基于场景的无人机任务现场测试
Scenario-Based Field Testing of Drone Missions
AI总结：
本文针对无人机现场测试缺乏结构化指导的问题，提出了现场测试场景管理方法，利用基于场景的需求工程和行为驱动开发定义可重用测试场景，评估表明该方法能有效促进无人机现场测试与数据分析。
摘要：
在航空航天领域测试和验证信息物理系统（CPSs），例如无人机救援任务的现场测试，由于天气条件等易变的任务环境而面临挑战。虽然测试过程和方法论已很成熟，但针对现场测试的结构化指导和执行支持仍然薄弱。本文确定了无人机任务现场测试的需求，并引入了用于自适应现场测试指导的现场测试场景管理方法。FiTS旨在为现场测试人员提供充分的指导，作为高效数据收集的基础，以促进现场测试和CPSs的质量保证与迭代改进。FiTS将利用基于场景的需求工程和行为驱动开发中的概念来定义结构化且可重用的测试场景，并为特定角色的指导分配专门的任务和职责。我们通过以下方式评估FiTS：(i) 将其应用于搜救无人机应用的三个用例以证明其可行性，以及 (ii) 采访经验丰富的无人机开发者以评估其有用性并收集进一步的需求。研究结果表明，FiTS在促进无人机现场测试和数据分析方面是可行且有用的。
英文摘要：
Testing and validating Cyber-Physical Systems (CPSs) in the aerospace domain, such as field testing of drone rescue missions, poses challenges due to volatile mission environments, such as weather conditions. While testing processes and methodologies are well established, structured guidance and execution support for field tests are still weak. This paper identifies requirements for field testing of drone missions, and introduces the Field Testing Scenario Management (FiTS) approach for adaptive field testing guidance. FiTS aims to provide sufficient guidance for field testers as a foundation for efficient data collection to facilitate quality assurance and iterative improvement of field tests and CPSs. FiTS shall leverage concepts from scenario-based requirements engineering and Behavior-Driven Development to define structured and reusable test scenarios, with dedicated tasks and responsibilities for role-specific guidance. We evaluate FiTS by (i) applying it to three use cases for a search-and-rescue drone application to demonstrate feasibility and (ii) interviews with experienced drone developers to assess its usefulness and collect further requirements. The study results indicate FiTS to be feasible and useful to facilitate drone field testing and data analysis
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
