450-4096/02 – Industrial Robotics II (PR II)
Gurantor department | Department of Cybernetics and Biomedical Engineering | Credits | 4 |
Subject guarantor | Ing. Radim Hercík, Ph.D. | Subject version guarantor | Ing. Radim Hercík, Ph.D. |
Study level | undergraduate or graduate | | |
| | Study language | English |
Year of introduction | 2019/2020 | Year of cancellation | |
Intended for the faculties | FEI | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
The aim of the course is to provide students with extensive information in the field of industrial / mobile robots and its groups management, advanced robotics, mobile and collective robotics, machine learning and artificial intelligence. After studying the module, the student should get an overview of the AI methods used, the principles of machine learning, planning and decision making. They should gain practical experience with their use and acquire other skills needed to create intelligent agents and autonomous control of robot groups.
Teaching methods
Lectures
Individual consultations
Experimental work in labs
Project work
Other activities
Summary
The subject follows the Industrial Robotics I from the bachelor's study. It focuses on advanced robotics, sensors, mobile and collective robotics, machine learning and artificial intelligence. In the practical part of laboratory exercises it deals with the advanced control of industrial and mobile robots with more degrees of freedom with simple and multisensor systems for local and global monitoring of position, speed and acceleration in the area and space and autonomous fulfillment of given tasks.
Compulsory literature:
Reza N. Jazar: Theory of Applied Robotics: Kinematics, Dynamics, and Control. Springer, 2010.
Stuart J. Russel and Peter Norvig. Artificial Intelligence, a Modern Approach. 3rd edition, 2010
Recommended literature:
Additional study materials
Way of continuous check of knowledge in the course of semester
Combined exam (written and oral).
Ongoing monitoring of studies: semester project
Credit conditions: implementation and defense of a semester project (40 points)
E-learning
Other requirements
There are no additional requirements.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures:
1. Subsystems and key components of applications with industrial robots.
2. Industrial sensors and sensors for industrial and mobile robotics.
3. Gripping systems, grippers.
4. Machine vision, bin-picking tasks.
5. Camera systems for industrial and mobile robotics, navigation.
6. Industrial networks, 5G, cloud computing and its use in industrial and mobile robotics.
7. Communication of industrial robots with control systems.
8. Communication of mobile robots with control systems.
9. Safety, optical barriers, lidars, radars in industrial and mobile robotics.
10. Cooperation of several industrial robots.
11. Virtual modeling, digital twin in industrial robotics.
12. Virtual reality, augmented reality, assisted assembly as support for industrial and mobile robotics.
Exercises:
1. Safety training, organization of exercises.
2. Slow work with Kuka robots.
3. Ways of grasping objects using Kuka industrial robots.
4. Creating a program for Kuka robots using the WorkVisual environment, part I.
5. Creating a program for Kuka robots using the WorkVisual environment part II.
6. Advanced programming of Kuka robots part I.
7. Advanced programming of Kuka robots part II.
8. Use of the industrial 5G network for communication with industrial robots - UseCase creation.
9. Use of the industrial 5G network for communication with industrial mobile robots - UseCase creation.
10. Virtual reality and its connection to industrial robotics.
11. SmartFactory line and method of implementing Kuka industrial robots and Mir mobile robot into one functional unit.
12. Defense of the semester project, credit.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction