The North Carolina Agriculture and Technical State University (NC A&T) in collaboration with Georgia Tech Research Institute (GTRI) has developed methodologies for creating simulation-based technology tools that are capable of inferring the perceptions and behavioral states of autonomous systems. These methodologies have the potential to provide the Test and Evaluation (T&E) community at the Department of Defense (DoD) with a greater insight into the internal processes of these systems. The methodologies use only external observations and do not require complete knowledge of the internal processing of and/or any modifications to the system under test. This paper presents an example of one such simulation-based technology tool, named as the Data-Driven Intelligent Prediction Tool (DIPT). DIPT was developed for testing a multi-platform Unmanned Aerial Vehicle (UAV) system capable of conducting collaborative search missions. DIPT's Graphical User Interface (GUI) enables the testers to view the aircraft's current operating state, predicts its current target-detection status, and provides reasoning for exhibiting a particular behavior along with an explanation of assigning a particular task to it.
翻译:北卡罗来纳州农业和技术大学(北卡罗来纳州农业和技术大学)与格鲁吉亚技术研究所(GTRI)合作,开发了能够推断自主系统感知和行为状态的模拟技术工具的方法,这些方法有可能为国防部测试和评价界提供对这些系统内部过程的更深入了解,这些方法仅使用外部观测,不需要完全了解测试系统的内部处理和/或任何修改,本文举例说明了这种模拟技术工具,称为数据驱动智能预测工具(DIPT),开发了DIPT,用于测试能够执行协作搜索任务的多平台无人驾驶飞行器系统。DIPT的图形用户界面(GUI)使测试者能够查看飞机目前的运行状态,预测其目前的目标探测状态,并为展示特定行为提供推理,同时解释指派给它的特定任务。