Using Physics-Informed Neural Networks for Shape Estimation of Concentric Tube Robots
Accurately modeling the mechanics of concentric tube robots (CTRs) remains challenging due to nonlinear curvature coupling, torsional interactions, and sensitivity to material and geometric parameters. Physics-informed neural networks (PINNs) offer a flexible alternative by embedding governing equations directly into t...