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TEL390 Special Topics in Applied Robotics

Credits (ECTS):10

Responsible faculty:Fakultet for realfag og teknologi

Course responsible:Antonio Candea Leite

Campus / Online:Taught campus Ås

Teaching language:English

Course frequency:Annually.

Nominal workload:

Lectures, seminars, workshops, practical exercises, and self-study: approximately 250-300 hours.

  • Lectures/seminars/workshops: 56 hours/4 hours per week;
  • Practical exercises: 54-64 hours, individually or in groups with other students;
  • Work with Master's thesis proposal, term paper, presentations and self-study: 110-130 hours.

Teaching and exam period:This course starts in the autumn parallel. This course has teaching and evaluation during the autumn parallel.

About this course

In this course, students will write a term paper (state-of-the-art review and research articles) and a Master's thesis proposal in applied robotics. First, the students will learn about state-of-the-art topics in applied robotics through (i) individual work by studying scientific publications and monographs, analyzing R&D projects, and preparing/delivering presentations, through (ii) teamwork by attending lectures and participating in seminars/workshops or through other appropriate subjects and methodologies. In the middle of the semester, a joint meeting will be offered to help and discuss the different term papers. One-on-one meetings for individual follow-up can also be scheduled by the teachers. At the end of the semester, a colloquium session will be organized to present all of the term papers.

Learning outcome

Students will acquire in-depth knowledge about a specific topic in applied robotics, learn how to present knowledge in written and oral form according to scientific standards, and gain an overview of current developments in applied robotics. Upon completion of this course, students are expected to have the following general knowledge, skills, and competence:

Knowledge:

  • Get an overview of a particular research area and find relevant literature;
  • Describe the theme of the Master's thesis research, its objective, and its relevance;
  • How to develop research questions, hypothesis, and methodologies;
  • Be aware of the ethical standards in research and scientific integrity.

Skills:

  • Design and write a term paper and a Master's thesis proposal;
  • Describe the research methods and techniques for verification and validation of the results;
  • Systematically record, organize, and analyze theoretical and practical results;
  • Evaluate the pros and cons of a variety of qualitative, quantitative and mixed research methods;
  • Critically assess the use of different research methods and ways of collecting and analyzing data;
  • Discuss the reliability, validity and usefulness of the study and results.

Competence:

  • Take appropriate steps to address your research topic, time- and data management plans;
  • Reflect on the research process and what you learned about scientific research techniques;
  • Seek, receive and provide feedback to colleagues in a positive and constructive way;
  • Write a term paper and a Master's thesis proposal;
  • Report research that is based on your own findings in a scientific and ethical manner.
  • Learning activities

    The student must select a topic on applied robotics and work independently with the term paper and Master's thesis proposal under the guidance of one or more teachers. The student shall also prepare and deliver an oral presentation in a bachelor level based on the term paper to a relevant group of evaluators. Then, the learning activities to engage the students are:

    • Independent study of relevant course material with guidance, as well as presentation for and discussion with your peers and teachers;
    • The students improve their public speaking and presentation skills and become a more effective speaker in the workplace;
    • The students choose a topic, no later than the middle of the course, preferably relevant to their term paper and Master's thesis proposal;
    • The students prepare a presentation and a written technical report on the topic and deliver the presentation to their peers;
    • The students attend the presentations and scientific discussions after the presentations, to build collective knowledge and capability in scientific reasoning goals.
  • Teaching support

    Presentations, workshops, practical exercises, and other information will be available through the course webpage in Canvas.

    During the course, students will share and present their work individually and in groups to a teacher, and also in plenary session to get feedback from peers and faculty.

    Online text editors and grammar checkers can be utilized as support during the writing process.

    Students can also request appointments with the teacher in his office at pre-arranged times and by email.

  • Syllabus

    • Lynn P. Nygaard, "Writing Your Master′s Thesis: From A to Zen", Sage Publications, 2017.
    • David V. Thiel, "Research Methods for Engineers", Cambridge University Press, 2014.
    • Angel Borja, "11 Steps to Structuring a Science Paper Editors Will Take Seriously", Elsevier Connect, 2021.

    The students should also access the Resources for Academic Writing, to find tools and resources to help them in the process of academic writing such as: The Writing Centre, NMBU Scientific Writing Resource Portal (in Canvas) and Search and Write. Extra literature and material from Elsevier Connect database will be consulted and defined at the beginning of the course.

  • Prerequisites

    • TEL240 - Control and Engineering and Automation, ECTS 10.
    • TEL200 - Introduction to Robotics, ECTS 10.
    • TEL211 - Robot Programming, ECTS 10.
  • Recommended prerequisites

    • TEL280 - Mobile Robots and Navigation, ECTS 10.
  • Assessment method

    Assessment is based on participation in seminar/workshop discussions, oral presentation, written term paper and Master's thesis proposal.

    Participation in seminar/workshop discussions and oral presentation must be passed.

    The final grade (A-E/F) will be determined on the basis of the term paper and Master's thesis proposal.



    Portfolio Karakterregel: Letter grades
  • About use of AI

    K2 - specified use of AI:

    In this course, students are encouraged to leverage Artificial Intelligence (AI) tools to enhance their academic work. However, there are specific guidelines regarding the appropriate use of AI assistance.

    Permitted Use of AI Tools:

    • Writing Improvement: AI may be used to enhance grammar, clarity, and structure in students' own writing.
    • Reference Search: Students can use AI tools to identify relevant academic papers, books, and sources for their research.
    • Learning and Concept Clarification: AI-generated explanations of concepts, frameworks, and best practices are allowed.
    • Documentation and Formatting Assistance: AI may be utilized to refine citations, references, and adherence to academic writing standards.

    Prohibited Use of AI Tools:

    • Assignment Writing: AI must not be used to generate entire essays, reports, or significant portions of coursework.
    • Automated Completion of Assignments: Students should not rely on AI tools to produce content that they have not meaningfully contributed to.
    • Plagiarism or Direct Copying: Any AI-generated content that is copied and submitted without personal revision is not allowed.
    • Bypassing Learning Objectives: The intent of this course is to develop critical thinking and writing skills; using AI in a way that circumvents the learning process is strictly prohibited.

    Academic Integrity and Accountability:

    • Disclosure: If AI tools are used for writing improvement or reference searching, students must indicate how and where they utilized AI assistance in their submission.
    • Originality: All submitted work must be the student’s own, with AI acting as a support tool rather than a replacement for personal effort.
    • Consequences of Misuse: Any violation of this policy may result in penalties, including reduced grades, assignment re-submission requirements, or disciplinary action according to the university’s academic integrity policies.

    By adhering to these guidelines, students can take advantage of AI-driven learning while ensuring they develop strong academic and writing skills independently. If there are any questions regarding the use of AI, students should consult those responsible for the course for clarification.

    Descriptions of AI-category codes.

  • Examiner scheme

    An external evaluator will contribute to the appraisal of the term paper and the Master's thesis proposal.
  • Mandatory activity

    Participation in Seminar/Workshop meetings, Oral presentation, Written term paper (state-of-the-art review and research articles) and Master's thesis proposal.
  • Preferential right

    Applied Robotics.

    Students from other science and technology courses are welcome to join, subject to prior approval from the head of the department.

  • Admission requirements

    Science and Technology.