Yuntao Zhang

Yuntao Zhang 张云涛

Ph.D. Candidate in Naval Architecture and Ocean Engineering

Harbin Engineering University

Autonomous Surface Vehicles · Multi-Agent Systems · Formation & Encirclement Control · Reinforcement Learning

About

I am a Ph.D. candidate at Harbin Engineering University. My research focuses on cooperative autonomy for unmanned surface vehicles (USVs), particularly formation control and dynamic target encirclement. I am interested in combining model-based control, multi-agent reinforcement learning, and marine robotics simulation to develop cooperative methods that remain meaningful under realistic vessel dynamics and actuation constraints.

Before my doctoral study, I worked as an R&D engineer at EFORT Intelligent Equipment, where I worked on robotic arm software, ROS, and device drivers. I received my B.S. degree in Automation from Nanjing University.

Research Interests

Cooperative USV Control

Formation acquisition and maintenance for underactuated unmanned surface vehicles.

Dynamic Target Encirclement

Pursuit, encirclement and persistent containment of moving targets by multiple USVs.

Multi-Agent Reinforcement Learning

Learning-based cooperative decision making with emphasis on interpretable and reproducible control architectures.

Marine Robotics Simulation

Algorithm development from lightweight planar environments to ROS 2, VRX and WAM-V validation.

News

Our paper “Speed-heading co-shaping for USV path following” was accepted by the Journal of Harbin Engineering University.

Submitted “Order-preserving formation acquisition for dynamic target encirclement by underactuated USVs.”

Research focus extended toward persistent dynamic-target encirclement and multi-USV cooperative pursuit.

Selected Publications

Google Scholar →
  1. Yuntao Zhang, Shaocheng Di, Jingzheng Yao. “Speed-heading co-shaping for USV path following.” Accepted, Journal of Harbin Engineering University, 2026. In press.

  2. Yuntao Zhang, et al. “Order-preserving formation acquisition for dynamic target encirclement by underactuated USVs.” Manuscript under review, 2026.

  3. Yuntao Zhang, Shaocheng Di, Jingzheng Yao. “Multi-USV Cooperative Control Strategy Based on Model Predictive Control with Deep Reinforcement Learning.” ICCES, 2024.

Selected entries are shown here. The publication page will be expanded from verified bibliographic records.

Research

Dynamic Target Encirclement

Multi-USV · Pursuit–evasion · Persistent containment

Cooperative methods for acquiring and maintaining an encirclement formation around a moving target, with emphasis on underactuated vessel dynamics and persistent task completion.

Code →

Multi-USV Formation Control

MARL · Cooperative control · Formation

Learning-enabled formation control in lightweight, reproducible multi-agent simulation environments, including teacher-guided and residual-learning ideas.

Code →

VRX / WAM-V Validation

ROS 2 · Marine robotics · Sim-to-sim

Engineering validation of cooperative USV algorithms using the VRX simulation ecosystem and WAM-V platform.

Code →

Education & Experience

Harbin Engineering University

Ph.D. Candidate, Naval Architecture and Ocean Engineering

EFORT Intelligent Equipment

R&D Engineer — robotic arm software, ROS and device drivers

Nanjing University

B.S. in Automation

Contact

For research-related correspondence, please contact me at yuntaochn@gmail.com.