# Reactive Planner
This project generates solutions to trajectory planning problems given in the [CommonRoad](https://commonroad.in.tum.de/) scenario format.
The trajectories are generated using the sampling-based approach in [1][2]. This approach plans motions by sampling a
discrete set of trajectories, represented as quintic polynomials in a Frenet frame and selecting an optimal trajectory according
to a given cost function.
<img src="doc/images/ZAM_Tjunction-1_42_T-1.gif" alt="reactive-planner" width="600"/>
## Getting Started
These instructions should help you to install the trajectory planner and use it for development and testing purposes.
To install the package from PyPi, please run:
```shell
pip install commonroad-reactive-planner
```
### Requirements
The software is written in Python 3.8 and tested on Ubuntu 18.04-22.04. The required python dependencies are listed in `pyproject.toml`.
For the python installation, we suggest the usage of [Anaconda](http://www.anaconda.com/download/#download).
For the development IDE we suggest [PyCharm](http://www.jetbrains.com/pycharm/)
### Installation from Source
1. Clone this repository & create a new conda environment, e.g., `conda create -n commonroad-py38 python=3.8`
2. Go to cloned root directory and install the package:
* Install the package via poetry: `poetry install`
* Install the package via pip: `pip install .`
### How to run
**Main example script** `run_planner.py`:
The example script shows how to run the planner on an exemplary CommonRoad scenario with the following steps:
* creating a planner configuration
* instantiating the reactive planner
* running the planner in a cyclic replanning loop with a fixed replanning fequency
In addition we also provide an interactive Jupyter notebook tutorial in the `tutorial/` folder.
## Literature
[1] Werling M., et al. *Optimal trajectory generation for dynamic street scenarios in a frenet frame*. In: IEEE International Conference on Robotics and Automation, Anchorage, Alaska, 987–993.
[2] Werling M., et al. *Optimal trajectories for time-critical street scenarios using discretized terminal manifolds* In:
The International Journal of Robotics Research, 2012
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