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crl_kino's Introduction

This package is used to solve the kinodynamic problem using RRT.

Installation

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 .

Use

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 

Results

RRT tree growing process path

The final course path

crl_kino's People

Contributors

hierich avatar sldai avatar tyzhao0121 avatar

Stargazers

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Watchers

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crl_kino's Issues

help =-=

Hello author, when I use the test.py file of this package, it prompts me
File "examples/test.py", line 1, in
from crl_kino.policy.rl_policy import load_policy, policy_forward
ModuleNotFoundError: No module named 'crl_kino',
what's the reason? orz

Visualization problems

Hello, I meet a problem. I can not display the algorithm as yours. How can I visualize it? Do I need to install something else? Looking forward to your reply! Thank you!

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