Socially Intelligent Robotics Project - 2023 Home


Welcome to SIR Project-2023! This is the main information for the course. This is where you will be directed to all information pertaining to course content and logistics. Enjoy!

1. General course information

Course code: XM_0076

Duration: 4 weeks - Period 3 (Jan 2023)

Level: Master (Artificial Intelligence)

Credits: 6 EC

Link to the study guide: https://studiegids.vu.nl/EN/courses/2021-2022/XM_0076

Schedule and locations:
Plenary session: Monday 13:30-15:15 @Social AI lab (NU-11A93)

Practical sessions: @Social AI lab (NU-11A93) (physical attendance mandatory except for extraordinary circumstance)

Mondays 9:00 – 13:00

Wednesdays 9:00 – 13:00

Thursdays 13:00 — 17:00

Fridays 9:00 – 13:00, 13:00 – 17:00

Your group should sign up beforehand for the lab sessions through this link (the link will be updated each Friday for the subsequent week). Each slot has a capacity of 2 groups.

Instructor: Kim Baraka

Teaching assistants (your main point of contact):

Kelly Spaans k.e.spaans@student.vu.nl (TA coordinator)

Geo Juglan g.juglan@vu.nl

Oromia Sero o.g.sero@student.vu.nl

Vasiliki Vasileiou v.vasileiou@student.vu.nl

2. What is this course about?

Robots are expected to enter several aspects of our daily lives (e.g., shopping malls, airports, hotels, the home) and will be expected to be socially intelligent for smooth integration in human environments. This project is a continuation of the Socially Intelligent Robotics course, and focuses on applying AI techniques to socially interactive robots. In a period of 4 weeks, students will program capabilities for the social robot Pepper and evaluate its performance in an interactive setting involving one or more human(s). Examples of such capabilities would be social cue detection algorithms, e.g. emotion, gaze, or similar, or behavioral capabilities for generating expressions, e.g., learnt from human users. The specific choice of work (which will be held in groups) will be specified during the project.

3. Organization

The course consists of three main components:

  • Practical sessions @VU campus where you will have access to a Pepper robot to work in groups on your project assignment (see assignment page)
  • Plenary sessions in which discussions happen, feedback is given to the groups, and course material is occasionally presented

4. Grading

You will be graded based on your code and your final presentation, which will include a short oral presentation, a live demo, and a Q&A session. Specific rubrics can be found below.

Your are expected to keep a concise but comprehensive logbooIn case we find clear differences in what and how much individual group members have contributed to the final result (deliverables), we may take this into account and differentiate grades for individual group members. We will use input from the TAs who will discuss with your group each week to establish such differences.

Presentation 40%

Creativity of solution: Does the solution show a creative effort beyond "vanilla" approaches?

Specificity of the approach and project goals: Are the goals set for the project clearly laid out and reasonable in scope?

Complexity of the technical approach: To what extent does the solution go beyond a simple FSM?

Justification of design choices: Are the design choices properly motivated and justified in terms of domain knowledge?

Organization of the slides: Are the slides well organized and form a coherent story?

Discussion (10%)

Critical thinking: Do the students show a critical perspective on their own work, including acknowledging and proposing solutions to limitations?

Understanding: Do the students answer concretely and specifically within the scope of the question and without irrelevant details?

Demo (25%)

Demonstrability of the technical approach: Is personalization and/or learning visible in the demo setup?

Richness of the interaction: To what extend is the interaction "flowy", multi-modal, and natural?

Software (25%)

Modularity: Is the code properly organized in modules that can be easily extended in future iterations?

Cleanliness: Is the code easy to read, well documented, including giving proper credit to non-original code?

Complexity: Does the code demonstrate significant effort at integrating multiple libraries and functionalities together in a complex but elegant way?

Individual contribution as assessed by logbook (-0.5 to +0.5)

5. Corona rules

The latest Corona measures can be access here.

Please follow this decision tree to check whether or not you are allowed to be on campus, e.g., after travel, or if you or someone you were in contact with test positive.

If you haven’t done so already, we encourage you to:

6. Inclusivity statement

We strive to offer students with a safe and inclusive classroom environment. We welcome the perspective of students of all ethnicities, genders, spiritual beliefs, and sexual orientations, among others. If you feel discriminated on the basis of your identity, please report it to the course staff.

If you have a disability and require accommodations, please let us know before the beginning of the course so that we can discuss your accommodations and needs to make the course as accessible to you as possible.

7. Academic integrity and code of conduct

Plagiarism is not tolerated for both reports and code. You are welcome to use any code you see fit for your project, as long as you appropriately cite your sources both in the report and in the code itself (as comments).

Any behavior that violated the VU rules for academic integrity and code of conduct will not be tolerated.