Max Robotics — Global Service Robot Directory + US Certification

About

Zicun Hong is a rising leader in bio-inspired robotics, specializing in fish locomotion modeling, soft robotics, and intelligent control systems. His most influential work, "A General Kinematic Model of Fish Locomotion Enables Robot Fish to Master Multiple Swimming Motions" (2023, 47 citations), introduced the first unified mathematical framework capable of replicating diverse fish swimming modes—from cruising to fast turns—fundamentally advancing robotic fish versatility. Hong further pioneered the application of deep reinforcement learning for online motion control of underactuated robotic eels (2022, 39 citations), demonstrating how body flexibility and passive designs can dramatically improve swimming efficiency and energy consumption. His innovative work on multi-material embedded 3D printing (2024, 37 citations) enables one-step manufacturing of multifunctional soft robotic components, streamlining fabrication processes. Hong also developed a novel variable-stiffness tail using layer-jamming (2024, 6 citations), mimicking fish ability to adjust body stiffness for optimal performance across speeds. With over 150 total citations, his research bridges theoretical modeling, advanced manufacturing, and adaptive control, offering practical solutions for underwater exploration and robotic design.