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Neural-ESO achieves unprecedented operational reliability in learning-based control by balancing predictive neural networks with traditional error correction methods.
Achieving millimeter-level tracking accuracy and real-time safety guarantees in robotic manipulation, even under dynamic uncertainties, could redefine standards for safe human-robot interaction.