Skip to content

jonnyhyman/G-FOLD-Python

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

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!

About

Rocket Landing "Guidance for Fuel Optimal Diverts" in Python

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages