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KR Series Ch.21 Explores AI Safety Foundations for Autonomous and Embodied Robots

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A chapter from the STATERA Library's Volume 06 on AMR AI and Embodied Intelligence examines safety for AI-driven robotics. It argues that as robots shift from rule-based control to learning systems such as deep networks, foundation models, and reinforcement learning agents, safety becomes a central engineering challenge. The text frames AI safety as a system-level concern tied to human protection, operational stability, regulatory compliance, and public trust. It also distinguishes capability from reliability and outlines hazards, risk, uncertainty, and robustness across the perception, decision, and action pipeline. The excerpt is part of a Korean-language series hosted on GitHub.

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