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. Video can be found here.

Methodology: Color = Sparrow + ASL

1. Sparrow: A Reinforcement Learning Friendly Simulator for Mobile Robot

2. 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.

Citing the Project

To cite this repository in publications:

@article{Color2025XJH,
title = {Train a real-world local path planner in one hour via partially decoupled reinforcement learning and vectorized diversity},
journal = {Engineering Applications of Artificial Intelligence},
volume = {141},
pages = {109726},
year = {2025},
issn = {0952-1976},
doi = {https://doi.org/10.1016/j.engappai.2024.109726},
}