https://github.com/erdos-project/rrt_star_planner
https://github.com/erdos-project/rrt_star_planner
Last synced: 7 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/erdos-project/rrt_star_planner
- Owner: erdos-project
- License: apache-2.0
- Created: 2020-03-07T00:33:00.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2022-06-22T19:54:41.000Z (about 3 years ago)
- Last Synced: 2024-04-22T10:14:04.374Z (about 1 year ago)
- Language: C++
- Size: 695 KB
- Stars: 5
- Watchers: 3
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# RRT*
## Overview
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](https://github.com/erdos-project/pylot), an [erdos](https://github.com/erdos-project) project.
The base RRT code is inspired by [sourishg/rrt-simulator](https://github.com/sourishg/rrt-simulator), which implements RRT.
Reference Paper:
[Sampling-based Algorithms for Optimal Motion Planning](https://arxiv.org/pdf/1105.1186.pdf)
## Profiling
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
```
## Setup
```
git clone https://github.com/erdos-project/rrt-star-planning.git
./build.sh
```
## Example Usage
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
```