Safety-Bounded Autonomy: Architectural Safety Enforcement for Distributed Robotic Systems
Abstract
This paper introduces the concept of safety-bounded autonomy, an architectural framework for ensuring safe operation in distributed robotic systems. As robotic platforms increasingly operate in complex and shared environments, traditional control architectures that allow autonomy layers to directly influence actuation can lead to unsafe system states, particularly in distributed multi-robot systems or in environments involving human interaction. The proposed framework introduces an architectural separation between autonomous decision-making and physical actuation. Autonomous modules may generate candidate actions, but these actions must pass through dedicated architectural enforcement mechanisms before execution. The architecture includes capability gating, runtime safety monitoring, and explicit safe operational state constraints, ensuring that system transitions remain within a defined safe state space. The paper presents a conceptual reference architecture for safety-bounded autonomy and discusses how architectural safety enforcement can be applied to distributed robotic systems, including robot fleets, industrial robotics, and autonomous inspection platforms. By treating safety as an architectural property of the robotic system, rather than solely a control or algorithmic problem, safety-bounded autonomy provides a foundation for designing robotic systems that remain operationally flexible while maintaining strict safety guarantees. This work is part of a broader research program on governance and execution control in autonomous robotic systems, including capability governance, safety-bounded autonomy, and non-bypassable execution control architectures.
Fields of Study & Subjects
Safety Systems Engineering in Autonomy
Robotics and Automated Systems
AI-based Problem Solving and Planning
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 12 March 2026
- Language
- EN
- Document type
- Preprint