EUDM Planner
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Update (Sept. 2020): The whole dependencies and a playable demo will be released in: https://github.com/HKUST-Aerial-Robotics/EPSILON
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Notice: The current version is for reference only.
Introduction
This is the project page of the paper "Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching" which is accepted by IEEE International Conference on Robotics and Automation (ICRA) 2020.
Our paper is currently available on arXiv.
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Lu Zhang, Wenchao Ding, Jing Chen and Shaojie Shen. Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching. arXiv preprint arXiv:2003.02746.
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L. Zhang and W. Ding contributed equally to this project.
@article{zhang2020efficient,
title={Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching},
author={Zhang, Lu and Ding, Wenchao and Chen, Jing and Shen, Shaojie},
journal={arXiv preprint arXiv:2003.02746},
year={2019}
}
Videos:
The overall structure is shown as follows:
