AeroAstro Undergraduate Research Opportunities

Below are Undergraduate Research Opportunities currently open in MIT Aeronautics and Astronautics. Note that while a project may have started (first date under "Project duration") the UROP position is still open. For more information about, or to apply for, any of the positions, contact the person at the end of each listing. For general questions regarding AeroAstro UROPS, contact mas [at] mit.edu (Ms. Marie Stuppard).

AeroAstro labs wishing to submit a UROP opening may do so via our online form (certificate required).

RC Aircraft Flights for Lightning Strike Research

Affiliated Lab/Research Group
Project description

Do you want to use your hobby to contribute to research? We need an experienced RC pilot to fly a 2 meter wing-span fixed-wing aircraft, that will be mounted with a system to electrically charge and discharge an aircraft in flight.

The Aerospace Plasma’s group is doing hands-on research to investigate the static charging of aircraft. The objective of this project is to demonstrate that we can artificially control the electrostatic potential of the aircraft (~40 kV) using ion emission.

The student will have the opportunity to develop the testing platform, which can include machining, low voltage and high voltage circuits and electronics, telemetry, and, of course, flying the research aircraft to collect data! 

Prerequisites

We are looking for one or two UROPs with piloting experience for RC fixed-wing aircraft. An interest in experimental, hands-on research.

The UROP can be for credit or direct funding from the UROP office.

Interested? Reach out to the contact above and include a resume and a few sentences about any prior RC airplane, electronics, hardware development, physics, and systems experience.

Project duration
to
Students who may apply
Freshman
Sophomore
Junior
Senior
Compensation
For Credit
For Pay

For more information or to apply, contact:

Ben Martell

Machine Learning for Atmosphere Modeling for Space Situational Awareness

Affiliated Lab/Research Group
Project description

Are you an undergraduate student interested in using AI methods to improve atmosphere models for satellite orbit predictions? Join the ARCLab this spring to explore how machine learning can help make spaceflight safer.

The space sector is growing fast with increasing number of launches each year and plans for mega satellite constellations to provide worldwide internet connectivity. More satellites in space however also means a higher risk of spacecraft collisions. Potential collisions can be avoided by predicting the trajectories of satellites and maneuvering the spacecraft to safety. 

The goal of this UROP is to use machine learning techniques to improve atmosphere models for satellite orbit predictions. The atmosphere namely affects the orbits of satellites due to drag. Accurate modelling of the atmosphere is however challenging and models are computationally expensive such that one needs high performance computing to use them. 

In this project, the UROP student will apply machine learning (ML) to improve the speed and accuracy of atmosphere models. The ML models will be trained using atmospheric data and the use of different ML techniques (such as autoencoders and recurrent neural networks) to improve atmosphere forecasts will be explored. The outcome of this research project has the potential to result in a publication. 

Funding is available for this UROP this semester. Prospective UROP students should either be comfortable programmers or have a background and interest in AI/machine learning or numerical methods.

Project duration
to
Students who may apply
Freshman
Sophomore
Junior
Senior
Compensation
For Pay

For more information or to apply, contact:

David Gondelach

Space Situational Awareness UROP

Affiliated Lab/Research Group
Project description

Are you an undergraduate student interested in using AI methods to understand and predict satellite behavior? Join a team of researchers this spring to learn more about space situational awareness (SSA) and study the near-Earth space environment. 

This UROP aims to build a train-test database to support explorations of new AI and machine-learning techniques for satellite maneuver detection and characterization. Improved techniques for satellite maneuver detection and characterization increase the accuracy of analysts' efforts to extrapolate the future positions of satellites to avoid collisions, detect unusual or hazardous behaviors on-orbit, and improve the ability to correlate multiple discrete observations to a particular satellite or satellites.  

UROP students will join a mixed-discipline team of researchers to learn about the data and methods used to estimate satellite orbits, develop AI approaches to determine satellite behavior and detect changes, and decide how to identify unexpected satellite maneuver behavior and goals. Students will work with real, historical satellite data to develop and publish a database of orbital maneuvers to better understand the history of satellite operations in the most popular orbital regimes around the Earth.

More specifically, Spring 2020 UROP students will:

  1. Locate and integrate publicly available sources of satellite maneuver truth data with a real observation data-set provided for this project, as well as U.S. government two-line element data. Use this integrated dataset to create a train-test database for AI-powered satellite maneuver detection and characterization. 
  2. Transform observations into orbit estimates for spacecraft.
  3. If time and student interest permits, develop AI/machine-learning tools to identify maneuvers from optical telescope observations and/or TLEs.

This UROP is open to all students, including those funded by the UROP office and those pursuing course credit. For a credit UROP, interested students should submit a proposal by the UROP deadline and add 16.UR to their registration. Students who participated in the fall 2019 SSA-AI UROP are specifically encouraged to apply and will have priority.

Project duration
to
Students who may apply
Freshman
Sophomore
Junior
Senior
Compensation
For Credit
For Pay

For more information or to apply, contact:

Miles Lifson

Robotic Docking with Tumbling Space Objects

Affiliated Lab/Research Group
Project description

The Space Systems Lab (SSL) is bringing its space robotics research to the next generation! The SSL’s SPHERES platform aboard the International Space Station (ISS) is getting a capable successor, Astrobee, a robotic free-flyer with a manipulator arm running the Robotic Operating System (ROS). Astrobee can see through multiple cameras and sensors, grapple payloads, interact with astronauts, and is reprogrammable for a wide range of space autonomy research.

This project, one of the SSL’s first on Astrobee, aims to demonstrate planning, estimation, and control techniques needed to dock with and grapple tumbling objects. These techniques are essential in order to mitigate space debris, fix broken satellites, and assemble large space structures. UROP(s) will work with the Astrobee Gazebo simulator, learn about autonomy algorithms, and collaborate on code for ISS and ground testing. Write code to run in space, work with a modern space robotics platform, and engage in cutting-edge space autonomy research through this UROP. 

We are looking for one to two motivated UROPs with a passion for space and robotics. Interested? Reach out to the contact below. Please include a resume and a few sentences about any prior coding, math, and space systems experience. Prior experience with Linux, ROS, C++, Python, and exposure to controls/estimation is highly desirable.

Faculty supervisor: Prof. Richard Linares

Project duration
to
Students who may apply
Freshman
Sophomore
Junior
Senior
Compensation
For Credit
For Pay

For more information or to apply, contact:

Keenan Albee

Spin Ap: A Dynamic Testbed for a Spinning Apperture Satellite

Affiliated Lab/Research Group
Project description

Spinning aperture (Spin Ap) satellites have the potential to decrease the size, weight, and cost of in-space telescopes. The SSL is currently working on a dynamics and controls testbed to test the feasibility of such a spacecraft that only uses a rotating rectangular “strip” for a mirror. Whether you are interested in controls, dynamics, hardware, software, microprocessors, or CubeSats please join us in developing what could be the next big spinoff in remote sensing technology. The goal of this UROP project is to get the testbed up and running by the end of the semester. Possible tasks include setting up a reaction wheel controller, development of a PCB board, and integration of all the subsystems (reaction wheels, gyros, camera and magnetorquers, etc.) into the full testbed.

Project duration
to
Students who may apply
Sophomore
Junior
Senior
Compensation
For Credit
For Pay
Faculty supervisor

For more information or to apply, contact:

Alejandro Cabrales Hernandez

WaferSat: Design and Prototyping of Tiny Satellites with Huge Potential

Affiliated Lab/Research Group
Project description

You've heard of the satellite (500 kg). You've heard of the CubeSat (5 kg). The next giant leap is the WaferSat (0.05 kg). As satellites get smaller, they get lighter, easier to launch, and less expensive. Although they are small, their lower cost may permit many to be built. By operating them as a team they could provide the same performance as large satellites but at lower cost. The unique feature of WaferSats is that their size is small enough to allow them to be built using Micro-Electro-Mechanical Systems (MEMS) technology. The pervasiveness of MEMS fabrication techniques therefore provides the potential to further reduce cost. The goal of this UROP project is to design and prototype a WaferSat, with a good possibility of your WaferSat being launched into orbit. This project will be conducted as a team UROP with multiple UROP students working together with several faculty and graduate students. A UROP for three or six units is suggested. 

Project duration
to
Students who may apply
Freshman
Sophomore
Junior
Senior
Compensation
For Credit
For Pay
Faculty supervisor

For more information or to apply, contact:

Michael Fifield

ACDL research in computational methods

Affiliated Lab/Research Group
Project description

The MIT ACDL's mission is the advancement and application of computational methods for the design, optimization, and control of aerospace and other complex systems. ACDL research addresses a range of topics including advanced computational fluid dynamics and mechanics; uncertainty quantification; data assimilation and statistical inference; surrogate and reduced modeling; and simulation-based design techniques. 

ACDL typically has ongoing UROP opportunities in all of the lab's focus areas. Prospective UROP students should either be comfortable programmers or have a strong background and interest in applied mathematics and numerical methods—or both. UROPs may be for pay or for credit, by arrangement with the specific faculty supervisor.

Interested undergraduates are encouraged to contact the lab UROP coordinator at the email address listed below. Please include in the email a brief description of your interests as well as your coding and math experience. This will help the coordinators determine if there is a good fit for you within the lab.

ACDL faculty are: David Darmofal, Mark Drela, Woody Hoburg, Youssef Marzouk (director), Jaime Peraire, Qiqi Wang, and Karen Willcox. More information on ACDL research can be found at http://acdl-web.mit.edu and on each faculty member's individual website.

Project duration
to
Students who may apply
Freshman
Sophomore
Junior
Senior
Compensation
For Credit
For Pay
Faculty supervisor

For more information or to apply, contact:

Benjamin Zhang