Introduction to Perception and Robotics

Syllabus

Learning Objectives

Upon completion of 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 objects and how they move
• Develop a control architecture for a mobile robotic system
• Implement navigation and localization algorithms based on sensor fusion and environment representation
• Write moderately involved programs in Python and Java to control a robotic system
• Construct, program, and test the operation of a robotic system to perform a specified task

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. The course requires access to a laptop. If you don’t have access to a laptop, please contact the instructor ASAP. All programming assignments will be completed in Python.

Lecture Delivery and Grading Components

Important: You cannot take this class unless you can make the regularly scheduled class periods at 3.30pm.

• Lectures will be pre-recorded and available 2 workdays before class time. Students are expected to watch the lecture before each class time.
• Questionnaires: to reinforce the lecture and prepare for class time, the students will be required to answer a short questionnaire by Sunday evening about the two lectures assigned for viewing. This will count for 5% of your grade.
• Quizzes: there will be 5 modules, as indicated on the schedule. At the end of each module, there will be an online quiz worth 6% of your grade each, for a total of 30%. Quizzes will have a combination of multiple choice and essay questions, as appropriate.
• Q&A: students are expected to attend each class period, Monday and Wednesday at 3.30. Class will start with a 30 minute quick review and Q&A, followed by project-related activities (see below).
• Activities: there will be six projects, each having an in-class activity component which forms an integral part of your participation grade, for a total of 5%. For these activities, you will be placed in groups that will remain stable for two projects, then shuffled.
• Projects: each project will additionally have a powerpoint template that will have to be submitted on Gradescope as a pdf and, possibly accompanied with code and/or videos. Project are released and are due on Fridays, and project deliverables will make up 60% of your grade.

Grading

The grading distribution is:

The Late policy for this course will be 20% per day late.

Academic Integrity

Academic dishonesty will not be tolerated. This includes cheating, lying about course matters, plagiarism, or helping others commit a violation of the Honor Code. Plagiarism includes reproducing the words of others without both the use of quotation marks and citation. Students are reminded of the obligations and expectations associated with the Georgia Tech Academic Honor Code and Student Code of Conduct, available online at www.honor.gatech.edu.

You are expected to implement the core components of each project on your own, but the extra credit opportunities often build on third party data sets or code. That’s fine. Feel free to include results built on other software, as long as you are clear in your hand-in that it is not your own work.

You should not view or edit anyone else’s code. You should not post code to Piazza, except for starter code / helper code that isn’t related to the core project.

Learning Accommodations

If needed, we will make classroom accommodations for students with documented disabilities. These accommodations must be arranged in advance and in accordance with the ADAPTS office (www.adapts.gatech.edu).

Important Links:

• Piazza. This should be your first stop for questions and announcements.
• canvas.gatech.edu will be used for occasional announcements and disseminating the lecture videos .
• Gradescope is where you will submit assignments. It is also available from the Canvas menu.

Contact Info and Office Hours:

Use Piazza to ask questions and seek clarifications. If you have a very specific question (related to your grade etc.) or a question that involves your personal information (your gt id number etc.), make a private post on Piazza.

The TA office hours will be announced, with an accompanying Bluejeans link, in a pinned post on Piazza.

• Binit Shah
• Yetong Zhang
• Rachit Bhargava
• Dashiel Heidt
• Pratyusha Karnati
• Maya Rajan
• John Yi

Acknowledgements

The materials from this class rely significantly on slides prepared by other instructors. Each slide set and assignment contains acknowledgements. Feel free to use these slides for academic or research purposes, but please maintain all acknowledgements.