AEROS: 具現化能力モジュールを備えた単一エージェント動作アーキテクチャ
AEROS: A Single-Agent Operating Architecture with Embodied Capability Modules
ロボットを単一の持続的な知的エージェントとしてモデル化し、能力をインストール可能なモジュール（ECM）として拡張する新しいアーキテクチャAEROSを提案。ポリシー分離ランタイムにより安全性を保証し、シミュレーションで高い成功率とモジュール交換性を実証した。
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著者: Xue Qin, Simin Luan, John See, Cong Yang, Zhijun Li
分類: cs.RO, cs.AI
原文アブストラクト
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.
関連論文
- 対話型自律ロボットのための階層型アーキテクチャLAAIRアーキテクチャ
