Neural Operators for Design-Space Surrogate Modeling of Tendon-Actuated Continuum Robots

ArXi:2605.19104v1 Announce Type: cross Continuum robots enable dexterous manipulation in constrained environments, but require accurate and efficient models for real-time manipulation and control. Traditional physics-based models can be computationally expensive and may suffer from inaccuracies due to unmodeled effects, while current learning-based methods often generalize poorly beyond the specific robot on which they are trained.