Course detail
Robotics (in English)
FIT-ROBaAcad. year: 2020/2021
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.
Supervisor
Department
Nabízen zahradničním studentům
Všech fakult
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.
Recommended optional programme components
Not applicable.
Recommended or required reading
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.
LYNCH, Kevin M. and PARK, Frank C. Modern robotics: mechanics, planning, and control. Cambridge (Reino Unido) : Cambridge University Press, 2018.
GOVERS, Francis X. Artificial intelligence for robotics: buildintelligent robots that perform human tasks using AI techniques. Birmingham, UK : Packt Publishing Ltd, 2018.
Nolfi, S., Floreano, D.: Evolutionary Robotics : The Biology, Intelligence, and Technology of Self-Organizing Machines (Intelligent Robotics and Autonomous Agents), Bradford Books, 2004, ISBN 0262640562
Holland, J., M.: Designing Autonomous Mobile Robots: Inside the Mind of an Intelligent Machine, 2003, ISBN 0750676833
Craig, J., J.: Introduction to Robotics: Mechanics and Control, Prentice Hall, 2003, ISBN 0201543613
Sciavicco, L., Siciliano, B.: Modelling and Control of Robot Manipulators (Advanced Textbooks in Control and Signal Processing), Springer Verlag, 2000, ISBN 1852332212
Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2000, ISBN 0262133830
Spong, M., Vydyasagar, M.: Robot Dynamics and Control, J. Willey, 1989, ISBN 047161243X
Planned learning activities and teaching methods
Not applicable.
Assesment methods and criteria linked to learning outcomes
- Graded laboratories.
- Mid-term written test.
- Evaluated project with a defence.
Language of instruction
English
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.
Classification of course in study plans
- Programme IT-MGR-2 Master's
branch MBI , any year of study, winter semester, 5 credits, elective
branch MPV , any year of study, winter semester, 5 credits, elective
branch MGM , any year of study, winter semester, 5 credits, elective - Programme IT-MGR-2 Master's
branch MGMe , any year of study, winter semester, 5 credits, compulsory-optional
- Programme IT-MGR-2 Master's
branch MSK , any year of study, winter semester, 5 credits, elective
branch MIS , any year of study, winter semester, 5 credits, elective
branch MBS , any year of study, winter semester, 5 credits, elective
branch MIN , any year of study, winter semester, 5 credits, compulsory-optional
branch MMI , any year of study, winter semester, 5 credits, elective
branch MMM , any year of study, winter semester, 5 credits, elective - Programme MITAI Master's
specialization NADE , any year of study, winter semester, 5 credits, elective
specialization NBIO , any year of study, winter semester, 5 credits, elective
specialization NGRI , any year of study, winter semester, 5 credits, elective
specialization NNET , any year of study, winter semester, 5 credits, elective
specialization NVIZ , any year of study, winter semester, 5 credits, elective
specialization NCPS , any year of study, winter semester, 5 credits, elective
specialization NSEC , any year of study, winter semester, 5 credits, elective
specialization NEMB , any year of study, winter semester, 5 credits, elective
specialization NHPC , any year of study, winter semester, 5 credits, elective
specialization NISD , any year of study, winter semester, 5 credits, elective
specialization NIDE , any year of study, winter semester, 5 credits, compulsory
specialization NISY , any year of study, winter semester, 5 credits, elective
specialization NMAL , any year of study, winter semester, 5 credits, elective
specialization NMAT , any year of study, winter semester, 5 credits, elective
specialization NSEN , any year of study, winter semester, 5 credits, elective
specialization NVER , any year of study, winter semester, 5 credits, elective
specialization NSPE , any year of study, winter semester, 5 credits, elective - Programme IT-MGR-1H Master's
branch MGH , any year of study, winter semester, 5 credits, recommended
Type of course unit
Lecture
26 hours, optionally
Teacher / Lecturer
Syllabus
- History, evolution, and current trends in robotics. Introduction to robotics. Robotic applications. Robotic competitions.
- Kinematics and statics. Direct and inverse task of kinematics.
- Path planning in the cartesian coordinate system.
- Effectors,sensors and power supply of robots. Applications of the cameras, laser distance meters, and sonars.
- Midterm test.
- Basic parameters of the mobile robots. Model and control of the wheel mobile robots.
- Robotic middleware. Robot Operating System (ROS), philosophy of ROS, nodes and communication among them.
- Maps - configuration space and 3D models. Probability in robotics. Introduction. Bayesian filtering, Kalman and particle filters. Model of robot movements and measurement model.
- Methods of the global and local localization. GPS based localization, Monte Carlo method.
- Map building. Algorithms for simultaneous localization and mapping (SLAM).
- Trajectory planning in known and unknown environment. Bug algorithm, potential fields, visibility graphs and probabilistic methods.
- Introduction to control and regulation.
- Multicopters, principle, control, properties, usage. Human - robot collaboration.
Laboratory exercise
6 hours, compulsory
Teacher / Lecturer
Syllabus
- Lego Mindstorms
- Basics of ROS, sensor reading
- Advanced work in ROS
Project
20 hours, compulsory
Teacher / Lecturer
Syllabus
Project implemented on some of the robots from FIT.