Selected Publications
ProxFly: Robust Control for Close Proximity Quadcopter Flight via Residual Reinforcement Learning
Ruiqi Zhang, Dingqi Zhang, Mark W. Mueller
IEEE International Conference on Robotics and Automation (ICRA), 2025
[ArXiv] [Video] [Website]
"A residual RL-based controller for hovering, tracking and midair quadcopter docking in close proximity!"
Ruiqi Zhang, Dingqi Zhang, Mark W. Mueller
IEEE International Conference on Robotics and Automation (ICRA), 2025
[ArXiv] [Video] [Website]
"A residual RL-based controller for hovering, tracking and midair quadcopter docking in close proximity!"
Spreeze: High-Throughput Parallel Reinforcement Learning Framework
Jing Hou, Guang Chen*, Ruiqi Zhang, Zhijun Li, Shangding Gu, Changjun Jiang
IEEE Transactions on Parallel and Distributed Systems, 2024
[Paper]
"A highly parallelized RL frameworks Spreeze with automatic hyperparameter adjustment."
Jing Hou, Guang Chen*, Ruiqi Zhang, Zhijun Li, Shangding Gu, Changjun Jiang
IEEE Transactions on Parallel and Distributed Systems, 2024
[Paper]
"A highly parallelized RL frameworks Spreeze with automatic hyperparameter adjustment."
Residual Policy Learning Facilitates Efficient Model-Free Autonomous Racing
Ruiqi Zhang, Jing Hou, Guang Chen*, Zhijun Li, Jianxiao Chen, Alois Knoll
IEEE Robotics and Automation Letters, 2022
[Paper] [Video] [Code]
"A human-level RL-based controller for generalizable high-speed mapless Autonomous Racing."
Ruiqi Zhang, Jing Hou, Guang Chen*, Zhijun Li, Jianxiao Chen, Alois Knoll
IEEE Robotics and Automation Letters, 2022
[Paper] [Video] [Code]
"A human-level RL-based controller for generalizable high-speed mapless Autonomous Racing."
Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
Ruiqi Zhang, Jing Hou, Florian Walter, et al. [ArXiv] [Website]
"A comprehesive survey for the benchmark, methodologies, challenges and future of MARL for autonomous driving."
Ruiqi Zhang, Jing Hou, Florian Walter, et al. [ArXiv] [Website]
"A comprehesive survey for the benchmark, methodologies, challenges and future of MARL for autonomous driving."
Scalable Differentiable Reward Learning for Real-World Safe Autonomous Driving
Jing Hou, Jiayi Guan, Ruiqi Zhang, et al.
Nature Computational Science (Under Review)
[Pre-Print] [Code]
"We propose a differentiable reward method to learn a safe, scalable policy for EV autonomous driving in the real world."
Jing Hou, Jiayi Guan, Ruiqi Zhang, et al.
Nature Computational Science (Under Review)
[Pre-Print] [Code]
"We propose a differentiable reward method to learn a safe, scalable policy for EV autonomous driving in the real world."
Awards
- Shanghai Outstanding Student, 2023 (Ranking 1st)
- Weichai Enterprise Scholarship, 2022
- Silver Prize of Formula Student China, 2021
- Tongji Outstanding Scholarship for Undergraduates, 2019, 2020
Service
Academic Reviewer (partial)
- IEEE Transactions on Robotics (T-RO)
- International Journal of Robotics Research (IJRR)
- IEEE Transaction on Automation Science and Engineering (T-ASE)
- IEEE Robotics and Automation Letters (RA-L)
- IEEE International Conference on Robotics and Automation (ICRA)
- IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Conference on Robot Learning (CoRL)
- Robotics: Science and Systems (RSS)
Affiliations
Mentors
Prof. Mark Mueller
UC Berkeley
Prof. Guang CHEN
Tongji University
Prof. Alois Knoll
TU München
Prof. Lin SHAO
NUS
Dr. Xiao MA
Tiktok
Dr. Jing HOU
Shanghai AI Lab
Miscellanea
In my spare time, I like watching MLB and NBA games, Formula 1 and Japanese animation.
Specifically, I'm a big fan of YOASOBI (a J-POP band) and Shohei Ohtani. Let's Go Dodgers!
Also I'm a player of wide-range Games like Genshin Impact and PalWorld.
Welcome to contact me for any reason!
Contact
- richzhang@berkeley.edu
- 2505 Hearst Ave., Etcheverry Hall, University of California, Berkeley, CA 94709, USA