Zixuan Zhuang

I am currently a visiting student at the Human-Centered Robotics Lab, Department of Electrical and Computer Engineering, National University of Singapore, under the supervision of Prof. Fan Shi. I am pursuing my Master's degree at Sun Yat-sen University, advised by Prof. Hui Cheng. Previously, I was a visiting student in the STAR Group at Sun Yat-sen University, working with Prof. Boyu Zhou. I received my Bachelor's degree in Electrical Engineering and Automation from Northeastern University in 2023. I am actively seeking Ph.D. opportunities starting in Fall 2026.

Email / Google Scholar / Github

Robots I've Worked On

RoboMaster Robot	Unitree Go2
Mobile Manipulator	Quadrotor

Honors

2025 - ICRA 2025 Travel Grant
2022 - IEEE ICRA RoboMaster University AI Challenge - First Prize / Third Place
2023 - Outstanding Graduate Student Award

Research

My research interests focus on locomotion and loco-manipulation for embodied robots. I have hands-on experience with both rule-based approaches and learning-based methods, and my work aims to bridge model-driven control and data-driven learning to enable robust and agile robot behaviors in complex and unknown environments. Below are some representative projects and research works I have conducted in these areas.

	SAC-Loco: Safe and Adjustable Compliant Quadrupedal Locomotion Aoqian Zhang^, Zixuan Zhuang^, Chunzheng Wang, Shuzhi Sam Ge, Fan Shi, Cheng Xiang^† Under Review, 2026 PDF / An end-to-end joint-level locomotion policy with adjustable compliance, enabling adaptive motion under external forces while ensuring velocity tracking and robustness against large disturbances.
	Motion Planning for Mobile Manipulators in Unknown Environments Zixuan Zhuang Master Thesis, 2026 A Real-Time Trajectory Planning Method for Mobile Manipulators with Hard Constraints.
	RM-Planner: Integrating Reinforcement Learning with Whole-Body Model Predictive Control for Mobile Manipulation Zixuan Zhuang^, Le Zheng^, Wanyue Li, Renming Liu, Peng Lu, Hui Cheng^† IEEE International Conference on Robotics & Automation (ICRA), 2025 video / PDF / We propose a mobile manipulation framework that integrates reinforcement learning with whole-body model predictive control for operation in unknown and complex environments.
	Star-Searcher: A Complete and Efficient Aerial System for Autonomous Target Search in Complex Unknown Environments Yiming Luo, Zixuan Zhuang, Neng Pan, Chen Feng, Shaojie Shen, Fei Gao, Hui Cheng, Boyu Zhou^† IEEE Robotics and Automation Letters (RA-L), 2024 video / PDF / We propose Star-Searcher, a hierarchical UAV-based target search system that combines viewpoint clustering and history-aware planning to achieve efficient and complete search in complex unknown environments.

Feel free to steal this website's source code. Do not scrape the HTML from this page itself, as it includes analytics tags that you do not want on your own website — use the github code instead. Also, consider using Leonid Keselman's Jekyll fork of this page.