CIS 700: Integrated Intelligence for Robotics

Fall 2016, University of Pennsylvania

Instructor:  Eric Eaton, Ph.D.


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 colored in blue, which have very tentative dates at this point and are more likely to shift than topics coming up soon.

Wk Date Topic Reading Comments                 

W 8/31
Introduction to Course & Project
(Prof. Eaton)

Introduction to ROS
(Guest speaker: Chris Clingerman)

M 9/5
Labor Day (no class)

W 9/7
Discussion: Project Planning

M 9/12
Architectures for Integrating Perception, Learning and Control: case studies of the
Stanford STAIR & CMU CoBots
Other resources:

W 9/14
Discussion: Project Planning

M 9/19
Architectures for Integrating Perception, Learning and Control: the
DARPA Robotic Challenge
W 9/21
Getting Started Due
M 9/26
Architectures for Integrating Perception, Learning and Control:
the DARPA Grand & Urban Challenges

W 9/28
Architectures for Integrating Perception, Learning, and Control: Layered Learning
M 10/3
Computer Vision for Object Recognition & Scene Understanding
(Prof. Eaton)
Focus Group proposals due

Other resources:
W 10/5
Deep Learning for Object Recognition & Scene Understanding

Other resources:
M 10/10
Deep Reinforcement Learning

Project Team proposals due
W 10/12
Discussion on Project Designs

8 M 10/17
Inverse Reinforcement Learning
(Brooks & Mendez)
Other resources:
W 10/19 Multi-task and Transfer Learning
(Rostami & Willett)
Project Design Due
M 10/24
Lifelong Machine Learning
(Prof. Eaton)
Other resources:
W 10/26
RoboBrain Project & Cloud Robotics
Other resources:

M 10/31
Intermediate Task Demonstration 1
Intermediate Documentation Due
W 11/2
Novel Object Grasping & Manipulation
Other resources:
M 11/7
Grasping in Cluttered Environments
(Baucom & Yeung)

W 11/9
Planning in Dynamic Environments
(Gilbert & Thompson)
Other resources:
12 M 11/14
Intermediate Task Demonstration 2

HTN Planning in Continuous Deployment
(Prof. Eaton)
Handout - Reading Packet on Planning and HTNs Intermediate Documentation Due
W 11/16
Anytime Path Planning/Re-planning

13 M 11/21
Discussion on Projects

W 11/23
No Class (Friday class schedule)

14 M 11/28
HRI: Learning from Demonstration
Other resources:
W 11/30
Intermediate Task Demonstration 3

Intermediate Documentation Due

Optional Resources: Collaborative Problem Solving

M 12/5
HRI: National Language Interfaces
W 12/7
Social, Economic & Privacy Considerations of Personal Robots
(Kent & Wright)
Other resources:
M 12/12
In-class working day to coordinate final projects

Optional resources: Multi-Robot Coordination &
RoboCup Soccer

Wed 12/21 @2pm
Final Project Showcase

All Final Project Submissions Due by 12/22

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.


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.


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:


Photo of Eric Eaton


Eric Eaton, Ph.D.

E-mail: -- Make certain you put "[CIS 700]" at the start of the subject line to ensure a quicker response.

Office Hours: Mondays/Wednesdays 10:30-11:30am

Office: Levine 264

Course Policies


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.

Whenever you e-mail me, be sure to use a meaningful subject line and include the phrase "[CIS 700]" at the beginning of the subject line. Your e-mail will catch my attention and I will respond quicker if you do this. I make an effort to respond to e-mails within 24 hours on weekdays and 48 hours on weekends.  However, unless it is a private matter, you should be posting your questions/issues to 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.


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:
Topic Presentations: 20%
Seminar and Course Participation:
Project - Proposal / Getting Started Task:
Project - Design:
Project - Intermediate Milestone Performance / Documentation:
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:

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 project team)
Open Collaboration
(but remember, you will be graded on YOUR effort)
  • reading summaries
  • topic presentation(s)
  • "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.