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 | Technical 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 | Adequate knowledge in mathematics, science and subjects specific to the software engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. | |||||
| 2 | The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. | X | ||||
| 3 | The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. | X | ||||
| 4 | The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in software engineering applications; the ability to utilize information technologies effectively. | X | ||||
| 5 | The ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the software engineering discipline. | |||||
| 6 | The ability to work effectively in inter/inner disciplinary teams; ability to work individually. | |||||
| 7 | Effective oral and written communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
| 8 | The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
| 9 | Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development | |||||
| 10 | The ability to behave according to ethical principles, awareness of professional and ethical responsibility. | |||||
| 11 | Knowledge of the standards utilized in software engineering applications. | |||||
| 12 | Knowledge on business practices such as project management, risk management and change management. | |||||
| 13 | Awareness about entrepreneurship, and innovation. | |||||
| 14 | Knowledge on sustainable development. | |||||
| 15 | Knowledge of the effects of software engineering applications on the universal and social dimensions of health, environment, and safety. | |||||
| 16 | Awareness of the legal consequences of engineering solutions. | |||||
| 17 | An ability to apply algorithmic principles, mathematical foundations, and computer science theory in the modeling and design of computer-based systems with the trade-offs involved in design choices. | |||||
| 18 | The ability to apply engineering approach to the development of software systems by analyzing, designing, implementing, verifying, validating and maintaining software systems. | |||||
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 | ||