Sertac Karaman

Associate Professor of Aeronautics and Astronautics,

Laboratory for Information and Decision Systems,

Institute for Data, Systems and Society,

Massachusetts Institute of Technology

UNDERGRADUATE TEACHING

16.30/16.31
Feedback Control Systems

Feedback Control Systems is an advanced control theory course offered by the AeroAstro Department at MIT. Both undergraduate students and graduate students can enroll in this course. The course teaches state-space methods for control theory with applications in aerospace and beyond.

 

In the Spring '15 semester, the course will feature drone experiments. We will give each student Parrot's minidrone, Rolling Spider, which they will keep till the end of the semester. Students will use our Matlab/Simulink toolbox to program their control systems into the drone.

 

Course Website: http://dronecontrol.mit.edu

github page: https://github.com/Parrot-Developers/RollingSpiderEdu

 

Taught in semesters:

  • Fall 2015
  • Fall 2014
  • Fall 2013

 

Next offering: Fall 2016

6.141J/16.405J
Robotics: Science and Systems

The Robotics: Science and Systems course is a technical elective that teaches robotics to undergraduate students throughout MIT. The course features laboratory exercises for mechanical design, control systems implementation, as well as software development for planning and perception.

 

 

Taught in semesters:

  • Spring 2016
  • Spring 2015 (jointly with Nicholas Roy)

 

Next offering: Spring 2017

16.82 and 16.821
Flight Vehicle Engineering

The Flight Vehicle Engineering (16.82) and Flight Vehicle Development (16.821) are the aeronautics capstone courses for AeroAstro students. The Flight Vehicle Design course is offered in the fall semester, when the students design a flight vehicle concept for a real customer. The Flight Vehicle Engineering is a follow-up that is offered the following spring, when the students build the concept which they designed in the Fall.

 

In the most recent offering in Spring 2015, the students designed and built an autonomous airplane that can land on water, and autonomously recognize and dock to a submersible charging station. The seaplane used computer vision algorithms to identify the charging station when on water.

 

Students designed and built the flight vehicle, the embedded systems hardware, as well as the embedded software. The embedded hardware included a Raspberry Pi2, an inertial measurement unit, a GPS unit, and a video camera. The embedded software was implemented using the lcm and libbot libraries. The computer vision code was written in C++ using the OpenCV libraries.

 

 

Taught in semesters:

  • Spring 2015 (jointly with Mark Drela and John Hansman)
  • Spring 2014 (jointly with Mark Drela)
  • Spring 2013 (jointly with Mark Drela and John Hansman)
  • Fall 2012 (jointly with Mark Drela and John Hansman)

GRADUATE TEACHING

16.499S
Advanced Planning Algorithms

The Advance Planning Algorithms course is intended for starting graduate students working in robotics or control theory. The course teaches algorithmic methods for several planning and control problems in a unified manner. Topics include path planning, motion planning, motion planning with temporal logic specifications, planning under uncertainty, and differential games.

 

Taught in semesters:

  • Spring 2014

6.241J/16.338J
Dynamic Systems and Control

Dynamic Systems and Control is an introductory graduate course that teaches the foundations of control theory. The course covers linear systems, modern control theory, optimal control theory as well as nonlinear systems.

 

Taught in semesters:

  • Spring 2013 (jointly with Jonathan How)

OUTREACH

RACECAR for High Schoolers:
The Beaver Works Summer Institute

The RACECAR class is now offered for high school students. In the summer of 2016, the course was offered to 46 high-school students coming from across the United States. In a 4-week residential program, the students learned the foundations of robotics in theory lectures, practiced their skills in hands-on laboratory exercises. The class also included lectures on teamwork and collaboration, as well as seminars from established researchers in the field and experienced entrepreneurs. Students demonstrated their learning in a final course challenge. They designed and implemented software for fully autonomous mini race cars.

RACECAR Hackathon

The RACECAR hackathon is a short course offered annually during the Independent Activities Period (IAP), which takes place on the month of January. The students are taught the basics of robotics in seven lectures, and they practice skills in short laboratory exercises using a mini race car platform.

 

The mini race cars are built on a standard RC race car platform. They are governed by Nvidia's latest embedded supercomputer, the Nvidia Jetson. They also have a laser scanner, a camera, an inertial measurement unit, and a visual odometer on board.

 

The course features a three-day hack-a-thon-style competition. Students design and implement software that allows their mini race cars to navigate as fast as possible in MIT's tunnels.

 

Here is a video describing the course and showing the winner's flawless run through MIT's corridor:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

For more information: http://racecar.mit.edu

 

Taught in semesters:

  • IAP 2017 (jointly with  Mike Boulet, Ken Gregson, Owen Guldner)
  • IAP 2016 (jointly with Luca Carlone, Mike Boulet, Ken Gregson, Owen Guldner)
  • IAP 2015 (jointly with Mike Boulet, Owen Guldner, and Mike Park)

 

 

TEACHING SCHEDULE

CURRENT & FUTURE TEACHING

Spring 2017:

6.141J/16.405J: Robotics: Science and Systems

PAST TEACHING

IAP 2016:

Fall 2016:

Summer 2016:

Spring 2016:

IAP 2015:

Fall 2015:

Spring 2015:

 

IAP 2015:

Fall 2014:

Spring 2014:

 

Fall 2013:

Spring 2013:

 

Fall 2012:

IAP RACECAR

16.30/16.31: Feedback Control Systems

RACECAR Summer Program for High Schoolers

6.141J/16.405J: Robotics: Science and Systems

IAP RACECAR

16.30/16.31: Feedback Control Systems

6.141J/16.405J: Robotics: Science and Systems

16.821: Flight Vehicle Development

IAP RACECAR

16.30/16.31: Feedback Control Systems

16.82: Flight Vehicle Engineering

16.499S: Advanced Planning Algorithms

16.30/16.31: Feedback Control Systems

6.241J/16.338J: Dynamic Systems and Control

16.821: Flight Vehicle Development

16.82: Flight Vehicle Engineering