Safety-Bounded Autonomy: Architectural Safety Enforcement for Distributed Robotic Systems

Autonomous robotic systems increasingly operate in dynamic and partially unpredictable environments such as logistics facilities, manufacturing sites, and public spaces. As autonomy levels increase, ensuring safe and bounded system behavior becomes a central challenge. This paper introduces the concept of safety-bounded autonomy, an architectural approach that constrains robotic decision-making and execution through explicit runtime safety enforcement mechanisms. Instead of relying solely on design-time verification, the proposed architecture introduces governance layers that monitor, authorize, and constrain robot capabilities during system operation. The framework integrates capability authorization, safety constraint verification, and runtime monitoring into the control architecture of autonomous robotic systems. By embedding safety enforcement directly within the system architecture, autonomous behavior can be dynamically restricted to predefined safety boundaries while still enabling adaptive operation. The paper further discusses how safety-bounded autonomy can scale to distributed robot fleets by introducing coordinated governance mechanisms across multiple autonomous agents. The approach contributes to emerging research on trustworthy AI, cyber-physical systems safety, and architectural governance for autonomous robotic platforms.