README.md

HDPlanner_Exp_and_Nav

Public code and datasets for HDPlanner: Advancing Autonomous Deployments in Unknown Environments through Hierarchical Decision Networks, which has been accepted by IEEE Robotics and Automation Letters (RA-L).

We propose a hierarchical planning approach for robot exploration and navigation in unknown environments, where our decision networks decompose long-term objectives into short-term task assignment (beacon) and informative path planning (waypoint).

Main Dependencies

• python == 3.8.8
• pytorch == 1.8.1
• ray == 1.2.0
• scikit-image == 0.21.0
• scikit-learn == 1.3.0
• scipy == 1.10.1
• matplotlib == 3.6.2
• tensorboard == 2.11.0

Citation

If you find our work helpful or enlightening, feel free to cite our paper:

@ARTICLE{10767278,
  author={Liang, Jingsong and Cao, Yuhong and Ma, Yixiao and Zhao, Hanqi and Sartoretti, Guillaume},
  journal={IEEE Robotics and Automation Letters}, 
  title={HDPlanner: Advancing Autonomous Deployments in Unknown Environments Through Hierarchical Decision Networks}, 
  year={2025},
  volume={10},
  number={1},
  pages={256-263},
  doi={10.1109/LRA.2024.3506281}
}

Authors

Jingsong Liang, Yuhong Cao, Yixiao Ma, Hanqi Zhao, Guillaume Sartoretti