI , any year of study, winter semester, elective
    branch MPV , any year of study, winter semester, elective
    branch MGM , any year of study, winter semester, elective

  • Programme IT-MGR-2 Master's

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

  • Programme IT-MGR-2 Master's

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

  • Programme MITAI Master's

    specialization NADE , any year of study, winter semester, elective
    specialization NBIO , any year of study, winter semester, elective
    specialization NGRI , any year of study, winter semester, elective
    specialization NNET , any year of study, winter semester, elective
    specialization NVIZ , any year of study, winter semester, elective
    specialization NCPS , any year of study, winter semester, elective
    specialization NSEC , any year of study, winter semester, elective
    specialization NEMB , any year of study, winter semester, elective
    specialization NEMB do 2021/22 , any year of study, winter semester, elective
    specialization NHPC , any year of study, winter semester, elective
    specialization NISD , any year of study, winter semester, elective
    specialization NIDE , any year of study, winter semester, compulsory
    specialization NISY do 2020/21 , any year of study, winter semester, elective
    specialization NISY , any year of study, winter semester, elective
    specialization NMAL , any year of study, winter semester, elective
    specialization NMAT , any year of study, winter semester, elective
    specialization NSEN , any year of study, winter semester, elective
    specialization NVER , any year of study, winter semester, elective
    specialization NSPE , any year of study, winter semester, elective

  • Programme MIT-EN Master's, any year of study, winter semester, elective

  • Programme IT-MGR-1H Master's

    branch MGH , 1. year of study, winter semester, recommended

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Ing. Daniel Bambušek
Ing. Jan Beran
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.
  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.

Laboratory exercise

12 hours, optionally

Teacher / Lecturer

Ing. Daniel Bambušek
Ing. Jaroslav Rozman, Ph.D.

Syllabus

  1. Basic work with Arduino
  2. Working with sensors
  3. Motor control
  4. Basics of ROS, sensor reading
  5. Advanced work in ROS
  6. Final task

Project

14 hours, compulsory

Teacher / Lecturer

Ing. Jaroslav Rozman, Ph.D.

Syllabus

Project implemented on the robot from FIT.

eLearning

eLearning: currently opened course