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GuSTO

Guaranteed Sequential Trajectory Optimization (GuSTO), using sequential convex programming for trajectory optimization with strong theoretical guarantees

Readme

GuSTO.jl: Guaranteed Sequential Trajectory Optimization

This is a Julia suite for trajectory optimization using the Guaranteed Sequential Trajectory Optimization (GuSTO) framework. Details can be found in this paper.

GuSTO.jl runs on julia v1.X, although an older version running on julia v0.6.4 can be found in the julia-v0.6 branch.

Also required are the BulletCollision.jl and AstrobeeRobot.jl packages. GuSTO.jl performs optimization through the JuMP.jl interface, and Gurobi and Ipopt are currently used in examples.

Quickstart

An example notebook can be run through:

jupyter notebook examples/freeflyerSE2.ipynb

Click to watch demo video:

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References

First Commit

09/15/2018

Last Touched

about 1 month ago

Commits

46 commits

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