To teach kinematic calculations, trajectory planning, and various control methods for designing robots of manipulator or rover type. To have theoretical information and functions of different sensors and actuators comprehended with applications to be developed on available robotic systems.
20
Contribution of the Course to Professional Development
21
Learning Outcomes:
1
Being able to perform forward or inverse position calculations for different robot configurations;
2
Being able to perform forward or inverse velocity calculations through differential analysis;
3
Knowing techniques that are used for trajectory planning and motion, velocity, or force control;
4
Having knowledge about types and functions of sensors and actuators;
5
Being able to program robotic systems using proper interfaces;
6
Being able to develop controller software for a robotic system to run in real-time;
22
Course Content:
Week
Theoretical
Practical
1
Robotic systems and application areas, common robot configurations
2
Fundamentals of mathematical robot modeling, homogeneous coordinates and representation of transformations with matrices
3
Forward and inverse kinematics for common robot configurations
4
Programming different robots with interfaces of robot operating system
5
Denavit-Hartenberg representation of forward and inverse kinematics
6
Differential motion analysis, forward and inverse Jacobian calculations
7
Dynamic analysis and forces
8
Path and trajectory planning, trajectory planning with high-order polynomials and via points
9
Motion, velocity, and force control, proportional, integral, and derivative controllers
10
Vision-based control methods
11
Fuzzy logic-based control methods
12
Sensors: position, velocity, acceleration, pressure, light and proximity sensors, range scanners and camera systems
13
Actuators: hydraulic and pneumatic devices, electric motors
14
Project presentations
23
Textbooks, References and/or Other Materials:
1. Niku, S. B., 2001. Introduction to Robotics Analysis, Systems, Applications, Prentice Hall, New Jersey. 2. Siegwart, R., Nourbakhsh, I. R., and Scaramuzza, D., 2010. Introduction to Autonomous Mobile Robots, MIT Press (2nd Edition).
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Assesment
TERM LEARNING ACTIVITIES
NUMBER
PERCENT
Midterm Exam
1
20
Quiz
0
0
Homeworks, Performances
4
20
Final Exam
1
60
Total
6
100
Contribution of Term (Year) Learning Activities to Success Grade
40
Contribution of Final Exam to Success Grade
60
Total
100
Measurement and Evaluation Techniques Used in the Course
Information
25
ECTS / WORK LOAD TABLE
Activites
NUMBER
TIME [Hour]
Total WorkLoad [Hour]
Theoretical
14
3
42
Practicals/Labs
0
0
0
Self Study and Preparation
14
2
28
Homeworks, Performances
4
8
32
Projects
1
20
20
Field Studies
0
0
0
Midtermexams
1
10
10
Others
0
0
0
Final Exams
1
14
14
Total WorkLoad
146
Total workload/ 30 hr
4,87
ECTS Credit of the Course
5
26
CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
