Title:

Robotics (in English)

Code:ROBa
Ac.Year:2018/2019
Sem:Winter
Curriculums:
ProgrammeField/
Specialization
YearDuty
IT-MSC-2MBI-Elective
IT-MSC-2MBS-Elective
IT-MSC-2MGM-Elective
IT-MSC-2MGMe-Compulsory-Elective - group C
IT-MSC-2MIN-Compulsory-Elective - group I
IT-MSC-2MIS-Elective
IT-MSC-2MMI-Elective
IT-MSC-2MMM-Elective
IT-MSC-2MPV-Elective
IT-MSC-2MSK-Elective
Language of Instruction:English
News:
This course is instructed in English, and it is intended for incoming Erasmus+ students, too.

Credits:5
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:2606020
 ExamsTestsExercisesLaboratoriesOther
Points:55200025
Guarantor:Orság Filip, Ing., Ph.D. (DITS)
Lecturer:Orság Filip, Ing., Ph.D. (DITS)
Rozman Jaroslav, Ing., Ph.D. (DITS)
Instructor:Bambušek Daniel, Ing. (DCGM)
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
 
Learning objectives:
  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.
Description:
  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.
Learning outcomes and competencies:
  The students acquire knowledge of current state and trends in robotics. Also, they acquire practical knowledge from construction and use of robots.
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. Effectors and power supply of robots. Using stereocamera for distance measurement.
  5. Basic parameters of the mobile robots. Model and control of the wheel mobile robots.
  6. Robotic middleware. Robot Operating System (ROS), philosophy of ROS, nodes and communication among them.
  7. Maps - configuration space and 3D models.
  8. 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 theory and regulation.
  13. Multicopters, principle, control, properties, usage.
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.
Fundamental literature:
 
  • Siegwart, R. a Nourbakhsh, I. R.: Introduction to Autonomous Mobile Robots. MIT Press, 2011. ISBN-13: 978-0262015356
  • Thrun, S., Burgard, W. a Fox, D.: Probabilistic Robotics. MIT Press, 2005. ISBN 0-262-201623
  • Choset, H., Lynch, K. M., Hutchinson, S. et al.: Principles of Robot Motion. MIT, Press, 2005. ISBN 0-262-03327-5.
  • Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2000,  ISBN 0262133830 
Study literature:
 
  1. Siegwart, R. a Nourbakhsh, I. R.: Introduction to Autonomous Mobile Robots. MIT Press, 2011. ISBN-13: 978-0262015356
  2. Thrun, S., Burgard, W. a Fox, D.: Probabilistic Robotics. MIT Press, 2005. ISBN 0-262-201623
  3. Choset, H., Lynch, K. M., Hutchinson, S. et al.: Principles of Robot Motion. MIT, Press, 2005. ISBN 0-262-03327-5.
  4. Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2000,  ISBN 0262133830
Progress assessment:
  
  1. Mid-term written test.
  2. Evaluated project with a defence.
 

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