At the end of this course, the students; 1) Learn the use of mathematical expressions on mobile robots. 2) Learn the choosing sensors and last control units for mobile robots. 3) Will be able to develop algorithms and formulate for mobile robot problems, i.e. position detection, mapping, path planning. 4) Will be able to do applications of smart systems on mobile robots. 5) Learn the use of robots in solutions of real life problems.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
Mobile robot architectures, mobile robot kinematics, mobile robot perception (sensors), Control of mobile robots, Localization, Map building, and path planning in mobile robots, Simultaneous Localization and Map Building, Artificial intelligent robots, Behavior based robotics, Target tracking, obstacle detection,
COURSE CONTENTS
WEEK
TOPICS
1st Week
Introduction to mobile robots
2nd Week
Historical development of mobile robots
3rd Week
Matrix and vector applications on mobile robots
4th Week
The forward and inverse kinematics in robots
5th Week
Dynamical modelling on mobile robots
6th Week
Dynamical modelling on mobile robots
7th Week
Sensors and last control units
8th Week
Midterm Exam
9th Week
Position detection on mobile robots
10th Week
Position detection on mobile robots
11th Week
Mapping on mobile robots
12th Week
Mapping on mobile robots
13th Week
Target tracking
14th Week
Target tracking
RECOMENDED OR REQUIRED READING
1. Introduction to Robotics: Analysis, Systems, Applications, Saeed B. Niku, Prentice Hall 2002 2. Introduction to Robotics: Hohn. J.Craig third edition 2005
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Lecture,Questions/Answers,Presentation
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
30
Assignment
1
15
Project
1
25
Total(%)
70
Contribution of In-term Studies to Overall Grade(%)
70
Contribution of Final Examination to Overall Grade(%)
30
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
3
3
Preparation for Quiz
0
0
0
Individual or group work
14
8
112
Preparation for Final exam
1
40
40
Course hours
14
3
42
Preparation for Midterm exam
1
30
30
Laboratory (including preparation)
0
0
0
Final exam
1
3
3
Homework
2
35
70
Total Workload
300
Total Workload / 30
10
ECTS Credits of the Course
10
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)