Professor: Andrea Bajcsy (abajcsy [at] cmu [dot] edu)
Office Hours: Tues, 12:20 - 1:20 pm (after class)
Office Hours Location: NSH 4629
Teaching Assistant: Pranay Gupta (pranaygu [at] andrew [dot] cmu [dot] edu)
Office Hours: Mon, 4:00 - 5:00pm
Office Hours Location: NSH 4504
Lecture Time: Tues & Thurs, 11:00 - 12:20 pm
Lecture Location: Wean 4623
Syllabus: PDF
Canvas: https://canvas.cmu.edu/courses/41578
Overview
Human-robot interaction (HRI) is a multidisciplinary field that aims to create successful interactions between people and robots.
In this class, we will study algorithmic HRI topics such as mathematical human models, trajectory forecasting, shared autonomy, robot learning from human feedback, active learning, communication, and safety.
This course aims to provide an overview of the state of the art in algorithmic HRI.
As such, it will cover a large number of topics, with examples drawn from foundational work and research published in the last five years.
The course combines lecture, readings, in-class presentations, written reports, and a final project to engage students with the current challenges and approaches in the field.
The course also emphasizes the practice of reading and discussing scientific literature to learn and communicate about the most recent progress in HRI.
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News
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[11/21/24] Lecture notes 11 uploaded
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[11/20/24] New extended deadline for final project report: Dec 12!
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[11/14/24] Lecture notes 10 uploaded
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[10/29/24] Lecture notes 9 uploaded
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[10/10/24] Lecture notes 8 uploaded
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[10/08/24] Update: Class cancelled on Thur, Nov 7 because Andrea travels to Conference on Robot Learning
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[10/08/24] Lecture notes 7 uploaded
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[09/24/24] Prof. Dylan Losey's guest lecture slides uploaded
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[09/23/24] Consider using the AI Maker Space in Tepper for your projects! Contact Manager: Greg Armstrong (ai-makerspace@cs.cmu.edu)
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[09/17/24] Lecture notes 5 uploaded
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[09/05/24] Lecture notes 4 uploaded
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[09/03/24] Lecture notes 3 uploaded
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[09/02/24] Small updates to the first two week schedule and papers
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[08/29/24] Lecture notes 1 and 2 uploaded
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[08/19/24] New room location: Wean 4623
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Schedule (tentative)
Date |
Topic |
Info |
Week 1 Tue, Aug 27 |
Lecture Introduction |
- Please check the course syllabus
Materials:
Slides
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Week 1 Thurs, Aug 29 |
Lecture Fundamentals |
Single-Agent Decision Making
Materials:
Notes
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Week 2 Tue, Sept 3 |
Lecture Fundamentals |
Single-Agent Decision Making (cont'd)
Materials:
Notes
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Week 2 Thurs, Sept 5 |
Lecture Fundamentals |
Probability, Bayesian inference
Materials:
Notes
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Week 3 Tue, Sept 10 |
Paper discussion Fundamentals |
Required reading:
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Week 3 Thurs, Sept 12 |
Paper discussion Mathematical Human Models |
Required Reading:
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Week 4 Tue, Sept 17 |
Lecture Trajectory Forecasting |
Planning-based & learning-based; applications in manipulation, navigation
Materials:
Notes
Slides (project examples)
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Week 4 Thurs, Sept 19 |
Paper discussion Trajectory Forecasting |
Required reading:
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Week 5 Tues, Sept 24 |
Guest Lecture Shared Autonomy |
Due Project Proposal
Dylan Losey (Prof @ Virginia Tech)
Materials:
Slides
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Week 5 Thurs, Sept 26 |
Paper discussion Shared Autonomy |
Required reading:
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Week 6 Tue, Oct 1 |
Lecture Experimental Design |
Designing and conducting user studies
Materials:
Slides
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Week 6 Thurs, Oct 3 |
Paper discussion Experimental Design |
Required Reading:
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Week 7 Tue, Oct 8 |
Lecture Research Skills: Figures & Visuals |
Due Homework
What makes a visual or plot "good"? Is there a process we can follow?
Further Reading:
Materials:
Slides
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Week 7 Thurs, Oct 10 |
Lecture Research Skills: Technical Writing |
What is good technical writing? How can we become better writers?
Materials:
Slides
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Week 8 Tue, Oct 15 |
No Class (Fall Break) |
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Week 8 Thurs, Oct 17 |
No Class (Fall Break) |
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Week 9 Tue, Oct 22 |
Guest Lecture Robot Learning from Human Feedback |
Tesca Fitzgerald (Prof @ Yale)
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Week 9 Thurs, Oct 24 |
Paper discussion Robot Learning from Human Feedback |
Required Reading:
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Week 10 Tue, Oct 29 |
Guest Lecture Active Learning (Michelle Zhao) |
Due Mid-term Report
Information gain, Asking questions
Materials:
Slides
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Week 10 Thurs, Oct 31 |
Paper discussion Active Learning |
Required Reading:
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Week 11 Tue, Nov 5 |
No Class (Democracy Day) |
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Week 11 Thur, Nov 7 |
No Class (Andrea at CoRL) |
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Week 12 Tue, Nov 12 |
Paper discussion Communication |
Required Reading:
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Week 12 Thur, Nov 14 |
Guest Lecture HRI as a Game (Lasse Peters) |
Influence-aware planning
Materials:
Slides
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Week 13 Tue, Nov 19 |
Paper discussion HRI as a Game |
Required Reading:
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Week 13 Thurs, Nov 21 |
Lecture Safety & Uncertainty Quantification |
Decision-theoretic & statistical safety for HRI
Materials:
Slides
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Week 14 Tue, Nov 26 |
Paper discussion Safety & Uncertainty Quantification |
Required Reading:
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Week 14 Thurs, Nov 28 |
No Class (Thanksgiving) |
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Week 15 Tue, Dec 3 |
Final presentations |
Due Slides uploaded to Canvas Dec. 2, 11:59pm ET
Presenters: [Allison Chu, Cherry Bhatt, Sheen Cao], Yizhuo (Ethan) Di, Haoze He, [Louis Plottel, Yingxin Zhang], Will Heitman, Jasmine Kim
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Week 15 Thurs, Dec 5 |
Final presentations |
Presenters: [Lyuxing He, Lingkan Wang], Ellen Lee, Taiming Zhang, Arthur Fender Bucker, Diana Frias Franco
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Week 16 Tue, Dec 10 |
No Class (Final Exams) |
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Week 16 Thurs, Dec 12 |
No Class (Final Exams) |
Due Final report uploaded to Canvas by Dec 12, 11:59pm ET
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