SE- Human-Robot Interaction

Human-Robot Interaction (HRI)

Course Description

In this seminar, the current research studies on human-robot interaction (HRI) will be introduced. The course content involves both theoretical (such as embodiment, anthropomorphism, and emotions) and practical (e.g., HRI experiment design, robot types and sensors, and programming machine learning pipeline) aspects of human-robot interaction. We will particularly focus on interdisciplinary studies at the intersection of psychology, neuroscience, and robotics. Additionally, the Pepper humanoid and Nao robots will be available – depending on the Covid regulations in HU-Berlin– for designing and performing HRI experiments.

Update: According to HU-Berlin's summer semester policy and due to Covid-19, the lectures, assignments, and presentations will be held online via Zoom.

Prerequisites

Some experience with machine learning, programming, and robotics is required. Although we will not assume that you have an extensive background in these fields, basic understanding below-listed items will be necessary to follow the content of the course.

Linear Algebra: Throughout the course, we will intensely perform Matrix and vector operations to construct our machine learning pipelines. You should be familiar with the basics and notations of matrix/vector calculus.
Probability and Statistics: You should have (at least) a sound knowledge of the basic probability and statistics concepts: random variable, probability distribution, conditional probability, mean, variance, etc.
Programming: The programming language of this course is Python 3. If you are comfortable with other programming languages (e.g., C++/Matlab), the tutorials will help you to code in Python.
Tools/libraries: You should be familiar with software development tools and libraries: Git, TensorFlow, Keras, Numpy, Matplotlib (or Seaborn), etc.

During the first weeks of the course, we will point out supplementary resources to introduce the bare minimum requirements of the course. Additionally, we will arrange tutorial sessions on machine learning engineering to introduce common tools and practices to develop machine learning pipelines and deploy the machine learning models into simulated robot platforms.

Objectives

Upon completion of this seminar course, students will be able to:

develop hands-on programming skills to build machine learning pipeline for HRI experiments
understand state-of-the-art HRI studies and critically evaluate them
grasp the working principles of different robots and their usage in HRI experiments
design basic HRI experiments

Human-Robot Interaction (HRI)

Course Description

Prerequisites

Objectives

Instructors