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Rocket Landing "Guidance for Fuel Optimal Diverts" in Python

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Falcon Heavy Demo Mission

G-FOLD Python

Guidance for Fuel Optimal Landing Diverts (GFOLD)

This code reimplements GFOLD algorithm in Python with use of the fantastic cvxpy utility. The algorithm was defined by a number of papers, but chiefly this paper by Ackimese, Carson, and Blackmore at JPL.

What you can do with GFOLD-Python

What you can't do with GFOLD-Python

  • Attitude control
  • Robust control
  • Control of any kind (this is a guidance algorithm!)

How to use it

  • If you wish to do a static calculation (not generating C code)

    1. Define your vehicle and environment in GFOLD_Static_Parms
    1. Comment / Uncomment the constraints you wish to have in GFOLD_Static
    2. Run python GFOLD_Static.py (requires scipy)
    3. View the "evil" plots (this name is just a joke btw)
  • If you wish to do C code generation

    1. Set test = 0 at the top of GFOLD_Generate.py
    2. Run python GFOLD_Generate.py (requires cvxpy_codegen)
    3. Fix some of the known-bugs cvxpy_codegen creates - See issues page of the repo - Attempt to compile, and solve each error as they come
    4. Compile the generated C code
    5. (Optional:) Install the compiled CPython code into your Python distribution with setup.py if you wish to use the compiled code from Python - Be aware that the Python2.7 Windows Compiler provided by Microsoft will not work because it has a pathetically tiny stack heap size. Recommend using MinGW on Windows!

Documentation

  • Since this is a pre-alpha research project, the main documentation is found in #code comments, and in the content of the paper itself.

Requirements

  • Python 2.7 (I'm sorry about still using python 2, Mr. Guido, but cvxpy_codegen is the constraint here...)
  • scipy (for static solutions)
  • cvxpy (for static solutions)
  • cvxpy_codegen (for code generation)

License

GPLv3, copyleft license.

Chose this license because I spent way too many late nights and heartbeats working on this - and want to see what people do with it and have changes propagated forward!

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