RoboSafe: A Quantitative Character Safety Certification Framework for Social Robot Deployments in Public-Facing Environments

We present the RoboSafe Standard v1.0, a normative certification framework for the charac-

ter safety layer of physical AI systems — robots and AI-driven hardware that interact with hu-

man beings in physical spaces. As large language models are increasingly deployed on embodied

platforms (wheeled robots, bipedal humanoids, screen-face kiosks, digital human installations),

the absence of a shared, citable safety standard creates procurement ambiguity, compliance risk,

and accountability gaps.

RoboSafe defines three certification levels keyed to deployment environment risk: Level 1

(retail and corporate), Level 2 (hospitality, public space, and elder care), and Level 3 (clinical

and pediatric). Each level specifies measurable key performance indicator (KPI) thresholds

— including hard block accuracy, gray zone false positive rate, response substitution latency,

alignment agent approval rate, drift score, and PHI redaction coverage — along with normative

configuration requirements. A four-stage certification process (Configure, Simulate, Validate

KPIs, Maintain) provides a repeatable path to certification and continued compliance monitor-

ing.

The framework is designed to be technology-agnostic at the detection layer while mandat-

ing deterministic, auditable governance infrastructure above it. CharacterOS is the reference

implementation. This document is the authoritative specification and is citable in procurement

documents, RFP responses, enterprise contracts, and regulatory filings.