Zhenhan Liang

Iterative Learning Motion Control of Continuum Robots Based on Neural Ordinary Differential Equations

Traditional data-driven control methods often require large amounts of training data, posing significant challenges for continuum robots. Recently, neural ordinary differential equation (NODE) methods have demonstrated impressive capabilities for data-efficient modeling of continuum robots. However,