Python RRT*

A Python implementation of the RRT*, an optimal version of the Rapidly Exploring Random Tree algorithm. This implementation is based on the following paper:

Karaman, S., & Frazzoli, E. (2010). Optimal kinodynamic motion planning using incremental sampling-based methods. Proceedings of the IEEE Conference on Decision and Control, 7681–7687. https://doi.org/10.1109/CDC.2010.5717430

RRT* is a motion planning algorithm that allows to find an optimal path from an initial state to a goal region in the state space.

This project allows to study the effect of the different parameters on the obtained path as well as changing easily some part of the algorithm such as the steering function.

Installation and how-to-use

Clone the repository

git clone git@github.com:rdesarz/rrtstar.git

Install the project using pip. You can use the -e option to edit the parameters of the algorithm

python3 -m pip install -e rrtstar

Parameters can be changed in the commande_line.py file

To run the planner, type the following command

rrtstar

You should see a window similar to the following one:

Further work

• Improve performance by implementing specific algorithm to find near nodes (e.g. KD-tree)
• Use kinodynamic model

Authors

• Romain Desarzens - Initial work - rdesarz

License

This project is licensed under the MIT License - see the LICENSE.md file for details