450-6012/02 – Cybernetic Methods in Robotics (KMR)
| Gurantor department | Department of Cybernetics and Biomedical Engineering | Credits | 10 |
| Subject guarantor | doc. Ing. Bohumil Horák, Ph.D. | Subject version guarantor | doc. Ing. Bohumil Horák, Ph.D. |
| Study level | postgraduate | Requirement | Choice-compulsory |
| Year | | Semester | winter + summer |
| | Study language | English |
| Year of introduction | 2015/2016 | Year of cancellation | |
| Intended for the faculties | FEI | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Course Cybernetic methods in robotics is the subject of doctoral study. Target of this course is:
Extend the knowledges of previous studies courses in technical cybernetics, control systems for control of robotic systems
Introduce students in problematic of machine learning, situation modeling and byck-using of algorithms of this behavior for rontrol of robot systems
Introduce students to the problems of machine learning, modeling the situation and re-use of behavior control algorithms for robotic control systems
Teaching methods
Lectures
Individual consultations
Project work
Summary
Course Cybernetic methods in robotics is the subject of doctoral study. Extends the findings of studies graduate courses devoted to the study of cybernetics and control systems of the previous study, which assumes knowledge of the mathematical basis of which the student received during the Masters. The course has two lines of study, the first deals with the design and implementation of modern sophisticated control algorithms for robotic control systems, the second deals with the use of artificial intelligence in robotics. More specifically deals with machine learning, modeling the situation and re-use of behavior control algorithms for robotic control systems.
Compulsory literature:
Recommended literature:
Nocks.L.: The Robot: The Life Story of a Technology, Greenwood Technographies, 2007 ISBN 978-0313331688 224pp.
Hall, J.S. : Beyond AI: Creating the Conscience of the Machine. Prometheus Books, 2007 ISBN 978-1591025115 408pp.
Ertel, W.: Introduction to artificial intelligence. Springer int. publishing AG, 2017 ISBN 978-3319584867 311pp.
Way of continuous check of knowledge in the course of semester
Time schedule of subject study, with continuous processing of sub-tasks
E-learning
Other requirements
There are not defined other requirements for student
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1st Architecture of agents. Subsumption, reactive, deliberative architecture. Hybrid architecture.
2nd Multi-agent systems. Coordination, collaboration, cooperation, communication. Architecture of multi-agent systems.
3rd Machine Learning Methods. Learning deliberative and reactive agents. Other methods of learning.
4th The structure of the technical solution of robot or robots group, strategic systems, decision making, multicriteria decision making.
5th Embedded control system for robot, architecture.
6th Sensor system of the robot. Sensors internal and external environment
7th Communication of robot with external enviroment
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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