Reflex-Plan: A Safety Monitoring Architecture for Thinking Fast and Slow

Ensuring functional safety is crucial for the deployment of autonomous systems in real-life dynamic environments, as they must operate reliably and safely among humans. However, existing safety systems are designed with a closed-world assumption and can over-constrain the system by shutting down the robot at every safety violation, limiting the robot’s ability to complete its tasks. To address this problem, we present a novel operational safety approach supported by our software architecture Reflex-Plan, where a safety monitor proactively influences high-level planning to enable safe and adaptive recovery behaviors, thus preventing unnecessary stops. Unlike traditional safety monitors that primarily react to violations through predefined stop mechanisms, our software architecture follows a two-step process: the fast-thinking safety monitor provides immediate reflexive responses, while the slow-thinking high-level planner processes the safety monitor’s feedback to plan recovery strategies. This allows the robot to respond quickly to safety-critical situations while maintaining adaptability for long-term autonomy. We validate the effectiveness of Reflex-Plan through real-world robot experiments in a mock hospital environment. Our experimental results confirm that keeping immediate safety responses within the safety monitor ensures fast reactivity. Recovery strategies are delegated to the reasoning layer, which improves adaptation, reduces failures, and supports stable operation without external intervention.