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Robotics / Humanoid

Robotics
Safety & Security Compliance

Human-robot collaboration safety at its core. Starting from product safety and extending to AI and intelligent behavior — we cover industrial robots, collaborative robots, and the emerging frontier of humanoid robot safety.

ISO 10218ISO/TS 15066IEC 61508ISO 13849ISO PAS 8800

Product Safety → Collaborative Safety → AI Safety

Robot safety is evolving from traditional industrial fencing to human-robot coexistence, and now to AI-driven autonomous behavior safety. Each step requires its own standards framework.

Step 01 — Baseline

Industrial Robot Safety

ISO 10218 series defines baseline safety requirements for industrial robots. IEC 61508 / ISO 13849 provide the functional safety design framework.

Step 02 — Collaboration

Human-Robot Collaboration

ISO/TS 15066 defines force/pressure limits and safety design methods for collaborative robots — ensuring humans and robots can coexist safely.

Step 03 — AI Safety

Intelligent Behavior Safety

ISO PAS 8800 addresses AI-driven autonomous systems, defining safety verification methods for learning-based behaviors — the frontier of humanoid robot safety.

Core Standards Coverage

From traditional industrial robots to humanoid robots — the safety standards landscape is evolving rapidly

Industrial

ISO 10218-1/2

Safety standard for industrial robots and robot systems. Part 1 covers the robot itself, Part 2 covers system integration — defining safeguarding measures and risk assessment methods.

Collaborative

ISO/TS 15066

Safety specification for collaborative robot systems. Defines four collaboration modes (safety-rated stop, hand guiding, speed separation, power/force limiting) and biomechanical limits.

Functional Safety

IEC 61508 / ISO 13849

General functional safety and machinery safety control standards. Define SIL and PL levels, providing the framework for safety-related control system design and verification.

AI Safety

ISO PAS 8800

Safety standard for AI/ML systems. Defines lifecycle activities for training data, model validation, and operational monitoring — applicable to autonomous decision-making systems.

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