Max Robotics — Global Service Robot Directory + US Certification

About

Yun Niu is a leading researcher in the field of intelligent underwater robotics and autonomous systems, with a primary focus on real-time object detection and classification in complex marine environments. Her most significant contributions center on enhancing the YOLOv3 algorithm for underwater applications, notably through the development of YOLOv3-Marine and YOLOv3-UW. These innovations directly address critical challenges in underwater robotics, including improving detection speed and reducing the missed detection rate of small or densely packed targets—a persistent issue in cluttered underwater scenes. Her work on YOLOv3-Marine (2020), with 15 citations, and YOLOv3-UW (2019), with 9 citations, has provided foundational tools for intelligent underwater robot operations. Beyond detection algorithms, Niu has also advanced robotics education by building a flexible mobile robotics teaching toolkit that integrates MATLAB/Simulink with ROS and Gazebo (2021, 8 citations), bridging the gap between simulation and real-world robotic applications. Her research not only pushes the boundaries of autonomous underwater perception but also equips the next generation of roboticists with practical, accessible learning tools.