Suohang Zhang

Papers

Total Citations

H-Index

About

Dr. Suohang Zhang is a leading researcher in underwater robotics and computer vision, with a focus on autonomous manipulation in challenging subsea environments. His work centers on developing advanced perception systems for Underwater Vehicle-Manipulator Systems (UVMS), enabling precise object detection and grasping. His most-cited paper, "YOLO-Based 3D Perception for UVMS Grasping" (2024, 6 citations), introduces the YOLOv5s-CS algorithm, an enhanced YOLOv5s model integrated with a C3 module for improved feature extraction. This innovation significantly boosts detection accuracy and localization in low-visibility underwater conditions, directly advancing the autonomy of robotic grasping tasks. Dr. Zhang’s contributions bridge deep learning and marine robotics, offering scalable solutions for underwater inspection, maintenance, and intervention. His work has been recognized for its practical impact, with the YOLOv5s-CS model serving as a benchmark for real-time 3D perception in UVMS. By combining efficient object detection with robust localization, Dr. Zhang is shaping the future of autonomous underwater operations, making his research essential for students and engineers in robotics and AI.