İzmir Ekonomi Üniversitesi
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  • FACULTY OF ENGINEERING

    Department of Mechanical Engineering

    MCE 412 | Course Introduction and Application Information

    Course Name
    Autonomous Robotics
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    MCE 412
    Fall/Spring
    2
    2
    3
    6

    Prerequisites
      MATH 250 To get a grade of at least FD
    or EEE 281 To get a grade of at least FD
    Course Language
    English
    Course Type
    Elective
    Course Level
    First Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s)
    Assistant(s)
    Course Objectives 1. To provide basic knowledge on Autonomous Robotics 2. To introduce basic analysis and design methods with a curriculum enriched by application examples.
    Learning Outcomes
    #
    Content
    PC Sub
    * Contribution Level
    1
    2
    3
    4
    5
    11. Explain localization problem of a robot
    22. Describe mapping problem of a robot
    33. Define path planning for a robot
    44. Analyse sensors on an autonomous robot
    55. Design filtering algorithms for autonomous robot applications
    Course Description Introduction to Autonomous Robotics, motion models of a robot, measurement models of different sensor types, filtering techniques, simultaneous localization and mapping method

     



    Course Category

    Core Courses
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Introduction + Sheet 1 (Python Setup) CH1 and CH2, Computational Principles of Mobile Robotics, Gregory Dudek and Michael Jenkin-2nd Edition, Cambridge University Press, 2010.
    2 Linear Algebra Review + Sheet 2 (Linear Algebra practice in Python) Matrix Cookbook
    3 Wheeled Locomotion + Sheet 3 (Locomotion-Differential Drive Kinematics in Python) CH3, Computational Principles of Mobile Robotics, Gregory Dudek and Michael Jenkin-2nd Edition, Cambridge University Press, 2010.
    4 Sensors CH4, Computational Principles of Mobile Robotics, Gregory Dudek and Michael Jenkin-2nd Edition, Cambridge University Press, 2010.
    5 Probabilities and Bayes Review + Sheet 4 (Bayes Rule) CH2, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    6 Probabilistic Motion Models + Sheet 5 (Motion Models in Python) CH5, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    7 Probabilistic Sensor Models + Sheet 6 (Sensor Models in Python) CH6, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    8 The Kalman Filter CH3, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000. --- CH4, Computational Principles of Mobile Robotics, Gregory Dudek and Michael Jenkin-2nd Edition, Cambridge University Press, 2010.
    9 The Extended Kalman Filter + Sheet 8 (Extended Kalman Filter Implementation in Python) CH7, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    10 Discrete Filters CH8, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    11 The Particle Filter + Sheet 7 (Discrete Filter, Particle Filter Implementation in Python) CH8, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    12 Mapping with Known Poses + Sheet 9 (Mapping with Known Poses in Python) CH9, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    13 SLAM CH10, Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    14 Working on a Project
    15 Working on a Project
    16 Working on a Project

     

    Course Notes/Textbooks
    1. Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard and Dieter Fox, MIT Press, 2000
    2. Computational Principles of Mobile Robotics, Gregory Dudek and Michael Jenkin-2nd Edition, Cambridge University Press, 2010
    Suggested Readings/Materials
    1. Introduction to Autonomous Mobile Robots, Roland Siegwart and Illah R. Nourbakhsh, 2004
    2. Handbook oƒ Robotics, Bruno Siciliano and Oussama Khatib
    3. Matrix Cookbook, http://matrixcookbook.com
    4. Hands-On Python: A Tutorial Introduction for Beginners, Andrew N. Harrington
    5. Introduction to Probability, Dimitri P. Bertsekas and John N. Tsitsiklis

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing LO 1 LO 2 LO 3 LO 4 LO 5
    Participation
    10
    10
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    6
    50
    Presentation / Jury
    Project
    1
    20
    Seminar / Workshop
    Oral Exams
    Midterm
    Final Exam
    1
    20
    Total

    Weighting of Semester Activities on the Final Grade
    17
    80
    Weighting of End-of-Semester Activities on the Final Grade
    1
    20
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    16
    2
    32
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    6
    7
    42
    Presentation / Jury
    0
    Project
    1
    40
    40
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    0
    Final Exam
    1
    20
    20
        Total
    182

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1

    To have adequate knowledge in Mathematics, Mathematics based physics, statistics and linear algebra and Mechanical Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

    -
    -
    -
    -
    -
    2

    To be able to identify, define, formulate, and solve complex Mechanical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

    -
    -
    -
    -
    -
    3

    To be able to design a thermal and mechanical system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

    -
    -
    -
    -
    -
    4

    To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in engineering applications.

    -
    -
    -
    -
    -
    5

    To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Mechanical Engineering research topics.

    -
    -
    -
    -
    -
    6

    To be able to work efficiently in Mechanical Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

    -
    -
    -
    -
    -
    7

    To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

    -
    -
    -
    -
    -
    8

    To have knowledge about global and social impact of engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

    -
    -
    -
    -
    -
    9

    To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

    -
    -
    -
    -
    -
    10

    To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

    -
    -
    -
    -
    -
    11

    To be able to collect data in the area of Mechanical Engineering, and to be able to communicate with colleagues in a foreign language.

    -
    -
    -
    -
    -
    12

    To be able to speak a second foreign language at a medium level of fluency efficiently.

    -
    -
    -
    -
    -
    13

    To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Mechanical Engineering.

    -
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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