SylabUZ
Nazwa przedmiotu | Fundamentals of robotics |
Kod przedmiotu | 06.9-WE-AutP-FundRob-Er |
Wydział | Wydział Nauk Inżynieryjno-Technicznych |
Kierunek | Automatyka i robotyka |
Profil | ogólnoakademicki |
Rodzaj studiów | Program Erasmus pierwszego stopnia |
Semestr rozpoczęcia | semestr zimowy 2021/2022 |
Semestr | 4 |
Liczba punktów ECTS do zdobycia | 6 |
Typ przedmiotu | obowiązkowy |
Język nauczania | angielski |
Sylabus opracował |
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Forma zajęć | Liczba godzin w semestrze (stacjonarne) | Liczba godzin w tygodniu (stacjonarne) | Liczba godzin w semestrze (niestacjonarne) | Liczba godzin w tygodniu (niestacjonarne) | Forma zaliczenia |
Wykład | 30 | 2 | - | - | Egzamin |
Laboratorium | 30 | 2 | - | - | Zaliczenie na ocenę |
To provide fundamental knowledge in subject of analysis, control and motion planning for modern industrial robotic systems.
To develop skills in proper robot selection and evaluation for industrial process automation.
Modeling and simulation, Signals and dynamic systems, Control engineering
Introduction. Historical outline. Overview of robotic mechanical systems. Tasks performed by robots. Categories of manipulators and robots. Basic components of industrial robots. Grippers. A robot as part of a control system. Structures of manipulators and robots. Linear transformations. Rigid-body rotations.
Coordinate transformations and homogeneous coordinates. Degrees of freedom. .
Kinematics. Kinematic relationships of a manipulator. Link description. Link connections. Forward kinematics. Denavit-Hartenberg parameters. Inverse kinematics. Jacobians.
Dynamics. Joint-space dynamics. Euler-Lagrange equations. Equations of motion. Newton-Euler formalism. Dynamics of a rigid manipulator. Simulation of dynamics.
Trajectory generation. Trajectory planning in configuration space. Cartesian planning. Geometrical problems. Real-time trajectory generation. Trajectory planning using a dynamic model. Collision-free trajectory planning.
Robotic drives. Hydraulic drives. Pneumatic drives. Electric drives.
Robotic sensors. Processing information from sensors. Computer vision. Stereo-based reconstruction.
Applications of robots in industry. Welding applications. Spray painting applications. Assembly operations. Palletizing and material handling. Dispensing operations. Laboratory applications. Work cells.
Wheeled mobile robots. Forward and inverse kinematics of mobile robots. Perception: sensors, representation of uncertainty, feature extraction. Self-localization.
Other applications of robots. Humanoids. Entertainment robots. Medical robots. Exosceletons. Military and police robots.
Lecture. Laboratory exercises
Opis efektu | Symbole efektów | Metody weryfikacji | Forma zajęć |
Lecture – the main condition to get a pass are sufficient marks in written or oral tests conducted at least once per semester.
Laboratory – the passing condition is to obtain positive marks from all laboratory exercises to be planned during the semester.
Calculation of the final grade: lecture 50% + laboratory 50%
Zmodyfikowane przez dr hab. inż. Wojciech Paszke, prof. UZ (ostatnia modyfikacja: 12-07-2021 07:56)