About this Class

mushr robotic car being driven through remote control

Why take this class? 

Robots have made a profound impact in our lives. It is almost impossible to imagine a world without them. Without robots, we would not have phones (mass-produced by robot manipulators), delivery services (fulfilled by mobile robots), or affordable electronics. But still, robots have ways to go. Open-ended problems with robots are endless from space exploration, self-driving, and general-purpose home assistants. In this class, we will take the first steps to creating machines that can think and act (robots). We will go over the fundamentals of robotic behavior by studying robot kinematics, dynamics, and control. Following this, we will study how robots can plan long-term behaviors in their environments without crashing into obstacles. Finally, we will see how modern ideas in optimization and AI can enable robotic grasping, self-driving, and walking. This introductory course will focus on understanding foundational robotic concepts, while broadly looking at their application in the real world.

What are you expected to do?

This class is aimed towards advanced undergraduates and particularly towards students who want to learn robotics and robot AI, but who have never worked on a robot before. This will be a HW and project driven class. There will be no mid-term or final exams. Instead, you will be expected to implement concepts discussed and taught in this class. 

Prerequisites

  • Linear algebra, basics of probability, solving basic differential equations
  • Coding in Python and familiarity with Ubuntu OS.

Lecture

  • Lectures will be held in person.
  • The class will be recorded, we will post the link to the recorded lectures to the class campuswire.

Grading

  • Homeworks (45%)
  • Final Project (45%)
  • Discussions, both in class and in campuswire (10%)

Assignments

  • Assignments will use Python 3; we will provide you a virtual environment to install all dependencies.
  • We strongly recommended using Python for the project as well.

Final Project

  • Project proposals (1 page) will be due a week before midterms.
  • Maximum (and recommended) team size is 4.
  • Final presentations of all projects will take place a week before finals.

Course Textbook

This class is quite broad and hence there is no one textbook. Each lecture/topic will hence be accompanied with online reading material and chapters of relevant textbooks. 

Course Staff

  • Instructor: Lerrel Pinto
  • Teaching Assistant: Ben Evans
  • Teaching Assistant: Sneha Silwal

Office Hours

TBD

Remarks

  • A student in this course is expected to act professionally. Please also follow the CS regulations on academic integrity found here: https://cs.nyu.edu/home/undergrad/policy.html
  • Academic accommodations are available for students with disabilities. Please contact the Moses Center for Students with Disabilities (212-998-4980 or mosescsd@nyu.edu) for further information. Students who are requesting academic accommodations are advised to reach out to the Moses Center as early as possible in the semester for assistance. Please also email the instructor so appropriate accommodations may be made.

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