Knowledge about principles and implementations of elements of industrial and mobile robot systems. Understanding of robot control and programming. Understanding of robot vision as a part of applied artificial intelligence. Work with real robot systems and applications.
- differentiate the principles and versions of elements of industrial and mobile robots
- explain basic types of robot control
- explain basic principles of robot programming
- explain basic image processing algorithms for robot vision
- explain algorithms for object recognition, localization and manipulation
- create a virtual robot model by using VRML
- synthesize with VRML robot model by using Matlab
- explain algorithms for solving direct and inverse kinematics
Forms of Teaching
Organized in three thematic cycles (5+4+4 hours)Exercises
Can be organized if students ask for itLaboratory Work
Two project tasks: • For a given robot task one should design a robot using the LEGO Mindstorm NXT system, build a virtual model and execute the given task in virtual environment using Matlab • For a given robot task one should build a robot using the LEGO Mindstorm NXT system, and write a program and prepare demonstration of robot operation. The robot task assumes the use of robot vision.Experiments
In-class demonstration of examples of VRML programming.Consultations
One hour weekly upom requestSeminars
Creation of virtual robot model and control of robot model from MatlabAcquisition of Skills
Programming of real educational and industrial robots Mastering of basic VRML programmingOther
A multimedia textbook in Croatian is available for students
|Type||Threshold||Percent of Grade||Threshold||Percent of Grade|
|Seminar/Project||0 %||60 %||0 %||60 %|
|Mid Term Exam: Written||0 %||20 %||0 %|
|Final Exam: Written||0 %||20 %|
|Exam: Written||0 %||40 %|
|Exam: Oral||30 %|
The oral exam share is ±30%.
Week by Week Schedule
- Robots and robot systems - overview.
- Industrial robots and applications.
- Structure analysis of a robotic system with a SCARA robot.
- Kinematics fundamentals - homogeneous coordinates. Robot tool position and orientation.
- Denavit-Hartenberg method of determining robot kinematic parameters.
- Direct kinematics. Examples.
- Inverse kinematics. Examples.
- Midterm exam
- Introduction to VRML. Virtual modeling of robotic systems using VRML.
- Control of virtual robotic systems by using Matlab.
- Computer tools for modeling, simulation and control of robot systems
- Introduction to robot vision. Basic algorithms for image processing (noise filtering, edge detection, Hough transformation).
- Object recognition algorithms (chain code, pattern matching, calculation of moments). Determination of position and orientation of object in the robot workspace.
- Introduction to intelligent object manipulation using robot vision.
- Final exam