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About

Binrong Wen is a researcher at the forefront of bio-inspired robotics, specializing in the design, modeling, and intelligent control of wire-driven compliant robotic fish. His major contributions lie in bridging soft robotics with advanced control theory, particularly through the development of novel, wire-driven actuation mechanisms that mimic the natural undulatory motion of fish. Wen’s experimental work has systematically characterized the kinematics and hydrodynamics of robotic fishtails, providing foundational insights for efficient underwater propulsion. His most impactful study, "An experimental study of the wire-driven compliant robotic fish" (2023), has garnered 20 citations, establishing a benchmark for compliant underwater robots. Notably, Wen has pioneered the integration of reinforcement learning with Central Pattern Generators (CPGs), achieving high adaptability and robustness in robotic control—a breakthrough demonstrated in his 2023 work on CPG-controlled methods (6 citations). His latest research (2025) further advances this paradigm by enabling real-world training for heading control in complex environments, showcasing a lightweight, learning-based approach. With a growing citation record and a focus on practical, real-world deployment, Wen is shaping the future of autonomous underwater robotics.