Capability Lifecycle Governance in Autonomous Systems

This paper defines capability lifecycle governance as a foundational architectural layer for controlling autonomous systems within the Robotics Governance Architecture (RGA) framework. It introduces a structured model for managing capabilities across their lifecycle, including specification, validation, authorization, activation, monitoring, and revocation. Rather than relying on static configuration or implicit system behavior, capability governance establishes explicit and enforceable definitions of what a system is allowed to do, forming a formal boundary between design-time intent and runtime execution. This layer ensures that all executable actions are derived from explicitly governed capabilities and remain aligned with defined operational, safety, and contextual constraints. Capability lifecycle governance operates independently of execution mechanisms and does not directly enforce behavior. Instead, it defines the admissible capability space within which execution control mechanisms operate. This separation enables a clear architectural distinction between:- capability definition (what is allowed)- execution control (what is executed)- runtime safety enforcement (what is safe) Capability lifecycle governance may be realized through different system-level mechanisms, including software-based control logic, hardware-assisted enforcement, or distributed governance structures. By structuring capability management as a lifecycle-driven governance model, this work provides a scalable and system-agnostic foundation for building controllable, verifiable, and safety-bounded autonomous systems. This paper is part of the Robotics Governance Architecture (RGA) research series, which develops a layered framework for capability governance, non-bypassable execution control, and runtime safety enforcement. Related works A Governance Architecture for Safe and Bounded Autonomous RoboticsNon-Bypassable Execution Control in Autonomous SystemsSafety-Bounded Autonomy in Distributed Robotic Systems