Color: Train a Real-world Local Path Planner in One Hour

This is the code of the paper Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity. The video of the real world experiments can be found here.

Methodology: Color = Sparrow + ASL

Actor-Sharer-Learner (ASL): An Efficient Training Framework for Off-policy Deep Reinforcement Learning

The trianing curves of ASL on 57 Atari games are listed as follows.

Sparrow: A Reinforcement Learning Friendly Simulator for Mobile Robot

Citing the Project

To cite this repository in publications:

@article{Color2023JinghaoXin,
  title={Train a Real-world Local Path Planner in One Hour via Partially Decoupled Reinforcement Learning and Vectorized Diversity},
  author={Jinghao Xin, Jinwoo Kim, Zhi Li, and Ning Li},
  journal={arXiv preprint arXiv:2305.04180},
  url={https://doi.org/10.48550/arXiv.2305.04180},
  year={2023}
}