Introduction to Human-Robot Interaction and Practicum

Course Description

In this undergraduate class, you will learn about the theory and algorithms that enable robots to account for people in their decision making in a principled way. You will learn the basic interaction strategies in between humans and robots. The important aspects of the interaction will be discussed. We will explore the ways to make the interaction both efficient and comfortable. We will learn methods to observe and measure this relationship. The practicum will include the hands-on experiments and programming sessions where you will observe, measure and write programs according to the user's preferences for simple robots. Evaluation will be based on a mid-term and a final exam, attendance, quizes and research paper readings.

Invited Speakers

We had three valuable speakers at our lectures in Spring 2022-2023 Semester. We thank our speakers for their great talks and providing insights to our students.
  • XAI Talk by Senka Krivić (20.04.2023): Senka Krivić is an Assistant Professor at the Faculty of Electrical Engineering at the University of Sarajevo. Formerly, she spent several years as a Research Associate at the Department of Informatics at King's College London as a member of the Planning and Reasoning Group and the Human-AI Teaming (HAT) lab. She obtained her Ph.D. degree in Computer Science from the University of Innsbruck at Intelligent and Interactive Systems Group.
  • "Human-robot interaction from the perspective of autonomous vehicles" Talk by Anne Spalanzani (27.04.2023): Anne Spalanzani is a full Professor at University Of Grenoble-Alpes and a researcher at Chroma Team, Inria. Her research focuses on navigation and autonomous vehicles (cars and wheelchairs) in dynamic and human populated environments.
  • "Robot learning from and for interactions with humans" Talk by Oya Çeliktutan (04.05.2023): Oya Çeliktutan is an Associate Professor and Senior Lecturer in Robotics in King’s College London  at Faculty of Natural, Mathematical, & Engineering Sciences, UK. She is the Head of Social AI and Robotics (SAIR) Lab. She obtained her PhD degree in Electrical and Electronic Engineering from Bogazici University, Turkey, in collaboration with the National Institute of Applied Sciences of Lyon, France. After her PhD, she spent five years as a postdoctoral researcher in the Personal Robotics Lab, Imperial College London; Graphics and Interaction Research Group (Rainbow), University of Cambridge; and Multimedia and Vision Research Group, Queen Mary University of London. In 2018, she joined King's College London as a Lecturer in Robotics.

Learning Objectives

At the end of this course, you will gain knowledge about human-robot interaction evaluation and improvement of this relationship. When you finish this course, you should be able to:
  • The main concepts of HRI
  • Learn basic approaches to imitate human motions.
  • Analyze the design and implementation of a user study to evaluate algorithms for HRI
  • Types of interaction between humans and robots
  • Application types for HRI
  • Research Methods for HRI

Tentative List of Topics

  • Robot Properties
  • Bayesian Inference
  • Experimental design
  • Collaboration in human-robot teams
  • Learning from demonstration
  • Application types for HRI
  • Research Methods for HRI
  • Interaction Types for HRI
  • Emotions in HRI

Tentative List of Topics for Lab

Prerequisites

Basic Python. There are no other formal prerequisites, but knowledge of probability theory and linear algebra is encouraged.

Grading

MT1 %30
Final %40
Attendance %10
Readings and Quizes %20

Grading for Lab

Participation in Other Experiments as Subjects %20
Final Project %40
Programming and Analysis of Outcomes %40

Textbook

You can use the following books:
Bartneck, C., Belpaeme, T., Eyssel, F., Kanda, T., Keijsers, M., & Sabanovic, S. (2020). Human-Robot Interaction – An Introduction. Cambridge: Cambridge University Press. (Download)
Thomaz, Andrea, Guy Hoffman, and Maya Cakmak. “Computational human-robot interaction.” Foundations and Trends in Robotics 4, no. 2-3 (2016): 105-223. PDF
Probabilistic Robotics. Thrun, Burgard, & Fox, MIT Press, 2005.
Programming Robots with ROS: A Practical Introduction to the Robot Operating System. Quigley, Gerkey, & Smart, O’Reilley, 2015.

Expectations

You can expect me to come to class on time, clearly communicate, give you feedback on a timely manner, adjust lecture material based on performance on presentations and quizzes. I can expect you to come to class on time, be attentive and engaged in class, take notes and ask questions when something is not clear, spend an adequate amount of time on the class each week (at least 3 hours), spend 60-80 hours on your class.