标题： 机器人系统的自动化行为驱动验收测试 显示英文标题

标题： Automated Behaviour-Driven Acceptance Testing of Robotic Systems

摘要： 机器人应用的规范和验证需要弥合需求制定与系统测试之间的差距。 这通常涉及手动且容易出错的任务，随着需求、设计和实现的发展，这些任务变得更加复杂。 为系统性地解决这一挑战，我们提出扩展行为驱动开发（BDD）以定义和验证机器人系统的接受标准。 在此背景下，我们使用领域特定建模，并将可组合的BDD模型表示为知识图谱，以便进行稳健的查询和操作，促进可执行测试模型的生成。 一种领域特定语言有助于高效地指定机器人接受标准。 我们探索通过集成BDD框架、Isaac Sim和模型转换的软件架构，实现接受测试的自动生成功能和执行，重点针对抓取和放置应用的接受标准。 我们使用现有的抓取和放置实现测试了该架构，并评估了执行结果，这展示了当针对代理和环境的不同变化进行测试时，该应用的行为和失败方式有何不同。 这项研究推进了机器人系统的严格和自动化评估，有助于提高其可靠性和可信度。 显示英文摘要

摘要： The specification and validation of robotics applications require bridging the gap between formulating requirements and systematic testing. This often involves manual and error-prone tasks that become more complex as requirements, design, and implementation evolve. To address this challenge systematically, we propose extending behaviour-driven development (BDD) to define and verify acceptance criteria for robotic systems. In this context, we use domain-specific modelling and represent composable BDD models as knowledge graphs for robust querying and manipulation, facilitating the generation of executable testing models. A domain-specific language helps to efficiently specify robotic acceptance criteria. We explore the potential for automated generation and execution of acceptance tests through a software architecture that integrates a BDD framework, Isaac Sim, and model transformations, focusing on acceptance criteria for pick-and-place applications. We tested this architecture with an existing pick-and-place implementation and evaluated the execution results, which shows how this application behaves and fails differently when tested against variations of the agent and environment. This research advances the rigorous and automated evaluation of robotic systems, contributing to their reliability and trustworthiness.