Xiaozhen Zhang

Xiaozhen Zhang is currently a Postdoctoral Fellow in the Department of Aeronautical and Aviation Engineering at The Hong Kong Polytechnic University, where he works under the supervision of Prof. Hailong Huang. He earned his Ph.D. degree in 2025 from Beijing Institute of Technology, advised by Prof. Qingkai Yang. During February to August 2025, he was a Visiting Ph.D. Scholar at Nanyang Technological University, Singapore, working with Prof. Lihua Xie. He previously received his M.S. degree in 2021 and B.E. degree in 2018 from Northwestern Polytechnical University, under the supervision of Prof. Panfeng Huang.

His research interests include robotics and autonomous systems, multi-agent systems, swarm intelligence, distributed control and optimization, and learning-enabled autonomy.

Dr Zhang is dedicated to exploring the coordination and autonomy of multi-robot systems, with the ultimate vision of enabling robot swarms to achieve autonomous, intelligent, and human-compatible collective behavior in complex environments. To pursue this vision, I integrate distributed control, optimization, estimation, and learning-enabled AI techniques to bridge the gap between individual intelligence and collective autonomy.

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[7] Cooperative Shape-Translation Estimation and Control for Time-Varying Linear Formation
Xiaozhen Zhang, Qingkai Yang*, Xianlin Zeng, Hao Fang, and Jie Chen
IEEE Transactions on Automatic Control, 2025. (Full Paper)
DOI: 10.1109/TAC.2025.3540570. [PDF]

This work develops a shape-translation estimation and control framework that enables multi-agent systems to track time-varying linear formations.

[6] Linear Formation Control of Multi-Agent Systems
Xiaozhen Zhang, Qingkai Yang*, Fan Xiao, Hao Fang, and Jie Chen
Automatica, 2024. (Regular Paper)
DOI: 10.1016/j.automatica.2024.111935. [PDF]

This work proposes linear formation control to enable multi-agent systems to achieve formations generated by linear transformations. It extends affine formation control to high-dimensional nominal configurations.

[5] Joint Estimation and Planar Affine Formation Control with Displacement Measurements
Qingkai Yang*, Xiaozhen Zhang, Hao Fang, Ming Cao, and Jie Chen
IEEE Transactions on Control Systems Technology, 2024. (Full Paper)
DOI: 10.1109/TCST.2024.3449008. [PDF]

This work proposes a displacement-based distributed estimator for identifying the time-varying affine formation shape matrix.

[4] Distributed Variation Parameter Design for Dynamic Formation Maneuvers With Bearing Constraints
Xiaozhen Zhang, Qingkai Yang*, Jingshuo Lyu, Xinyue Zhao, and Hao Fang
IEEE Transactions on Automation Science and Engineering, 2023.
DOI: 10.1109/TASE.2023.3283095. [PDF]

This work develops a distributed method for adjusting the scale parameters of bearing-constrained dynamic formations, allowing the formation scale to adapt online to environmental changes.

[3] Formation Planning for Tethered Multirotor UAV Cooperative Transportation With Unknown Payload and Cable Length
Xiaozhen Zhang, Fan Zhang*, Panfeng Huang
IEEE Transactions on Automation Science and Engineering, 2023.
DOI: 10.1109/TASE.2023.3279827.  [PDF] [Media]

This work addresses formation planning for tethered multirotor cooperative transportation with uncertain payload and cable length, enabling online adjustment of cable tension distribution for load balancing.

[2] Self-Triggered Based Coordinate Control With Low Communication for Tethered Multi-UAV Collaborative Transportation
Xiaozhen Zhang, Fan Zhang, Panfeng Huang*, Jiale Gao, Hang Yu, Chongxu Pei, Yizhai Zhang
IEEE Robotics and Automation Letters, 2021.
DOI: 10.1109/LRA.2021.3057294. [PDF] [Media]

This work develops a self-triggered cooperative path-following controller for tethered multi-UAV transportation with reduced communication.

[1] Analysis, planning and control for cooperative transportation of tethered multi-rotor UAVs
Ya Liu, Fan Zhang, Panfeng Huang*, and Xiaozhen Zhang
Aerospace Science and Technology, 2021.
DOI: 10.1016/j.ast.2021.106673.

This work develops an integrated analysis, planning, and control framework for tethered multi-rotor cooperative transportation.

[5] How Do Robot Swarms Behave Compliantly?
Xiaozhen Zhang, Zeming Zhao, Qingkai Yang, Hao Fang, and Jie Chen
IEEE 19th International Conference on Control & Automation (ICCA), 2025.
DOI: 10.1109/ICCA65672.2025.11129731.

This work introduces compliance to robot swarms and studies flexible collective responses to external interactions.

[4] A Distributed Algorithm for Solving A Time-Varying Linear Equation
Xiaozhen Zhang, Qingkai Yang, Haijiao Wei, Wei Chen, Zhihong Peng, and Hao Fang
62nd IEEE Conference on Decision and Control (CDC), 2023.
DOI: 10.1109/CDC49753.2023.10383585. [PDF]

This work proposes a distributed algorithm for solving time-varying linear equations over multi-agent networks without centralized information.

[3] Distributed Decision Making on Scaling Size for Obstacle Avoidance in Affine Formation Control
Xiaozhen Zhang, Jingshuo Lv, Shaolei Wei, and Qingkai Yang
37th Youth Academic Annual Conference of Chinese Association of Automation (YAC), 2022.
DOI: 10.1109/YAC57282.2022.10023557.

[2] Design and Analysis of Truss Aerial Transportation System (TATS): The Lightweight Bar Spherical Joint Mechanism
Xiaozhen Zhang, Qingkai Yang, Rui Yu, Delong Wu, Shaozhun Wei, Jingqiang Cui, and Hao Fang
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022.
DOI: 10.1109/IROS47612.2022.9981191. [PDF] [Media]

This work proposes the Truss Aerial Transportation System, a lightweight cooperative transportation architecture based on bar-spherical joint mechanisms.

[1] Distributed Control for Cooperative Transportation in Presence of Unknown Disturbance
Xiaozhen Zhang, Fan Zhang, Panfeng Huang, Chen Wang, and Ya Liu
IEEE International Conference on Real-time Computing and Robotics (RCAR), 2019.
DOI:10.1109/RCAR47638.2019.9044011.