发表机构
Autonomous Robotics Systems Limited; University of Hyderabad; Ideabytes Software India Private Limited; Georgia Institute of Technology; Akkodis AS&D GmbH; Universiti Malaya（自主机器人系统有限公司; 海得拉巴大学; Ideabytes软件印度私人有限公司; 佐治亚理工学院; Akkodis AS&D有限公司; 马来亚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种面向自主无人机SysML驱动设计的MBSE框架，以SysML为设计主干整合开发流程，将逻辑架构映射至ROS 2，通过典型任务场景示例，实现需求分配等功能，提升早期设计的可追溯性与一致性。
AI 中文摘要
自主无人机（UAV）是复杂的信息物理系统，需在安全性、时序性和可靠性约束下，整合飞行控制、导航、感知、通信、电源管理及任务级决策。然而，许多自主无人机开发流程仍依赖以文档为中心的需求、分离的架构描述和软件实现工件，易在早期设计阶段引发歧义、接口不一致和弱可追溯性。本文提出一种用于自主无人机SysML驱动开发的基于模型的系统工程（MBSE）设计框架，以系统建模语言（SysML）作为正式设计主干，将无人机开发划分为利益相关者需求、功能分解、逻辑架构及物理/软件分配四个关联层级；通过SysML需求图、活动图、块定义图、内部块图、状态机图和参数化图，捕获无人机系统的功能、结构、行为、接口和性能方面。随后，该框架将逻辑架构系统映射至机器人操作系统2（ROS 2）软件架构，将SysML块关联至ROS 2节点，流端口与连接器关联至话题，请求-响应交互关联至服务，面向目标的行为关联至动作。该框架通过自主起飞、航点导航、悬停稳定、避障、返航及应急处理等典型自主无人机任务场景在设计层面进行示例说明，生成的模型支持需求分配、接口定义、子系统职责分配及验证规划，可在仿真或物理部署前使用。
英文摘要
Autonomous Unmanned Aerial Vehicles (UAVs) are complex cyber-physical systems that require the coordinated integration of flight control, navigation, perception, communication, power management, and mission-level decision-making under safety, timing, and reliability constraints. However, many autonomous UAV development workflows still rely on document-centric requirements, separated architectural descriptions, and software implementation artifacts, which can lead to ambiguity, interface inconsistencies, and weak traceability during early design. This paper presents a Model-Based Systems Engineering (MBSE) design framework for the SysML-driven development of autonomous UAVs. The proposed framework uses the Systems Modeling Language (SysML) as a formal design backbone to structure UAV development across four connected layers: stakeholder requirements, functional decomposition, logical architecture, and physical/software allocation. SysML requirement diagrams, activity diagrams, block definition diagrams, internal block diagrams, state machine diagrams, and parametric diagrams are used to capture the functional, structural, behavioral, interface, and performance aspects of the UAV system. The logical architecture is then systematically mapped to a Robot Operating System 2 (ROS 2) software architecture by relating SysML blocks to ROS 2 nodes, flow ports and connectors to topics, request-response interactions to services, and goal-oriented behaviors to actions. The framework is illustrated at the design level using representative autonomous UAV mission scenarios, including autonomous take-off, waypoint navigation, hover stabilization, obstacle avoidance, return-to-home, and emergency handling. The resulting model supports requirement allocation, interface definition, subsystem responsibility assignment, and verification planning before simulation or physical deployment.
CommentsAccepted for presentation at the 2026 International Conference on Autonomous Aerial Vehicles (ICAAV-2026), 20-21 Aug 2026, Bengaluru, India
