•   Autonomous Systems ELA18RE03-3002 24.10.2022-18.12.2022  3 credits  (ELA19D-V) +-
    Competence objectives of the study unit
    Is familiar with the basic concepts of intelligent systems and neural networks.
    Understand the principles of self-learning systems and master relevant concepts regarding autonomous robots.
    Prerequisites
    Microprocessor technology
    Applied electronics
    Content of the study unit
    Robot construction (hardware)
    Implementation of autonomous software
    Selection of sensors
    Optimization of implementation (software and sensors)
    Functionality tests
    Demonstrations and final tests
    Documentation of the implementation and selected algorithms
    Assessment criteria
    Failed (0)
    The assessment is made on the basis of submitted documentation and the result of the final test occasion.
    Assessment criteria – satisfactory (1-2)
    Is familiar with the basic concepts of intelligent systems
    Understands nonlinear systems and neural networks
    Understands the principles of self-learning systems
    Master relevant concepts in autonomous robots
    Assessment criteria – good (3-4)
    Is well versed in the basic concepts of intelligent systems
    Can utilize neural networks for technical modeling
    Is familiar with several different methods for implementing self-learning systems
    Can formulate, structure and report a relevant problem regarding autonomous systems or robots
    Assessment criteria – excellent (5)
    Owns a deep insight into the basic concepts of intelligent systems and can speculate on future challenges and opportunities
    Can perform demanding technical modeling using neural networks
    Can program and simulate self-learning systems
    Can successfully complete, report and structure a project on autonomous systems or autonomous robots
    Name of lecturer(s)

    Ronnie Sundsten

    Learning material

    Hardware Specific Documentation (Propeller Tutorials)

    Learning methods

    Group work and demonstrations
    Documentation of algorithms
    Documentation of implementation

    Teaching language

    Swedish

    Timing

    24.10.2022 - 18.12.2022

    Enrollment date range

    15.06.2022 - 30.10.2022

    Group(s)
    • ELA19D-V
    Responsible unit

    Faculty of Technology and Seafaring

    Small group(s)
    • ELA19-V-A (Size: 35.
    Teachers and responsibilities

    Roger Mäntylä

    Additional information

    w. 43-50: Two test occasions and a final test.

    Degree Programme(s)

    Degree Programme in Electrical Engineering and Automation

    Campus

    Vasa, Wolffskavägen 33

    Assessment scale

    H-5

    Alternative methods of attainment for implementation

    No alternative methods of performance. Requires presence due to access to laboratory equipment.

    Exam dates and retake possibilities

    Course examination 3 weeks after completion of the course.
    Test of autonomous functions.
    Submission of documentation according to given deadlines.

    Timing and attendance

    w. 43-50

    Student's schedule and workload

    The laboratory task and its documentation is carried out mainly in class, but also outside lecture hours.

    Assessment criteria
    Failed (0)

    The assessment is made on the basis of submitted documentation and the result of the final test occasion.