发表机构
Machine Perception and Intelligent Robotics Group (MAPIR-UMA), Malaga Institute for Mechatronics Engineering and Cyber-Physical Systems (IMECH.UMA), University of Malaga（机器感知与智能机器人组（MAPIR-UMA），马拉加机电一体化工程与网络物理系统研究所（IMECH.UMA），马拉加大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究针对GenAI推动下机器人架构中HRI层碎片化问题，提出采用代理-客户端协议（ACP），结合MCP构建三层解耦架构，消除架构依赖，支持异构界面，提供协作HRI能力，经实验验证了架构的互操作性和实时人在回路工作流程。
AI 中文摘要
生成式人工智能（GenAI）的进展，特别是大语言模型（LLMs），促使机器人架构向基于代理的高级编排发展，自然语言指令可转化为情境感知动作序列。虽然通过模型上下文协议（MCP），代理与机器人能力整合趋于标准化，但人机交互（HRI）上层仍因专有、临时接口而碎片化，阻碍实时人在回路协作。本文提出采用代理-客户端协议（ACP）作为基于代理的机器人系统中HRI层的统一通信契约。通过在接口-代理链路结合ACP，在代理-执行链路结合MCP，构建了完全解耦的三层架构，分离了人际交互、审议编排和物理执行。该拓扑消除了严格的架构依赖，支持异构用户界面连接同一机器人系统，允许更换底层机器人平台而无需特定客户端集成更改，还提供了对实时可观测性、明确人类授权和立即任务中断等协作HRI能力的原生支持。通过在物理移动机器人上实验评估该架构，展示了跨三个异构用户界面的互操作性，并验证了具有可忽略延迟开销的实时人在回路工作流程。
英文摘要
Recent advances in Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs), are driving robotic architectures toward agent-based high-level orchestration, in which natural-language instructions can be translated into context-aware action sequences. While the integration of these agents and robotic capabilities is increasingly converging toward standardization through the Model Context Protocol (MCP), the upper Human-Robot Interaction (HRI) layer remains fragmented by proprietary, ad hoc interfaces that hinder real-time human-in-the-loop collaboration. To address this fragmentation, this paper proposes the adoption of the Agent-Client Protocol (ACP) -- a communication standard originally introduced for coding agents in software engineering -- as a unified communication contract for the HRI layer in agent-based robotic systems. By combining ACP at the interface-agent link and MCP at the agent-execution link, we formulate a fully decoupled three-layer architecture that separates human interaction, deliberative orchestration, and physical execution. This topology removes rigid architectural dependencies, enabling heterogeneous user interfaces to connect to the same robotic system and allowing the underlying robotic platform to be replaced without requiring client-specific integration changes. Moreover, it provides native support for collaborative HRI capabilities such as real-time observability, explicit human authorization, and immediate task interruption. We experimentally evaluate the proposed architecture on a physical mobile robot, demonstrating interoperability across three heterogeneous user interfaces and validating real-time human-in-the-loop workflows with negligible latency overhead.
Comments8 pages, 5 figures, 1 table. Submitted to IEEE Robotics and Automation Letters (RA-L)
