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Robots Programming

ITI0201
Computer Science and ICT, Data, AI

About this course

overview: problems and progress, interpreting uncertain sensor data, localizing and mapping, navigation and control, motion planning

NB! This course will take place in spring semester 2024/2025 which starts on 3rd of February and ends on 16th of June (you can find that information under Start date section). The real course start and end dates will be announced at the beginning of February at the latest.

Learning outcomes

After completing this course, the student is able to:

  • integrate sensors, actuators, and software into a robot designed to undertake some task;
  • program a robot to accomplish simple tasks using deliberative, reactive, and/or hybrid control architectures;
  • implement fundamental motion planning algorithms for mobile differential drive robots,
  • characterize the uncertainties associated with common robot sensors and actuators; articulate strategies for mitigating these uncertainties;
  • understand the difficulties developing software for robots (i.e., real world applications);
  • comprehend the interdisciplinary nature of robotics and how other fields of science relate to robotics;
  • gain teamwork experience by working in a team.

Examination

Final assessment can consist of one test/assignment or several smaller assignments completed during the whole course. After declaring a course the student can re-sit the exam/assessment once. Assessment can be graded or non-graded. For specific information about the assessment process please get in touch with the contact person of this course. For specific information about grade transfer please contact your home university

Course requirements

Completion of "Introduction to Programming" or an equivalent course, with a solid understanding of Python programming fundamentals, including object-oriented programming concepts. Students should be able to apply basic data structures, solve computational problems, debug source code, write unit tests, and produce clean, well-documented source code. A general understanding of how to translate algorithm descriptions into source code is expected. Familiarity with coding standards is also required.

Resources

  • Kursuse e-tugi https://moodle.taltech.ee/course/view.php?id=32593
  • Kursuse koduleht <a href="https://courses.cs.ttu.ee/pages/ITI0201" target="_blank">https://courses.cs.ttu.ee/pages/ITI0201</a>Mordechai Ben-Ari and Francesco Mondada. Elements of Robotics. 2018John M. Zelle. Python Programming: An Introduction to Computer Science. 2010Steven M. LaValle. Planning Algorithms. 2006

Activities

lectures, practices

Additional information

  • Credits
    ECTS 6
  • Level
    Bachelor
  • Contact hours per week
    4
  • Instructors
    Gert Kanter
  • Mode of instruction
    Online - time-independent
If anything remains unclear, please check the FAQ of TalTech (Estonia).

Offering(s)

  • Start date

    3 February 2025

    • Ends
      16 June 2025
    • Term *
      Spring semester 2025
    • Instruction language
      English
    • Register between
      29 Oct - 29 Nov 2024
    Only 11 days to enrol
    Apply now
These offerings are valid for students of TUM (Germany)