Xuening Song

Shandong University of Science and Technology, Marine Biology Institute of Shandong Province

Papers

Total Citations

H-Index

About

Xuening Song is a robotics researcher whose work centers on bio-inspired underwater vehicles, with a particular focus on the design, modeling, and control of hybrid-driven robotic fish. Her research addresses a fundamental challenge in underwater robotics: balancing maneuverability with energy efficiency. By integrating propeller propulsion with biomimetic fin-based locomotion, Song’s hybrid actuator designs enable robotic fish to achieve both agile turning and sustained, efficient cruising—capabilities that are critical for long-duration underwater exploration and environmental monitoring. Her most-cited paper, "Waypoint-based path following for robotic fish with hybrid actuators" (2025, 3 citations), introduces a control framework that allows these hybrid vehicles to autonomously follow prescribed paths, a key step toward practical deployment. A companion study on design and maneuverability analysis (2025, 1 citation) provides foundational modeling for these systems, detailing how fin and propeller forces can be coordinated. Though early in her career, Song’s work is gaining traction for its practical approach to bridging the gap between biological inspiration and real-world robotic performance, positioning her as an emerging voice in the field of underwater robotics.