Bailong Liu

Harbin Engineering University, China University of Mining and Technology

Papers

Total Citations

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About

Bailong Liu is a pioneering researcher in autonomous robotics, with key contributions spanning multi-robot coordination, swarm intelligence, and underwater vehicle navigation. His work on "AUV Path Planning under Ocean Current Based on Reinforcement Learning in Electronic Chart" (2013, 20 citations) introduced a novel reinforcement learning framework that enables autonomous underwater vehicles to dynamically adapt their routes in response to ocean currents—a critical advancement for deep-sea exploration and environmental monitoring. In his earlier influential study "Formation Control of Multiple Behavior-based robots" (2006, 20 citations), Liu developed a leader-referenced, behavior-based approach with dynamic-dead-zone methods, allowing robot teams to maintain cohesive formations while navigating complex environments. This work laid foundational principles for flexible, real-time multi-robot coordination. Liu further explored emergent collective behaviors in "A Model of Rescue Task in Swarm Robots System" (2013, 2 citations), where he modeled rescue dynamics using mean-field theory and noise effects, advancing understanding of how swarm systems can perform coordinated emergency tasks. His research uniquely bridges theoretical modeling with practical robotic applications, demonstrating how behavior-based control and reinforcement learning can solve real-world challenges in dynamic, unstructured environments. Liu’s work continues to inspire new generations of roboticists working on autonomous systems, swarm robotics, and adaptive navigation.