A Novel Risk Assessment Framework for Ensuring the Safety of Humanoid Robots

Humanoid robots mimic human forms and utilize advanced artificial intelligence (AI), creating complex safety challenges that traditional frameworks struggle to address. This paper proposes an integrated risk assessment framework tailored for humanoid robots, combining Failure Modes and Effects Analysis, System-Theoretic Process Analysis, and an AI-specific Risk Index. Additionally, it systematically identifies and evaluates risks from mechanical and electrical failures, control system errors, and AI-driven behaviors such as biased data handling and unpredictable real-time decision-making. Applying this framework to 30 risk scenarios revealed critical vulnerabilities, including power system malfunctions, software logic errors, and autonomous decision anomalies. Based on these findings, specific safety measures were developed, emphasizing redundant hardware controls, multi-sensor validation, real-time software monitoring, and robust fail-safe mechanisms. The integrated approach significantly enhances traditional risk assessments, effectively bridging the gap between existing robotics safety standards and new AI-driven challenges, ensuring the safe and reliable operation of humanoid robots in dynamic human environments.