Robot Control - course description

General information

Course name	Robot Control
Course ID	06.9-WE-AutP-RC-Er
Faculty	Faculty of Computer Science, Electrical Engineering and Automatics
Field of study	WIEiA - oferta ERASMUS / Automatic Control and Robotics
Education profile	-
Level of studies	First-cycle Erasmus programme
Beginning semester	winter term 2018/2019

Course information

Semester	6
ECTS credits to win	4
Course type	obligatory
Teaching language	english
Author of syllabus	dr hab. inż. Maciej Patan, prof. UZ

Classes forms

The class form	Hours per semester (full-time)	Hours per week (full-time)	Hours per semester (part-time)	Hours per week (part-time)	Form of assignment
Lecture	15	1	-	-	Credit with grade
Laboratory	30	2	-	-	Credit with grade
Project	15	1	-	-	Credit with grade

Aim of the course

To provide fundamental skills within the framework of design and implementation of control algorithms with the use of various programming languages.
To provide knowledge on methods of control for mobile robots and robotic manipulators.

Prerequisites

Fundamentals of robotics, Control engineering

Scope

Robot manipulator as a control plant. Point to point control. PD and PID controllers. Observers. Trajectory interpolation. Robot control with Lead feedback and computed moment methods. Multidimensional control.

Robot force control. Natural and artificial constraints. Stiffness and susceptibility. Inverse dynamics in the problem space. Impedance control. Hybrid position/force control.

Advanced control. Feedback linearization. Sliding mode control. Adaptive control.

Programming of robot operation. Programming languages for robotics. Programming structures, robot programming through learning; Task-level programming languages; Requirements for programming languages.

Navigation of autonomic vehicle. Foundations of environment recognition methods. Adaptive identification of mobile robot models. Follower type motion control algorithm. State observers for mobile wheel robots. Prototyping of analyzed systems.

Teaching methods

Lecture, Laboratory exercises.

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

Lecture – the main condition to get a pass are sufficient marks in written or oral tests conducted at least once per semester.

Laboratory – the main condition to get a pass is scoring sufficient marks for all laboratory exercises.

Project - the main condition to get a pass is positive grade for prepared project.

Calculation of the final grade: lecture 40% + laboratory 30% + project 30%

Notes

Modified by dr hab. inż. Wojciech Paszke, prof. UZ (last modification: 29-04-2020 12:03)

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