Han Ruihua

I am a fourth year Ph.D. candidate in the Department of Computer Science at The University of Hong Kong (HKU), co-advised by Prof. Jia Pan and Prof. Qi Hao.
I am deeply passionate about developing the generally intelligent and theoretically guaranteed robotics systems capable of performing complex tasks comparable to human capabilities.
My current research focuses on the optimal control and motion planning for ground mobile robots navigating cluttered and inhabited environments. I am particularly interested in integrating learning techniques with optimization theory and applying them to real robots to enhance the adaptability and efficiency of intelligent autonomous systems.
The open-source code for my research work can be found on my GitHub, which has garnered 500+ stars from the community. Notable repositories include rl_rvo_nav (130+ stars), RDA_planner (130+ stars), ir_sim (70+ stars), and rvo_ros (30+ stars)
I am also interested in and researching the whole-body robot locomotion.

I am currently seeking postdoctoral opportunities in the field of robotics.

selected publications

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning

Ruihua Han , Shuai Wang , Shuaijun Wang , and 8 more authors

arXiv preprint arXiv:2403.06828, 2024

Bib PDF video

@article{han2024neupan,
  title = {NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning},
  author = {Han, Ruihua and Wang, Shuai and Wang, Shuaijun and Zhang, Zeqing and Chen, Jianjun and Lin, Shijie and Li, Chengyang and Xu, Chengzhong and Eldar, Yonina C and Hao, Qi and others},
  journal = {arXiv preprint arXiv:2403.06828},
  year = {2024},
}

Rda: An accelerated collision free motion planner for autonomous navigation in cluttered environments

Ruihua Han , Shuai Wang , Shuaijun Wang , and 5 more authors

IEEE Robotics and Automation Letters (RA-L), 2023

Bib PDF video Code

@article{han2023rda,
  title = {Rda: An accelerated collision free motion planner for autonomous navigation in cluttered environments},
  author = {Han, Ruihua and Wang, Shuai and Wang, Shuaijun and Zhang, Zeqing and Zhang, Qianru and Eldar, Yonina C and Hao, Qi and Pan, Jia},
  journal = {IEEE Robotics and Automation Letters (RA-L)},
  volume = {8},
  number = {3},
  pages = {1715--1722},
  year = {2023},
  publisher = {IEEE},
}

Reinforcement learned distributed multi-robot navigation with reciprocal velocity obstacle shaped rewards

Ruihua Han , Shengduo Chen , Shuaijun Wang , and 4 more authors

IEEE Robotics and Automation Letters, 2022

Bib PDF video Code

@article{han2022reinforcement,
  title = {Reinforcement learned distributed multi-robot navigation with reciprocal velocity obstacle shaped rewards},
  author = {Han, Ruihua and Chen, Shengduo and Wang, Shuaijun and Zhang, Zeqing and Gao, Rui and Hao, Qi and Pan, Jia},
  journal = {IEEE Robotics and Automation Letters},
  volume = {7},
  number = {3},
  pages = {5896--5903},
  year = {2022},
  publisher = {IEEE},
}

Cooperative multi-robot navigation in dynamic environment with deep reinforcement learning

Ruihua Han , Shengduo Chen , and Qi Hao

In 2020 IEEE International Conference on Robotics and Automation (ICRA) , 2020

Bib PDF video

@inproceedings{han2020cooperative,
  title = {Cooperative multi-robot navigation in dynamic environment with deep reinforcement learning},
  author = {Han, Ruihua and Chen, Shengduo and Hao, Qi},
  booktitle = {2020 IEEE International Conference on Robotics and Automation (ICRA)},
  pages = {448--454},
  year = {2020},
  organization = {IEEE},
}