ECTS - Path Planning and Navigation
Path Planning and Navigation (MECE447) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
---|---|---|---|---|---|---|---|
Path Planning and Navigation | MECE447 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | |
Learning and Teaching Strategies | . |
Course Lecturer(s) |
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Course Objectives | |
Course Learning Outcomes |
The students who succeeded in this course; |
Course Content | Introduction, kinematic models for mobile robots, mobile robot control, robot attitude, robot navigation, path finding, obstacle mapping and its application to robot navigation, application of Kalman filtering. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Introduction, Locomotion, Direct and Inverse Robot Kinematics, Homogenous Transformations | |
2 | Kinematics of Unicycle, Bicycle, Differential Drive, Tricycle, Ackermann and Omnidirectional robots | |
3 | Dynamic model for wheeled mobile Robot | |
4 | Heading and speed control of front wheel steered vehicle, Heading and speed control of differential drive robot, Computed control for heading and velocity, Pursuit controller, Stanley controller | |
5 | Heading and speed control of front wheel steered vehicle, Heading and speed control of differential drive robot, Computed control for heading and velocity, Pursuit controller, Stanley controller | |
6 | Taxonomy of driving, perception, sensors, software architecture, environment representation, Rotation matrix for Yaw, Pitch and Roll, Homogenous Transformation matrix, Rotating a vector | |
7 | Coordinate systems, Earth-centered Earth-fixed coordinate system, Computing location using Global Positioning System, Computing location using IMU, Dead Reckoning | |
8 | Coordinate systems, Earth-centered Earth-fixed coordinate system, Computing location using Global Positioning System, Computing location using IMU, Dead Reckoning | |
9 | Depth First Search, Breadth First Search, A* algorithm, Djikstra, Mini-Max, Alpha-Beta, Bug1, Bug2, Tangent Bug, Random Particle Optimization, Additive Attractive/Repulsive potential, Gradient descent | |
10 | Depth First Search, Breadth First Search, A* algorithm, Djikstra, Mini-Max, Alpha-Beta, Bug1, Bug2, Tangent Bug, Random Particle Optimization, Additive Attractive/Repulsive potential, Gradient descent | |
11 | Depth First Search, Breadth First Search, A* algorithm, Djikstra, Mini-Max, Alpha-Beta, Bug1, Bug2, Tangent Bug, Random Particle Optimization, Additive Attractive/Repulsive potential, Gradient descent | |
12 | Sensors for obstacle detection, Dead reckoning navigation, Use of previously detected obstacles for navigation | |
13 | Probabilistic estimation, Linear Kalman filtering, Extended Kalman filter | |
14 | Probabilistic estimation, Linear Kalman filtering, Extended Kalman filter |
Sources
Evaluation System
Requirements | Number | Percentage of Grade |
---|---|---|
Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | - | - |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | - | - |
Final Exam/Final Jury | - | - |
Toplam | 0 | 0 |
Percentage of Semester Work | |
---|---|
Percentage of Final Work | 100 |
Total | 100 |
Course Category
Core Courses | X |
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Major Area Courses | |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | ||
1 | An ability to apply knowledge in mathematics and basic sciences and computational skills to solve manufacturing engineering problems | |||||
2 | An ability to define and analyze issues related with manufacturing technologies | |||||
3 | An ability to develop a solution based approach and a model for an engineering problem and design and manage an experiment | |||||
4 | An ability to design a comprehensive manufacturing system based on creative utilization of fundamental engineering principles while fulfilling sustainability in environment and manufacturability and economic constraints | |||||
5 | An ability to chose and use modern technologies and engineering tools for manufacturing engineering applications | |||||
6 | An ability to utilize information technologies efficiently to acquire datum and analyze critically, articulate the outcome and make decision accordingly | |||||
7 | An ability to attain self-confidence and necessary organizational work skills to participate in multi-diciplinary and interdiciplinary teams as well as act individually | |||||
8 | An ability to attain efficient communication skills in Turkish and English both verbally and orally | |||||
9 | An ability to reach knowledge and to attain life-long learning and self-improvement skills, to follow recent advances in science and technology | |||||
10 | An awareness and responsibility about professional, legal, ethical and social issues in manufacturing engineering | |||||
11 | An awareness about solution focused project and risk management, enterpreneurship, innovative and sustainable development | |||||
12 | An understanding on the effects of engineering applications on health, social and legal aspects at universal and local level during decision making process |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | |||
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | |||
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | |||
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | |||
Prepration of Final Exams/Final Jury | |||
Total Workload | 0 |