Office hours
Instructor:
Time: Tuesday 14:00 - 15:30, or by
appointment
Office: GDC 3.432
Email:
jsinapov--AT--cs--DOT--utexas--DOT--edu
Teaching assistant and Mentors:
The TA and the mentors can meet you in the lab, GDC 3.414b.
TA
Shih-Yun Lo | yunl@ut | T | 10 am to noon |
W | 3 pm to 5 pm |
Mentors
Ricardo Delfin Garcia | ricardo.delfin.garcia@gmail | T | 5:00 to 7:00 pm |
W | 5:00 to 6:00 pm | ||
Th | 6:00 to 7:00 pm | ||
Roy Falik | roy.falik@ut | T | 2:00 to 4:00 pm |
F | 2:00 to 4:00 pm | ||
Arjun Karpur | arjun.karpur@gmail | M | 2:00 to 3:00 pm |
W | 9:30 to 11:30 am | ||
Th | 12:30 to 2:00 pm | ||
Carson Moore | carsonatxmoore@gmail | T | 2:30 to 4:30 pm |
W | noon - 2:00 pm | ||
Th | 2:30 to 4:30 pm | ||
Rishi Shah | rishi@cs.utexas | M | 2:00 to 4:00 pm |
W | 4:00 to 6:00 pm | ||
Nicholas Walker | nickswalker@icloud | M | 2:00 to 4:00 pm |
W | 4:00 to 6:00 pm | ||
F | 11:00 to noon |
Final Projects
The final project presentation schedule is avaialbe here.
- Title: Semi-Robust Detection and Following of Individuals
Team: Michael Brenan, Saket Sadani, Victoria Zhou
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Using Machine Vision to Follow A Moving Agent
Team: Zara Louis, Angelo Cioffi, Derek Hudson
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Implementing Multi-Floor Intelligence within a Moving Elevator
Team: Arnav Jain, Ashay Lokhande, Brahma Pavse
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Responding to Voice Commands
Team: Nathan John, Peter Thai, Briana Vargas
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Following a Person
Team: Michael Tirtowidjojo, Hector Fraire, Shailen Patel
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Robot Operation via Natural Voice Control
Team: Vincent Lee, Calvin Ly, Benjamin Chen
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Directional Communication Via LED Lights
Team: Aylish Wrench, Annie Phan
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: A Denunciation of The Monochrome
Team: Cristian Martinez, Erin Vines, Sabrina Herrero, Tijani Oluwatimilehin
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Emotional BWI Segway Bot
Team: Sangjin Shin
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Website to Display Robot Data
Team: Walter Sagehorn and Jonathan Butler
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Implementing Eulerian Video Magnification
Team: Kathryn Baldauf and Kiana Alcala
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Robotically Enhanced Snack Dispenser and Retrieval System
Team: JosieKate Cooley, Jacqueline Gibson, and Ashvin Govil
Proposal: [PDF] Final Report:[PDF] Github:[Link] - Title: Displaying local weather conditions through LEDs
Team: Justin Kang
Proposal: [PDF] Final Report:[PDF] Github:[Link]
Class Diary (including links to slides and readings)
- Affective Computing and Human-Robot Interaction
Slides from class: [PDF]
Main Reference: Picard, R. (1995) Affective Computing - Introduction to Reinforcement Learning
Slides from class: [PDF]
Guest Slides [author unknow]: [PDF]
Main Book Reference: Reinforcement Learning: An Introduction [PDF] - 4/28 Autonomous Tool Use
Slides from class: [PDF]
Optional Readings: [1] [2] - 4/26 Introduction to Machine Learning
Slides from class: [PDF]
- 4/21 Multimodal Perception
Slides from class: [PDF]
Optional Readings: [1] [2] [3]
- 4/19 The Sense of Touch
Slides from class: [PDF]
- 4/14 No Class -- work on your projects
- 4/12 About the robots...
Slides from class: [PDF]
move_base_client code from class: [ZIP] - 4/7 Model Registration and People Detection in PCL
Slides from class: [PDF]
- 4/5 Image Features and Registration
Slides from class: [PDF]
Assigned Readings: an article you find, plus Chapter 1 from here. - 3/31 Computer Vision in 3D: Point Cloud Library
Slides from class: [PDF]
Code from class: [ZIP] - 3/29 Theories of Vision
Slides from class: [PDF]
Assigned Readings: [1] [2]
- 3/24 Computer Vision: Motion
Slides from class: [PDF]
Homework 6 (due 4/5): [TXT]
move_base_client code from class: [ZIP]
OpenCV code from class: [ZIP]
- 3/22 Computer Vision: 2D Images
Slides from class: [PDF]
Assigned Readings: [1] [2] [3]
Code from class: [ZIP] rosbag: [ZIP]
- 3/10 Computational Perception of Natural Sound
Slides from class: [PDF]
- 3/8 Where in the world is the robot? a.k.a Robot Localization and Mapping
Slides from class:[PDF]
Assigned Readings: [1] [2] [3] - 3/3 Robot Bodies in ROS
Slides from class:[PDF]
Homework 5: [TXT]
- 3/1 Embodiment
Assigned Readings: [1] [2] [3]
Slides from class: [PDF]
- 2/25 Multi-Agent System / ROS Launch / Homework 4
Slides from class: [PDF]
Code from class: [ZIP]
- 2/23 Services in ROS II
Assigned Readings: [1]
[2]
[3]
Slides from class: [PDF]
Code from class: [ZIP]
Homework 4 (due Friday 3/4): [PDF]
- 2/18 Behavior-Based Robotics
Slides from class: [PDF]
- 2/16 Services in ROS
Assigned Readings: [1]
[2]
Slides from class: [PDF]
Code from class: [ZIP]
- 2/11 Turtlesim Controller (Part 2)
Slides from class: [PDF]
Code from class: [ZIP]
Homework 3 (due 2/18) - 2/9 Turtlesim Controller
Assigned Readings: [1] [2] [3]
Slides from class: [PDF]
Code from class: [ZIP] - 2/4 Introduction to ROS (Part 3)
Homework 2 (due 2/11)
Slides from class: [PDF]
Code from class: [ZIP] - 2/2 - Introduction to ROS and Linux Shell (Part 2)
Slides from class: [PDF]
Assigned Readings: [1] - 1/28 - Introduction to ROS and Linux Shell
Slides from class: [PDF]
Homework 1 (due 2/4) - 1/26 - C++ Tutorial (Part 2)
Assigned Readings: [1] [2] [3]
Slides from class: [PDF]
Code from class: [ZIP] - 1/21 - C++ Tutorial (Part 1)
Slides from class: [PDF]
Code from class: [ZIP] - 1/19 - Class Introduction
Assigned Readings: [1] [2] [3]
Slides from class: [PDF]
Course Overview
The focus of this course is on research involving intelligent and autonomous robots. In particular, specific topics covered this semester will include human-robot interaction, computational perception, and developmental robotics. Throughout the semester, the students will use the mobile robots that are currently part of the building wide intelligence (BWI) project. The idea is to have a pervasive intelligence throughout the building, in the form of robots that will perform a variety of tasks, such as leading people to their destinations or locating a person in the building.
The main goal of this course is to complete a small research project, advancing the abilities of the current BWI system.
Participation in the class discussions will also form a significant part of the grade. Class meetings will consist of discussions based on assigned readings and updates on project progress.
Philosophy and Goal
The foremost goal of this course is to expose the student to the full range of activities required of a real-life computer science researcher. It turns out that computer scientists rarely read textbooks, sit silently in lectures, work on programming assignments with correct and complete answers, or take exams. Rather, they
- read about and critically assess original research;
- speak in public;
- collaborate effectively with peers;
- devise solutions and/or approaches to open-ended problems; and
- write about these solutions and/or approaches.
This course presents an opportunity for students to help decide whether they would enjoy going on to graduate school and an eventual career as a computer science researcher. In particular, students will be required to read published research papers, write brief reactions to them, participate in class discussions, propose and execute a solution to a challenging open-ended problem, and write about their work. They will be given an opportunity to collaborate with other students on the final project.
Course Requirements
Grades will be based on
- class participation (10%);
- written responses to the readings; (10%)
- preliminary assignments; (60%)
- a final programming project. (20%)
Students should post responses to the readings on Canvas. Credit will be based on evidence that you have done the readings carefully. The response should include a summary of the reading along with any of the following:
- Insightful questions;
- Clarification questions about ambiguities;
- Comments about the relation of the reading to previous readings;
- Critiques on the research;
- Critiques on the writing style or clarity;
- Thoughts on what you would like to learn about in more detail;
- Possible extensions or related studies;
- Thoughts on the paper's importance; and
- Summaries of the most important things you learned.
Prerequisites
A strong interest in the question, ``What is intelligence and how can it be implemented in a physical robot?''
For best results take two lectures weekly. Common side effects may include sleepless nights, broken robots, nervousness, and banging head on keyboard. Frequent visits to the mentors and the TA have been shown to alleviate some of those symptoms. Talk to your instructor if this class is right for you.
Text and Website
There is no textbook for this course. Instead, relevant research papers will be initially assigned, and later chosen by the students following their interests.
Academic Dishonesty Policy
All work ideas, quotes, and code fragments that originate from elsewhere must be cited according to standard academic practice. Students caught cheating will automatically fail the course. If in doubt, look at the departmental guidelines and/or ask.
Notice about students with disabilities
The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. To determine if you qualify, please contact the Dean of Students at 471-6529; 471-4641 TTY. If they certify your needs, I will work with you to make appropriate arrangements.
Notice about missed work due to religious holy days
A student who misses an examination, work assignment, or other project due to the observance of a religious holy day will be given an opportunity to complete the work missed within a reasonable time after the absence, provided that he or she has properly notified the instructor. It is the policy of the University of Texas at Austin that the student must notify the instructor at least fourteen days prior to the classes scheduled on dates he or she will be absent to observe a religious holy day. For religious holy days that fall within the first two weeks of the semester, the notice should be given on the first day of the semester. The student will not be penalized for these excused absences, but the instructor may appropriately respond if the student fails to complete satisfactorily the missed assignment or examination within a reasonable time after the excused absence.
Credits
This course was previously taught by Matteo Leonetti who developed some of the course content, assignments, etc. If you enjoyed the course, feel free to send him a thank you note. Some of the lectures on Computational Perception and Developmental Robotics were originally developed and/or influenced by Professor Alexander Stoytchev at Iowa State University. If you enjoy them, feel free to send a thank you as well.
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