LEO-RobotAgent：面向語言驅動實體操作的通用途機器人代理

LEO-RobotAgent: A General-purpose Robotic Agent for Language-driven Embodied Operator

December 11, 2025

作者: Lihuang Chen, Xiangyu Luo, Jun Meng

cs.AI

摘要

我們提出LEO-RobotAgent——一個面向機器人的通用語言驅動智能體框架。該框架能讓大語言模型操作不同類型的機器人，在多樣化場景中完成不可預測的複雜任務，具有強泛化性、魯棒性和高效性特點。圍繞其構建的應用級系統可全面增強雙向人機意圖理解，降低人機交互門檻。在機器人任務規劃方面，現有研究大多聚焦大模型在單任務場景和單一機器人類型中的應用，這些算法往往結構複雜且缺乏通用性。為此，我們設計的LEO-RobotAgent框架盡可能採用簡潔結構，使大模型能在這一清晰框架內獨立進行思考、規劃與行動。我們提供模塊化且易註冊的工具集，允許大模型靈活調用各類工具以滿足多樣化需求，同時框架內置人機協作機制，使算法能像夥伴般與人類協同工作。實驗驗證表明，該框架可輕鬆適配無人機、機械臂和輪式機器人等主流機器人平台，並高效執行多種精心設計的不同複雜度任務。代碼已開源於：https://github.com/LegendLeoChen/LEO-RobotAgent。

English

We propose LEO-RobotAgent, a general-purpose language-driven intelligent agent framework for robots. Under this framework, LLMs can operate different types of robots to complete unpredictable complex tasks across various scenarios. This framework features strong generalization, robustness, and efficiency. The application-level system built around it can fully enhance bidirectional human-robot intent understanding and lower the threshold for human-robot interaction. Regarding robot task planning, the vast majority of existing studies focus on the application of large models in single-task scenarios and for single robot types. These algorithms often have complex structures and lack generalizability. Thus, the proposed LEO-RobotAgent framework is designed with a streamlined structure as much as possible, enabling large models to independently think, plan, and act within this clear framework. We provide a modular and easily registrable toolset, allowing large models to flexibly call various tools to meet different requirements. Meanwhile, the framework incorporates a human-robot interaction mechanism, enabling the algorithm to collaborate with humans like a partner. Experiments have verified that this framework can be easily adapted to mainstream robot platforms including unmanned aerial vehicles (UAVs), robotic arms, and wheeled robot, and efficiently execute a variety of carefully designed tasks with different complexity levels. Our code is available at https://github.com/LegendLeoChen/LEO-RobotAgent.