This repository is related to the 2022 CoG Robomaster Sim2Real Challenge which is organized by CASIA DRL Team. In this repository, we will provide the implementation of our algorithm.
This code is developed with python 3.7 and the networks are trained using PyTorch 1.10.2.
We recommend using conda to create a virtual environment.
Step 1.In this repository, two environments (Windows/Linux) have been provided. You can get the environment file in your project.
Step 2. Create virtual environment using conda.(you must have installed anaconda/miniconda first.)
conda env create -f environment_*.yml.
Step 3. Install the COG_API package with command:
pip install CogEnvDecoder --upgradeStep 4. Run the api_test.py, you will see our simulation environment.
The experiment can be run by calling the following code, where you may change the path to the environment file:
python submit_test.pyTo train a new model by calling
python train.pyIn our repository, we provide demo vedio and experiment report where you can download for reference. All rights reserved.
This project was completed by ==Chao Li, Xiaodong Liu and Ming Sang in the University of Chinese Academy of Sciences (UCAS)==. Special thanks to my teammates for their support and help, still miss that summer when we worked together to complete this big challenge!
Miss you guys! 🍻 ——xiaodong