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.
Physics-informed neural networks to model and control robots: A theoretical and experimental investigation
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QuietWalk combines an inverse-dynamics-constrained PINN for GRF estimation with RL to produce low-impact humanoid locomotion policies that generalize across footwear, cutting mean noise by 7.17 dB on hardware.
citing papers explorer
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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.
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QuietWalk: Physics-Informed Reinforcement Learning for Ground Reaction Force-Aware Humanoid Locomotion Under Diverse Footwear
QuietWalk combines an inverse-dynamics-constrained PINN for GRF estimation with RL to produce low-impact humanoid locomotion policies that generalize across footwear, cutting mean noise by 7.17 dB on hardware.