Project Description
The AVS Lab is looking for a motivated undergraduate student who can assist with on-going work to apply reinforcement learning (RL) techniques to spacecraft operations problems. This work will deploy reinforcement learning agents trained in simulation on-board a real spacecraft for a flight demonstration. The student will help develop the Python tools used to make calls to the spacecraft’s API to assemble observations (i.e., spacecraft position and velocity, reaction wheel speeds, etc.) and take actions (i.e., determine which targets to image). Students with experience in the Python and C++ programming languages are encouraged to apply. Additionally, experience in dynamics and controls (coursework or otherwise) will help the student quickly ramp up.
Special Requirements
- Sophomore/Junior in Aerospace Eng., Computer Science, Mechanical Eng., or Electrical Eng.
- Experience with Python and C/C++
- Basic understanding of dynamics
- Able to work independently given high-level guidance
- Able to commit to 5-10 hours per week
Contact
- Hanspeter Schaub (faculty)
- Adam Herrman (graduate student)