Syllabus

Objectives

This course is primarily designed for students who are new to robotics but want to get a quick exposure to various aspects of robotics development, including hardware, ROS, autonomous navigation, computer vision and machine learning, etc. It covers the industry best tools, workflows and practices, and bridges the gaps between academia courses and solutions to practical challenges in robot and robotics application development.

Prerequisites

A basic understanding of electronics, computer network and programming is assumed. Hands-on experience with CAD tools and 3D printing is also required.

Office Hours

After class, or by appointment, or post your questions in the forum provided for this purpose.

Grading Policy

• Labs (50%): 8 graded lab sessions, each worth 4-8%
• Final project (50%): demonstration (25%), presentation (15%), report (10%)

Class Policy

Regular attendance of both the lectures and lab sessions are essential and expected.

Academic Honesty

Lack of knowledge of the academic honesty policy is not a reasonable explanation for a violation.

Tentative Schedule

You can find the course schedule on this page.

Main References

As the course covers a wide variety of topics, students are encouraged to search and learn from resources from the Internet. The following is a short list of useful books that will be touched during the course. You may need to consult them occasionally.

• Roland Siegwart, Illah Reza Nourbakhsh and Davide Scaramuzza, Introduction to Autonomous Mobile Robots, Second Edition, MIT Press, 2011.
• Jason M. O’Kane, A Gentle Introduction to ROS , Independently published, 2013.