This package is used to solve the kinodynamic problem using RRT.
Now it is still in development, to install it for development:
Notice that if you have installed tianshou, please remove it or create another virtual env to install this package. Because we use tianshou for reinforcemenr learning, and change it a bit for our use.
conda create -n crl_kino python=3.6
conda activate crl_kino
git clone https://github.com/sldai/crl_kino.git
cd crl_kino
conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
pip install -e .
Test:
# kinodynamic RRT using dwa as steering function
python example/test.py --case rrt
# kinodynamic RRT using a trained policy as steering function
python example/test.py --case rl_rrt
Gif of kinodynamic rrt results will be saved in the current folder.
Train an agent:
python examples/rl_training.py
RRT tree growing process
The final course
