SCARS:缝合自主系统和机器人系统中因非功能性要求之间的冲突而造成的伤口

Mandira Roy, Raunak Bag, Novarun Deb, Agostino Cortesi, Rituparna Chaki, Nabendu Chaki
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引用次数: 0

摘要

在自主机器人系统中,功能需求(FRs)和非功能需求(NFRs)是从多个利益相关者那里收集来的。不同利益相关者的需求与机器人系统的不同组件以及系统的运行环境相关联。将不同来源(多个利益相关者)的需求汇总在一起,往往会产生不一致或相互冲突的需求集。机器人系统 NFR 之间的冲突在很大程度上取决于实际执行环境的特征。在早期规划阶段分析需求之间的不一致和冲突对于系统地设计机器人系统至关重要。在这项工作中,我们设计了一个名为 SCARS 的框架,并对其进行了实验评估,该框架提供:(a) 一种特定领域语言,通过考虑系统必须在其中运行的不同环境背景,扩展了 ROS2 特定领域语言 (DSL) 概念;(b) 支持分析它们对 NFR 的影响;(c) 计算在不同系统配置下可实现的最佳 NFR 满足程度。SCARS 的有效性已在 iRobot®$$ {}^{circledR } 上得到验证。$$ Create®$$ {}^{circledR }$$3 机器人上使用 Gazebo 仿真验证了 SCARS 的有效性。
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SCARS: Suturing wounds due to conflicts between non-functional requirements in autonomous and robotic systems
In autonomous and robotic systems, the functional requirements (FRs) and non-functional requirements (NFRs) are gathered from multiple stakeholders. The different stakeholder requirements are associated with different components of the robotic system and with the contexts in which the system may operate. This aggregation of requirements from different sources (multiple stakeholders) often results in inconsistent or conflicting sets of requirements. Conflicts among NFRs for robotic systems heavily depend on features of actual execution contexts. It is essential to analyze the inconsistencies and conflicts among the requirements in the early planning phase to design the robotic systems in a systematic manner. In this work, we design and experimentally evaluate a framework, called SCARS, providing: (a) a domain-specific language extending the ROS2 Domain Specific Language (DSL) concepts by considering the different environmental contexts in which the system has to operate, (b) support to analyze their impact on NFRs, and (c) the computation of the optimal degree of NFR satisfaction that can be achieved within different system configurations. The effectiveness of SCARS has been validated on the iRobot ® $$ {}^{\circledR } $$ Create ® $$ {}^{\circledR } $$ 3 robot using Gazebo simulation.
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