Infinite-Dimensional Closed-Loop Inverse Kinematics for Soft Robots via Neural Operators

arXiv:2602.18655 · cs.RO, cs.SY, eess.SY · Submitted 2026-02-20 · Read on arXiv

cs.RO, cs.SY, eess.SY

Submitted: 2026-02-20

Updated: 2026-10-09

Terminology

• DeepONet — 5× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Active Learning — 1× in this paper · explained in 6 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Closed-Loop Control — 1× in this paper · explained in 3 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Surrogate Model — 1× in this paper · explained in 2 episodes

Sources

• Real-Time Character Inverse Kinematics using the Gauss-Seidel Iterative Approximation Method
• Globally Optimal Inverse Kinematics as a Quadratic Program
• Deep Operator Neural Network Model Predictive Control
• Shape-Space Graphs: Fast and Collision-Free Path Planning for Soft Robots

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