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) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | |
| Learning and Teaching Strategies | . |
| Course Lecturer(s) |
|
| 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 |
|---|---|---|
| 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 |
|---|---|
| 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 | Knowledge of mathematics, natural sciences, engineering fundamentals, computing, and topics specific to the relevant engineering discipline; the ability to use this knowledge in the solution of complex engineering problems. | |||||
| 2 | The ability to identify, formulate, and analyze complex engineering problems using knowledge of basic sciences, mathematics, and engineering, and considering the UN Sustainable Development Goals relevant to the problem. | |||||
| 3 | The ability to design creative solutions for complex engineering problems; the ability to design complex systems, processes, devices, or products to meet current and future requirements, considering realistic constraints and conditions. | |||||
| 4 | The ability to select and use appropriate techniques, resources, and modern engineering and IT tools, including prediction and modeling, for the analysis and solution of complex engineering problems, with an awareness of their limitations. | |||||
| 5 | The ability to use research methods for the investigation of complex engineering problems, including literature search, designing and conducting experiments, collecting data, and analyzing and interpreting results. | |||||
| 6 | Knowledge of the effects of engineering practices on society, health and safety, the economy, sustainability, and the environment within the scope of the UN Sustainable Development Goals; awareness of the legal consequences of engineering solutions. | |||||
| 7 | Acting in accordance with engineering professional principles, knowledge of ethical responsibility; awareness of acting impartially without discrimination on any grounds and being inclusive of diversity. | |||||
| 8 | The ability to work effectively individually and in intra-disciplinary and multi-disciplinary teams (face-to-face, remote, or hybrid) as a team member or leader. | |||||
| 9 | "The ability to communicate effectively orally and in writing on technical topics, considering the various differences of the target audience (such as education, language, profession). | |||||
| 10 | Knowledge of practices in business life such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation. | |||||
| 11 | The ability to engage in life-long learning, including independent and continuous learning, adapting to new and emerging technologies, and thinking inquisitively regarding technological changes. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| 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 | ||