CSE378/525: Spring 2018 Introduction to Robotics

Tue Thu 5:30-6:50 Old Computer Science 2119

Dimitris Samaras


Course Description:

The objective of this course is to use a hands-on approach to introduce the basic concepts in robotics, focusing on mobile robots and illustrations of current state of the art research and applications. Course information will be tied to lab experiments; students will work in teams to build and test increasingly more complex robots, either in Matlab/Simulink or using actual robotics platforms, such as . Parrot AR Drone, Lego Mindstorm, and Intel Galileo. Basic concepts will be discussed, including coordinate transformations, sensors, path planning, kinematics, feedback and feedforward control, stressing the importance of integrating sensors, effectors and control. The last part of the course will focus on applying the knowledge from the initial lectures to the key approaches to mobile robot control (reactive, behavior-based, and hybrid), and briefly discuss robot learning and multi-robot systems. The last month of the lab will be spent in applying the learned material to a final project, in which the students will design and build a robot for a final demonstration. This course is intended for graduate students with interests in Robotics, Visual Computing, AI. Prerequisites include a foundation in Linear Algebra and Calculus, and the ability to program, preferably in Python, Matlab and C/C++.



Week 1.

Introduction Defining Robotics Brief History

Week 2.

Basic Imaging for Robotics. Coordinate Transformations, Sensing

Week 3.

Quiz 1, Probabilistic robotics

Week 4.

Localization and Mapping,

Week 5.

Mobile Platforms, Path Planning

Week 6.

Quiz2, Review

Week 7.

Inertial Navigation,

Week 8.

Midterm, Effectors and Actuators,

Week 9.

Direct Kinematics, Dynamics. Inverse Kinematics,

Week 10.

Feedback Control, Quiz 3

Week 11.

Reinforcement Learning

Week 12.

Deep Learning

Week 13.

Behavior-based control

Week 14.

Group Robotics

Week 15.

Final Projects


Recommended textbooks:



There will be homeworks, a final project, 3 in class 30 min quizzes and a midterm exam. Homeworks will be 35%, the project 30%, and the exams 35%. Weights are approximate and subject to change. You are expected to do homeworks (4) by yourselves. Even if you discuss them with your classmates, you should turn in your own code and write-up.  Final projects can be done by one or two people. Two people projects will be scaled accordingly.

Midterm date: March 20, 2018
You can have one sheet of paper with notes in the midterm and quizes.

Academic misconduct policy:

Don't cheat. Cheating on anything will be dealt with as academic misconduct and handled accordingly. I won't spend a lot of time trying to decide if you actually cheated. If I think cheating might have occurred, then evidence will be forwarded to the University's Academic Judiciary and they will decide. If cheating has occured, an F grade will be awarded. Discussion of assignments is acceptable, but you must do your own work. Near duplicate assignments will be considered cheating unless the assignment was restrictive enough to justify such similarities in independent work. Just think of it that way: Cheating impedes learning and having fun. The labs are meant to give you an opportunity to really understand the class material. If you don't do the lab yourself, you are likely to fail the exams. Please also note that opportunity makes thieves: It is your responsibility to protect your work and to ensure that it is not turned in by anyone else. No excuses! The University has a relevant policy:


Each student must pursue his or her academic goals honestly and be personally accountable for all submitted work. Representing another person's work as your own is always wrong. Any suspected instance academic dishonesty will be reported to the Academic Judiciary. For more comprehensive information on academic integrity, including categories of academic dishonesty, please refer to the academic judiciary website at http://www.stonybrook.edu/uaa/academicjudiciary/ _

____________ Adopted by the Undergraduate Council September 12, 2006 ________

Disability note:

If you have a physical, psychological, medical or learning disability that may impact on your ability to carry out assigned course work, I would urge that you contact the staff in the Disabled Student Services office (DSS) in the ECC building (where the Computer Store used to be), Telephone number: 632-6748v/TDD. DSS will review your concerns and determine with you what accommodations are necessary and appropriate. All information and documentation of disability are confidential.

Contact info:

    D. Samaras, Tel. 631-632-8464
    email: samaras@cs.sunysb.edu
    Office Hours: Tue. 3pm to 4:30 & Thu. 12.30pm to 2pm, or by appointment
                         New Computer Science room 263


TA: Ke Ma:

email: kemma@cs.stonybrook.edu

Office Hours: Mon. 2 to 4 pm, new CS 156