This repository contains a fast, C++ implementation of the RRT* algorithm with a Python wrapper. It is used as one of the motion planning models in pylot, an erdos project.
The base RRT code is inspired by sourishg/rrt-simulator, which implements RRT.
Reference Paper: Sampling-based Algorithms for Optimal Motion Planning
Some basic profiling of the code (80 meter x 10 meter search space, 10 obstacles) indicates the following expected performance:
Average Time (success): ~6 ms
Max Time (success): ~60 ms
Failure Case (Running all 2000 iterations): <250 ms
git clone https://github.com/erdos-project/rrt-star-planning.git
./build.sh
There is a Python wrapper and C++ API. The Python wrapper is located in
RRTStar/rrtstar_wrapper.py
and the C++ API is under
src/RRTStar/RRTStarWrapper.cpp
.
The following command will simulate a simple scenario to run the RRT* planning
algorithm.
python3 RRTStar/rrtstar.py