Liyang Xu

National University of Defense Technology

Papers

Total Citations

H-Index

About

Liyang Xu is a pioneering researcher at the intersection of underwater robotics and artificial intelligence, with a primary focus on bio-inspired robotic fish systems and swarm intelligence. His most impactful work, "Numerical Simulation and Analysis of Fish-Like Robots Swarm" (28 citations), addresses a critical gap in underwater robotics by moving beyond single-robot studies to investigate collective behavior in hydro-environments—a foundational contribution to understanding how robotic fish formations can achieve superior propulsion efficiency and maneuverability compared to traditional AUVs. Xu further advanced the field with "An Environmental Perception Framework for Robotic Fish Formation Based on Machine Learning Methods" (11 citations), where he developed novel perception systems that enable robotic fish to coordinate in formation while navigating complex aquatic environments. His work on "Optimizing High-dimensional Learner with Low-Dimension Action Features" (4 citations) tackles the fundamental challenge of balancing model-free and model-based reinforcement learning, proposing efficient frameworks for high-dimensional robotic tasks. Xu’s research is particularly notable for bridging theoretical machine learning with practical underwater applications, offering scalable solutions for environmental monitoring, search-and-rescue, and marine exploration. His contributions are shaping the next generation of autonomous underwater vehicles capable of intelligent, energy-efficient collective behavior.