提出可插拔的机器人能力模块架构，实现安全可控的智能体统一管理。
AEROS: A Single-Agent Operating Architecture with Embodied Capability Modules
- 将机器人建模为单一持久智能体，通过可安装的能力模块扩展功能。
- 在8项实验中任务成功率100%，政策层零误放行，模块热替换成功率100%。
- 适合需要模块化、安全可扩展的机器人系统研发人员参考。
当前机器人系统缺乏对智能、能力与执行的统一抽象。现有方法或采用耦合式单体架构，或分解为松散协作的模块或多智能体，常缺乏一致的身份与控制权模型。本文提出将机器人视为一个持续存在的智能主体，其能力通过可安装的实体能力模块（ECMs）扩展。每个ECM封装可执行技能、模型与工具，运行时通过策略分离机制强制执行约束与安全保证。该分离设计支持模块化扩展、能力组合执行及系统级安全一致性。我们在PyBullet仿真中以Franka Panda 7-DOF机械臂为平台，开展八项实验：重规划、故障恢复、策略执行、基线对比、跨任务泛化、ECM热替换、消融实验与失效边界分析。每组条件进行超过100次随机测试，AEROS在三个任务上实现100%成功率，优于基线（BehaviorTree.CPP风格和ProgPrompt风格为92–93%，扁平流水线为67–73%），策略层对所有非法动作零误接受，运行时优势无需任务特调即可跨任务泛化，且模块可在运行时加载，热替换后成功率达100%。
原文摘要 · Abstract (English)
Robotic systems lack a principled abstraction for organizing intelligence, capabilities, and execution in a unified manner. Existing approaches either couple skills within monolithic architectures or decompose functionality into loosely coordinated modules or multiple agents, often without a coherent model of identity and control authority. We argue that a robot should be modeled as a single persistent intelligent subject whose capabilities are extended through installable packages. We formalize this view as AEROS (Agent Execution Runtime Operating System), in which each robot corresponds to one persistent agent and capabilities are provided through Embodied Capability Modules (ECMs). Each ECM encapsulates executable skills, models, and tools, while execution constraints and safety guarantees are enforced by a policy-separated runtime. This separation enables modular extensibility, composable capability execution, and consistent system-level safety. We evaluate a reference implementation in PyBullet simulation with a Franka Panda 7-DOF manipulator across eight experiments covering re-planning, failure recovery, policy enforcement, baseline comparison, cross-task generality, ECM hot-swapping, ablation, and failure boundary analysis. Over 100 randomized trials per condition, AEROS achieves 100% task success across three tasks versus baselines (BehaviorTree.CPP-style and ProgPrompt-style at 92--93%, flat pipeline at 67--73%), the policy layer blocks all invalid actions with zero false acceptances, runtime benefits generalize across tasks without task-specific tuning, and ECMs load at runtime with 100% post-swap success.
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