在模拟中测试一个不确定的机器人-重复运行多少次?

Clément Robert, Jérémie Guiochet, H. Waeselynck
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引用次数: 2

摘要

测试自主机器人需要在现场进行测试,这可能是昂贵的,对系统及其环境有风险,甚至不可能设置。为了应对这些限制,一种扩展的方法是使用模拟器在虚拟环境中执行测试。由于机器人控制和仿真执行的不确定性,测试可能会在完全相同的输入(相同的世界和任务)下失败或通过。因此,一个重要的问题是:激活一个故障需要运行多少次?在本文中,我们特别关注功能测试背景下重复运行的效率和世界多样性。我们用一个工业案例研究来解决这个研究问题——一个由Naïo技术公司开发的农业除草机器人。我们得出结论,在本案例研究中,测试输入分集比重复运行更有效,以激活故障。更重要的是,我们提出了一种实验方法来评估非确定性的影响,这可能会在其他案例研究中重复使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Testing a non-deterministic robot in simulation - How many repeated runs ?
Testing autonomous robots requires test campaigns in the field that could be expensive, risky for the system and its environment, or even impossible to set up. To cope with these limits, an expanding approach is to perform tests in virtual environments using simulators. Due to the non-determinism of the robot control and simulation execution, a test might fail or pass with exactly the same inputs (same world and mission). An important question is thus: how many runs are required to activate a fault? We particularly focus in this paper on the efficiency of repeated runs and world diversity in the context of functional testing. We address this research question with an industrial case study - an agricultural weeding robot developed by Naïo Technologies. We conclude that, in this case study, test input diversity is more efficient than repeated runs in order to activate faults. More importantly, we propose an experimental approach to assess the impact of the non-determinism, which may be reused in other case studies.
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