Introduction to Robotics

Level:
Open to students entering grades 11 or 12 or freshman year of college in the fall
Session:
II - July 17–August 3, 2018
Days & Time:
Monday–Friday, 11:10 a.m.–1:00 p.m. and 3:10–5:00 p.m
Teacher(s):
Michael Liebis
Prerequisites:

No previous experience with robotics or programming is required, but participants should have an aptitude for logical reasoning and systematic thinking.

Course Description

Participants in this course develop a foundation in robotics covering design, construction, and computer programing. They build robots using VEX robotics parts and programmed in ROBOTC, a C based language. Lectures on topics drawn from physics, engineering, and computer science are combined with hands-on group projects.

Lecture topics include kinematics, torque, motors, gear ratios, sensors, and control loop feedback mechanisms. In the hands-on projects, students observe, for example, that their robots are not able to drive in a straight line without sensors. This leads to an exploration of gyroscopes and encoders so as to correct the problem and eventually to a lecture on PID control and a gentle introduction to the concept, from calculus, of integration.

In the final week of the course, the students form into teams and build robots that compete against each other to perform a task taken from a prior robotics competition.

Participants are expected to bring laptops for this class. Laptops can be either PC or Mac, but should have 8 to 10 GB of free space. Students who have already taken A.P. Physics or A.P. Computer Science may find that they are already familiar with many key concepts covered in this course and are encouraged to consider a different curricular option.

Teacher(s)

Michael Liebis

Michael Liebis holds a B.S. in applied mathematics from Columbia University and an M.S. in mathematics from Polytechnic University. He has done extensive graduate work in scientific computing with a focus on machine learning at New York University’s Courant Institute of Mathematical Sciences. Michael currently coaches the FRC robotics team at the Chapin School, teaches AP computer science at Dwight Global, and serves as a consultant for an international school in Shanghai. Prior to teaching he worked in quantitative trading, heading up algorithmic trading groups at Chase Manhattan Bank and at Millennium Partners LLC. 

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Specific course detail such as hours and instructors are subject to change at the discretion of the University. Not all instructors listed for a course teach all sections of that course.