Papers
10
Total Citations
94
H-Index
7
About
Mingxi Zhou is a robotics and marine autonomy researcher whose work spans autonomous underwater vehicles (AUVs), underwater navigation, and intelligent control systems. His research addresses some of the most pressing challenges in ocean exploration, including bathymetric mapping, underwater state estimation, and adaptive path planning for marine robots. Zhou has made notable contributions to coverage path planning for AUV-based seabed surveys, developing data-driven and uncertainty-driven online methods that improve the efficiency and adaptability of seafloor mapping missions. His work on underwater acoustic-based navigation and tightly-coupled visual-DVL-inertial odometry advances reliable localization for robots operating in GPS-denied environments, including the challenging under-ice domain. The development of the ALPHA hybrid AUV and the open-source ROS-MVP framework reflects his commitment to accessible, practical tools for the broader marine robotics community. Beyond ocean systems, Zhou has extended his expertise to soft robotics and multi-agent systems, contributing learning-based control strategies for soft trunk robots and distributed adaptive control for robotic manipulator networks. With a growing body of work accumulating citations across multiple disciplines, Zhou represents an emerging voice bridging theoretical control with real-world autonomous marine systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Learning-Based Tracking Control of Soft Robots14 citations · 2023
- 4
- 5
- 6
- 7
- 8
- 9
- 10