Socially Intelligent Robotics

2019-2020

Course Objective

The overall objective of this course is that students will be able to
apply basic design skills to create interaction designs for a social
robot and develop key skills of the social robot using AI techniques.

Students will gain an understanding about social robotics and related AI
techniques to control such a robot (e.g., conversational AI, computer
vision aimed at interacting with people, expressing gestures, etc.) and
apply this knowledge for designing a social robotics use case with the
Nao robot (Applying Knowledge and Understanding)
Students will be asked to evaluate their use case prototype on a social
robot, preferably in a real-world context with real potential users
(Making Judgments)
Students will need to present their use case ideas and design in the
course (during lectures) and (outside lectures) work in groups to design
a use case and will need to define and communicate about their
individual roles within their group (Communication).
Students will be challenged to take the initiative and direct their own
learning by designing a specific use case for a social robot, where
their design is grounded in existing (multi-disciplinary) literature
(Learning Skills).

Course Content

In this course we will take a user-centered approach to the design of
social robots and look into AI techniques for developing a social robot
that can interact with human users. We will look at the basic cognitive
skills we expect a social robot to have, including visual perception
(e.g. face recognition), speech recognition and dialogue, emotional
expression through body language, and the architecture for integrating
these various skills to execute them on the robot.

Teaching Methods

Lectures, and practical work (to be done by students in groups).

Method of Assessment

Exam and practical assignment (use case design for social robot).

It will not be possible to redo the practical assignment.

Entry Requirements

Students should have the programming skills (Python) and ability to
learn to use a programming framework for social robots that will be made
available in the course.

Literature

A brief course manual will be made available. The main literature used
will consist of existing literature (papers and other materials) on
social robotics and related AI techniques.

Custom Course Registration

The capacity for this course is 100 students.

General Information

Course Code XM_0074
Credits 6 EC
Period P2
Course Level 400
Language of Tuition English
Faculty Faculty of Science
Course Coordinator prof. dr. K.V. Hindriks
Examiner prof. dr. K.V. Hindriks
Teaching Staff prof. dr. K.V. Hindriks

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Study Group, Lecture
Target audiences

This course is also available as: