Course Personnel

Seth Hutchinson (course instructor)
216 College of Computing Building
801 Atlantic Dr NW
Atlanta, GA 30332

Grad TAs

Jake Williams, jakewilliams@gatech.edu
Vishvak Murahari, vishvak.murahari@gatech.edu
Ria Verma, rverma35@gatech.edu 903056431
Abhinav Jain, jain@gatech.edu 903003010

Undergrad TAs

Matthew Kaufer , mjkaufer@gmail.com
Raghav Raj Mittal, raghavmittal@gatech.edu
Brian Cai , briancai@gatech.edu
Abhinav Agarwal, aagarwal95@gatech.edu
Varun Ramachandran, varun30@gatech.edu
Adele Sun, ysun379@gatech.edu
Robert Cooper, rcooper39@gatech.edu
Jinghua Zhang, jzhang866@gatech.edu
Nikhil Ramesh, nikhilramesh97@gatech.edu
Hua "Austin" Jiang, huajiang@gatech.edu

Logistics

Lectures will be held in Room 1443 of theKlaus Advanced Computing Building, Tuesdays and Thursdays, 9:30-10:45pm.

Course Objectives

Upon completing this course, students will be able to

describe and explain what robots are and what they can do
describe mathematically the position and orientation of an object
develop a control architecture for a mobile robot system
implement sensor-based navigation and localization algorithms
write moderately complex Python programs to control a robotic system

Communication with Course Staff and Peers

We will use Piazza for course announcements, questions, and discussion.

For the best and fastest response, we ask that you post your questions on Piazza instead of sending email. If others are likely to have a similar question or benefit from the answer, make a public Piazza post. Feel free to make private posts to the course staff if your question concerns a solution, your grade or other private information. You can also reach out to your group lead TA for questions.

We encourage everyone to actively contribute to discussion, answer each other’s questions and generally use Piazza as broadly as possible to make the course run smoothly. Cozmo is a new platform, with a frequently changing SDK, so please check Piazza regularly for updates. We recommend configuring the email settings to send new post notifications in real time, not at the end of the day.

Prerequisites

The only formal prerequisite is CS1332 Data Structures & Algorithms. Prior knowledge of fundamentals of linear algebra and probability is helpful, but not required. Background in AI and Machine Learning is not assumed.

Grading

Quizzes:	36%
Labs:	60%
Participation	4%

Quizzes

There will be 8 quizzes throughout the semester. For each student, the two quizzes with the lowest grade will be dropped, and the remaining 6 quizzes will each be worth 6% of the final course grade. Because the lowest quizzes are being dropped, we will not be rescheduling quizzes missed due to travel, job interviews and minor illnesses. Special considerations will be made for extenuating circumstances.

Labs

There will be 6 lab assignments throughout the semester, each worth 10% of the final grade. Lab 1 will be completed individually, and labs 2-6 in pairs. Lab grades will be determined using the grading rubric provided with each lab assignment.
Late Policy: All lab assignments are due at the time and date indicated on the assignment document. Up to two late days are allowed, but a grade penalty of 50% and 75% will be applied at the first and second day, respectively. For example, a 100-point lab completed one day late would only receive at most 50 points. Since most labs require a live demo for grading (usually done in class), please contact a TA well ahead of time to schedule a time to demo your solution if you are missing class or are making a late submission.

Beginning with Lab 2, all lab assignments will be completed in pairs using a shared Anki Cozmo robot. Partner arrangements are not fixed and can change throughout the semester. In fact, we encourage anyone not satisfied with their partner to find a new partner to work with. We can help to facilitate partnering arrangements if needed.

You and your partner will receive a Cozmo robot to use for the semester that you will return, with all accessories, at the end of the course. Each Cozmo will be numbered and we will keep track of who has which robot. At the end of the semester, you are responsible for returning the robot for which your name is listed. If you switch teams and start using a new robot, please email one of the TAs and they will update the spreadsheet.
Note: The Cozmo robots are the property of the College of Computing, and the College may charge a fee of up to $175 for the cost of the robot if it is not returned at the end of the semester.

Participation

The participation grade will be based on peer review by your partner(s) at the end of the semester.

Academic Integrity

These days, cheating is remarkably easy. Using today's search engines, one can likely find answers to most any question that might be asked in this course. When discussing your homework with fellow students, it can be tempting to copy their work, and to include it in your submitted assignments. You should resist the temptation to do such things.
Review Georgia Tech’s Academic Honor Code. If, after reading this, you still have questions, feel free to raise these with the course instructor. Any work you present as your own should represent your own understanding of the material. When external sources were used as significant points of information (sample code, etc.), the source must be referenced in your submission. Following Georgia Tech’s guidelines, all suspected cases of academic cheating will be forwarded for review by the Office of Student Integrity.