A Julia package containing motion planning code related to the following papers on robotic motion planning:
- Fast Marching Tree: a Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions
- Optimal Sampling-Based Motion Planning under Differential Constraints: the Driftless Case
- Optimal Sampling-Based Motion Planning under Differential Constraints: the Drift Case with Linear Affine Dynamics
- Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty
After reading the Dependencies section below, install with
Pkg.clone("https://github.com/schmrlng/MotionPlanning.jl.git")at the julia> prompt (and let me know if it actually works!).
Doesn't exist. At least for now. Check out some basic usage examples and peruse the source, or message me if you have any particular questions about the code.
Until I do some reorganization/implement conditional dependencies, this package comes as one big monolithic block with a bunch of required packages. The starred packages below require additional python-based installation steps outside of Julia (see links).
- PyPlot*
- ArrayViews
- Devectorize
- Iterators
- GZip
- Grid
- Distances
- KDTrees
- ImmutableArrays
- SymPy*
- FastAnonymous
- This code is so alpha that if it was particle, it never would have made it past the paper planning phase.
- This code is so alpha that if it was a gorilla, even King Kong would be intimidated by its immense load time.
- This code is so alfa that if it was a car, Jeremy Clarkson would revel in its shoddy engineering.
- This code is so alfalfa... you get the picture. In all seriousness, lots of things in this package are likely to change in the immediate future as I port in old code, reorganize things, and address some of the 50+ "TODO"s scattered throughout the code.