CIS 700: Integrated Intelligence for Robotics

Fall 2018, University of Pennsylvania

Instructor:  Eric Eaton, Ph.D.


Schedule

The following schedule lists the tentative dates, presenters, and readings for each topic in this course.  Topics and readings are subject to change.  We may end up shifting topics slightly earlier or later in the schedule, depending on unanticipated events.  This is especially the case for topics in later weeks, which have very tentative dates at this point and are more likely to shift than topics coming up soon.
Wk Date Topic Reading Comments                 
1




W 8/29
Introduction to Course & Project
(Prof. Eaton)

Introduction to ROS and ROS Programming
  • E. Eaton. Teaching integrated AI through interdisciplinary project-driven courses. AI Magazine 38 (2), 2017.

2
M 9/3
Labor Day (no class)

W 9/5
Service Robot Overview
(Prof. Eaton)


3
M 9/10
Project Discussion
(Prof. Eaton)
  • Read all 2017 Team and Focus Group Reports

W 9/12
Project Planning
(Prof. Eaton)

4
M 9/17
Architectures for Integrating Perception, Learning and Control: case studies of the
Stanford STAIR & CMU CoBots
(Prof. Eaton)
Getting Started Due
W 9/19
In-Class Working Session
(Prof. Eaton out-of-town)
1:30-2:10pm Meet with project teams
2:10pm - 2:50pm Meet with focus groups


5
M 9/24
Architectures for Integrating Perception, Learning and Control: the
DARPA Robotic Challenge
(Arjun Kumar)

W 9/26
Architectures for Integrating Perception, Learning, and Control: Layered Learning
(Fernando Cladera Ojeda)

6
M 10/1
Discussion on Project Designs
Getting Started Due
W 10/3
Discussion on Project Designs (Continued)
Focus Group Designs Due
7
M 10/8
Deep Learning for Object Recognition & Scene Understanding Other resources:
W 10/10
Deep Reinforcement Learning

8 M 10/15
Progress Demos / Discussion

Focus Group Progress Demo 1
W 10/17 Inverse Reinforcement Learning Other resources:
9
M 10/22
Lifelong Machine Learning
(Prof. Eaton)
Progress Check-in
W 10/24
In-Class Working Session
(Prof. Eaton out-of-town)

Team Project Design Due
10
M 10/29
In-Class Working Session
(Prof. Eaton out-of-town)


W 10/31
Progress Demos / Discussion
Focus Group Progress Demo 2
11
M 11/5
Progress Check-In

Progress Check-in / Intermediate Documentation Due
W 11/7
Progress Check-In


12 M 11/12
Planning
(Prof. Eaton)

Team Demo 1 / Focus Group Progress Demo 3
W 11/14
HTN Planning
(Prof. Eaton)

Handout

13 M 11/19
Planning in Dynamic Environments Progress Check-in

Other resources:

W 11/21
No Class (Friday class schedule)


14 M 11/26
Anytime Path Planning/Re-planning Team Progress Demo 2
W 11/28
Novel Object Grasping and Manipulation TBA

15
M 12/3
Grasping in Cluttered Environments Progress Check-in
W 12/5
HRI: Learning from Demonstration
16
M 12/10
TBA

Team Progress Demo 3 / Initial Merge Deadline

TBA
Final Project Showcase

All Final Project Submissions Due by 12/17

Course Description

In order for robots to operate alongside humans in complex, unstructured, uncertain environments, they require substantial intelligence. However, the field of artificial intelligence (AI) has fragmented into various subfields, each studying different aspects of intelligence in relative isolation. The problem of designing intelligent robotic systems that persist in everyday environments provides an opportunity to reintegrate these different aspects of AI into a complete intelligent system.

In this project-based seminar course, students will study and develop an intelligent personal robot assistant, integrating perception, manipulation, learning, planning, and interaction. The resulting versatile robot will be capable of learning and performing a variety of tasks in real-world environments and collaborating effectively with humans. In addition, students will study a variety of advanced AI topics, including high-level perception and reasoning, scalable knowledge representation, lifelong/multi-task learning, integration of perception and control, learning from demonstration, and human-robot interaction.


Prerequisites

At least TWO (2) of the following courses:

Course Format

This course will include two major components:

  1. A seminar-style discussion of various topics in integrated intelligence
  2. A semester-long project developing an integrated intelligent personal assistant robot


Optional Textbook

Although there are plenty of online resources on ROS, I would highly recommend that you pick up the following textbook:

Programming Robots with
              ROS Cover Image
Programming Robots with ROS: A Practical Introduction to the Robot Operating System (1st Edition)
by Morgan Quigley, Brian Gerkey, William D. Smart.  O'Reilly.


Syllabus

We will study the following topics:

These topics and due dates are all subject to change. Readings for each of these topics will include a variety of journal articles, conference papers, and technical reports.


Key Due Dates

In addition to the major project milestone dates:


Instructor

Photo of Eric Eaton

INSTRUCTOR

Eric Eaton, Ph.D.

Please use Piazza for all course-content-related questions and personal issues, and Slack for all project-related questions/issues.

Office Hours: Mon/Thurs 12:30 - 1:30pm

Office: Levine 464




Course Policies

Communication

Attendance and active participation are expected in every class. Participation includes asking questions, contributing answers, proposing ideas, and providing constructive comments.

As you will discover, I am a proponent of two-way communication and I welcome feedback during the semester about the course. I am available to answer student questions, listen to concerns, and talk about any course-related topic (or otherwise!). Come to office hours! This helps me get to know you. You are welcome to stop by and chat. There are many more exciting topics to talk about that we won't have time to cover in-class.

Please use Piazza for all course-content-related questions and personal issues, and Slack for all project-related questions/issues. I make an effort to respond to messages within 24 hours on weekdays and 48 hours on weekends.  For private matters, be sure to use a private message on Piazza.

Although computer science and robotics work can be intense and solitary, please stay in touch with me and the other students in the course, particularly if you feel stuck on a topic or project and can't figure out how to proceed. Often a quick e-mail, face-to-face conference, or Piazza post can reveal solutions to problems and generate renewed creative and scholarly energy. It is essential that you begin assignments and projects early, since we will be covering a variety of challenging topics in this course.


Piazza logoWe will be using Piazza as the course message board.  We also make course-wide announcements through Piazza, be sure to sign up for it.  You are responsible for the content of all announcements on Piazza.


Grading

Your grade will be based upon your paper summaries and reading journal, topic presentations, seminar participation, and the semester project.  All assignments must be submitted according to the assignment submission instructions.

At the end of the semester, final grades will be calculated as a weighted average of all grades according to the following weights:

Paper Summaries:
15%
Topic Presentations: 15%
Seminar and Course Participation:
10%
Project - Getting Started Task
3%
Project - Focus Group Design 3%
Project - Team Project Proposal/Design 4%
Project - Focus Group Progress Demos
7%
Project - Intermediate Milestone Performance / Documentation:
8%
Project - Final Report / Showcase / Documentation / Final Task Performance: 35%
Total: 100%

All grades are given individually, including for the team components (e.g., the final project report).  This means that all members of the team may not receive identical grades for the same component; individual adjustments may be made based on the reported contribution of each team member.

Incomplete grades will be given only for verifiable medical illness or other such dire circumstances.

All graded work will receive a percentage grade between 0% and 100%.  Here is how the percentage grades will map to final letter grades; percentages are not rounded:

Percentage
Letter grade

Percentage Letter grade
97% <=
A+ (4.0)
77% <= C+ (2.3)
93% <= A (4.0) 73% <= C (2.0)
90% <= A- (3.7) 70% <= C- (1.7)
87% <= B+ (3.3) 67% <= D+ (1.3)
83% <= B (3.0) 60% <= D (1.0)
80% <= B- (2.7) < 60%
F (0.0)

The instructor reserves the right to adjust the percentage ranges for each letter grade upward in your favor.


Academic Integrity

All work in this course is subject to the University's Academic Integrity policy.  Violations of the academic integrity policy or the course collaboration policy will incur consequences according to university regulations.  Penalties for academic dishonesty may lower the final grade in the course.  If one student shares materials inappropriately with another student, both the donor and the recipient of the code are in violation of the academic integrity policy and will be referred to the Office of Student Conduct.

If required by any assignment, you must list all people you worked with or consulted, and all resources you consulted during the completion of the assignment.


Submission and Late Policy

All work must be turned in either in hard-copy or electronic submission, depending on the instructions given in the assignment.  E-mailed submissions will not be accepted, unless specified in the assignment instructions.  Extensions will be given only in the case of verifiable medical excuses or other such dire circumstances, if requested in advance.

Late submissions will not be accepted in this course.  All work must be turned in on-time.


Collaboration Policy

I want to encourage you to discuss the material and work together to understand it. Here are my thoughts on collaborating with other students, faculty, etc.:

Summary table:

Individual Work
Individual or Partnered Work
Isolated Team Work
(only members of your focus group / project team)
Open Collaboration
(but remember, you will be graded on YOUR effort)
  • reading summaries
  • topic presentation(s)
  • "getting started" ROS tutorials
  • "getting started" task
  • all written project documents
  • understanding the readings and topics
  • completing the project / tasks (you must document all assistance)

If you have any questions as to what types of collaborations are allowed and which are dishonest, please ask me before you make a mistake.


Electronic Devices

I have no problem with you using computers or tablets to take notes or consult reference materials during class.  Tempting though it may be, please do not check e-mail or visit websites that are not relevant to the course during class.  It is a distraction, both for you and (more importantly) for your fellow classmates.  Please silence your phones and computers when you enter class.