ROB 498 /599: Computational Human-Robot Interaction Fall 2023

Instructor: Christoforos Mavrogiannis (cmavro at umich dot edu)

GSI: Manohar Bhat (manubhat at umich dot edu)

Lectures: Tu/Th 15:00 - 16:30 (1060 FMCRB)

Class material: Piazza; ROB 599 Canvas; ROB 498 Canvas

Office hours: Tu/Th at 16:30-17:30 (3248 FMCRB)

Course description: This is an advanced course (3 units), covering computational techniques that enable robots to work with and around people. Topics will include estimation, planning, and control techniques, discussed in the context of applications like crowd navigation and collaborative manipulation. Besides algorithmic foundations, the course will explore topics in experiment design, discussing evaluation methodologies that will enable smooth deployment of robots in human environments. Through student-led paper presentations and a team project, students will gain exposure to the state of the art in computational HRI.

Learning objectives: In this class, students will gain exposure to computational techniques used to develop human-robot interaction (HRI) applications and systems and get familiar with the process of interpreting and presenting research. Specifically, by the end of the class, students will be able to:

Prerequisites: There are no formal prerequisites but mathematical maturity (e.g., ROB 101, Math 215, IOE 265) and programming background (e.g., ROB 320 or EECS 281) are expected. A foundation on the design of human-robot systems (e.g., ROB 204) is recommended.

Textbook: There is no official textbook. Background for most of the course components can be found in the book Computational Human-Robot Interaction by Thomaz, Hoffman and Cakmak (pdf). Background on probability and filtering can be found in Probabilistic Robotics by Thrun, Burgard, and Fox (pdf). Additional background on planning can be found in Planning Algorithms by Lavalle (pdf).


The grading will be based on the performance along the following components:

Syllabus: A more detailed syllabus document can be found here.

Acknowledgements: This class is inspired by HRI classes at USC, Cornell, and Berkeley.

© 2023 Christoforos Mavrogiannis