Robot Interaction

Doel vak

After successful completion of this course, students are expected to be able to:

• Articulate the core themes and challenges in the field of Social Robotics. (Knowledge and insight, Applying knowledge and insight, Judgement)
• Understand the multi-disciplinary contributions that develop Social Robots. (Knowledge and insight, Applying knowledge and insight, Judgement)
• Describe and evaluate main theories from various field to understand how humans interact and communicate with social robots. (Knowledge and insight, Applying knowledge and insight, Judgement)
• Understand, describe and compare screen-based versus robot-based interaction. (Knowledge and insight, Applying knowledge and insight, Judgement)
• Discuss and compare key findings in fundamental areas of Robot Interaction, such as typology of robots; application areas; relating to robots; psychological aspects; language understanding in robots; robots outperforming humans while being worse communicators; modeling theories for performance in robots; ethical considerations. (Knowledge and insight, Applying knowledge and insight, Judgement)
• Develop a good understanding of up-to-date and interdisciplinary scientific research in the field and in various application areas. (Knowledge and insight, Applying knowledge and insight, Judgement)
• Understand and apply an academic multi-disciplinary attitude, academic writing style, search for insights in complex phenomena, theoretical and empirical approaches. (Knowledge and insight, Applying knowledge and insight, Judgement, Communication, Learning skills)
• Apply an analytical approach to model communication in robots. (Knowledge and insight, Applying knowledge and insight, Judgement)
• Exercise reverse engineering, building scenarios, interaction design, concurrent algorithmic approaches. (Knowledge and insight, Applying knowledge and insight, Judgement, )

Inhoud vak

What does it mean when a robot steps out of your computer in physical space and starts interacting with humans as if it were a social entity itself? This course will address various aspects that come into play when physically present robots interact with humans. This course focuses mainly on social robots, humanoids in particular, suited for communicative purposes. We will discuss both sides of the coin: perspectives from the robot-side as well as perspectives from the user-side. Differences and similarities with common computer-based AI (cf. avatars, chatbots) are discussed in comparison to human-robot interaction, exemplified by main application areas (e.g., healthcare, education). Basic models and relevant aspects of the psychology of the user and ethical aspects are also discussed. If robots start talking to humans by themselves, how can they understand each other? Lectures will therefore also address the basics of the computational aspects involved (e.g., the Sense-Think-Act paradigm, and Large Language Models (LLMs)). How to translate theoretical models into effective computer models is another challenge that will not only be lectured on but also practised. A team of lecturers with the respective expertise will lecture on the wide variety of topics in this course. Several practical tutorials/workshops and a hackathon with real robots accompany the lectures to gain hands-on experience regarding the complexities of the human-centered human-robot interaction design and development process.

Aanvullende informatie onderwijsvormen

Lectures on a wide variety of topics related to Robot Interaction, two times a week.

Several practical tutorials/workshops will accompany the lectures as a 3rd meeting in the week. One of these sessions involves a hackathon. Details will be presented in the schedule/syllabus on Canvas.

Toetsvorm

Examination: final examination consisting of a multiple choice test of 40 questions and 5 open essay questions; the combined grade counts for 70% of the final grade for this course.

Assignments related to the workshops are also graded; the averaged grade for assignments counts for 30% of the final grade for this course. Most of these assignments are done in small groups; there is one individual exam preparation assignment.

To pass the course, each assignment needs to be passed. Also, to pass the exam, the separate multiple-choice and essay question sections must be passed (55%) separately to pass the exam.

There is only a resit for the examination.

Literatuur

For this course, you will read a relatively large number of journal articles, book chapters, and conference proceedings. The reading list will be announced on Canvas (in the syllabus) posted on Canvas before the start of the course. Access to journal articles/ book chapters / conference papers via Canvas, or else via the VU-library, check LibSearch, e-resources (e.g., select search in PsycInfo, EBSCOhost), else Google Scholar, or http://dx.doi.org

Aanvullende informatie doelgroep

Overige informatie

A detailed syllabus will be posted on Canvas in advance (approx. a week before the start of this course).

Use of generative AI is only permitted for orientation and brainstorming

In this course, generative AI (GenAI), such as ChatGPT or similar tools, may only be used for orientation and brainstorming, for example, to explore ideas or clarify questions. GenAI may not be used to generate content that becomes part of the final submission. The final product must be based entirely on the student's own understanding, analysis, and wording. Incorrect use of GenAI is considered fraud. If established, the submitted work or assessment result will be declared invalid, and the Examination Board may impose further measures.

Exception: During the hackathon, the use of generative AI (GenAI), such as ChatGPT or similar tools, is permitted. GenAI may be used as a fully integrated tool in developing the human-robot interaction (e.g., coding assistance, troubleshooting, dialogue content generation, etc.). The student remains responsible for the quality, accuracy, academic integrity, and accountability of the submitted work.

Toelichting Canvas