ARTICLEDEV.to AI·4/19/2026
Meta-Optimized Continual Adaptation for bio-inspired soft robotics maintenance with zero-trust governance guarantees
The author encountered significant degradation in a bio-inspired soft robotic gripper, revealing the inadequacy of standard reinforcement learning for time-evolving simulation-to-reality gaps. This led to a focus on meta-optimized continual adaptation for maintenance, integrating zero-trust governance.
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