arXiv:2607.14919cs.RO2026-07

用统一协议让人类与机器人实时协作,打破接口碎片化困局。

Human-Robot Interaction in GenAI Architectures via the Agent-Client Protocol

论文配图:Human-Robot Interaction in GenAI Architectures via the Agent-Client Protocol
图 1 · 摘自论文原文
  • 提出ACP协议统一人机交互层,实现三层次解耦架构。
  • 实测支持三种异构界面,延迟极低,可实时中断任务。
  • 适合开发可插拔、支持协同的智能机器人系统。

生成式人工智能(GenAI)尤其是大语言模型(LLMs)正推动机器人架构向基于智能体的高层编排演进,使自然语言指令可转化为上下文感知的动作序列。尽管智能体与机器人能力的集成正通过模型上下文协议(MCP)趋于标准化,但上层的人机交互(HRI)仍被各厂商私有的、临时的接口割裂,阻碍了实时人机协同。为此,本文提出采用最初用于软件工程中代码智能体的代理-客户端协议(ACP)作为基于智能体机器人系统的统一人机交互通信标准。通过在接口-智能体链路使用ACP、在智能体-执行链路使用MCP,构建完全解耦的三层架构:分离人类交互、决策编排与物理执行。该结构消除了刚性依赖,允许多样化用户界面连接同一机器人系统,且更换底层平台无需客户端适配。同时原生支持实时可观测性、显式人类授权和即时任务中断。实验在实体移动机器人上验证,实现了三种异构界面的互操作性,并证实了低延迟下的人机协同工作流。

原文摘要 · Abstract (English)

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.

人机交互智能体机器人

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