A PINN embedding Cosserat rod mechanics achieves sub-1% mean shape error for 6-DoF concentric tube robots using minimal training data and outperforms a pure physics baseline.
On the merits of joint space and orientation representations in learning the forward kinematics in se (3)
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Few-Shot Physics-Informed Neural Network for Shape Reconstruction of Concentric-Tube Robots
A PINN embedding Cosserat rod mechanics achieves sub-1% mean shape error for 6-DoF concentric tube robots using minimal training data and outperforms a pure physics baseline.