Papers
7
Total Citations
75
H-Index
5
About
Xiaocun Liao is a robotics researcher specializing in bio-inspired underwater locomotion, with a particular focus on the design, modeling, and control of robotic fish systems. Their work centers on bridging the gap between the extraordinary swimming capabilities of natural fish and the mechanical limitations of traditional multi-joint robotic platforms. Liao's most significant contributions involve wire-driven elastic robotic fish architectures that replace complex discrete joint systems with compliant, continuum-inspired mechanisms. Their 2022 paper on dynamic modeling and performance analysis of wire-driven elastic robotic fish has garnered 26 citations, establishing a foundational framework for this design paradigm. Complementary work on CPG-based control, dual elastic fishtails with energy-storing properties, and fast online stiffness adjustment mechanisms collectively demonstrate a systematic research program aimed at replicating the nuanced biomechanics of fish locomotion. Beyond mechanical design, Liao has contributed to optimization strategies using improved NSGA-II algorithms to balance competing objectives such as swimming speed and energy efficiency, as well as adaptive sensor fusion techniques for robotic fish localization. With over 75 cumulative citations across seven publications, their research represents a cohesive and growing body of work advancing the practical performance of bio-inspired underwater robots.
Research Focus
Key Achievements
Top Papers
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- 2A Wire-driven Elastic Robotic Fish and its Design and CPG-Based Control14 citations · 2022
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