UAVAT Framework: UAV Auto Test Framework for Experimental Validation of Multirotor sUAS Using a Motion Capture System

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The development of Unmanned Aerial Systems (UASs) continuously improves and advances the technology, which is a key enabler for many new applications, such as autonomous Beyond Visual Line of Sight (BVLOS) operations. However, ensuring a sufficient level of safety and performance of an UAS can be a challenging task, since it requires systematic experimental validation in order verify and document the reliability, robustness, and fault tolerance of the UAS and its critical components. In this paper we propose the UAV Auto Test Framework (UAVAT Framework), a framework for easy, systematic, and efficient experimental validation of the reliability, fault tolerance, and robustness of a multirotor small Unmanned Aerial Systems (sUAS) and its software and hardware components. We describe the hardware and software used for the UAVAT Framework setup, which consists of a Motion Capture (MoCap) system, a multirotor sUAS, and a tethered power system. In addition, we introduce the concept of test modules, a 'plug-and-play' software component with a set of recommended guidelines for defining testing configurations and enabling easy reuse and distribution of software components for sUAS testing. The capabilities of the UAVAT Framework are demonstrated by presenting the results from two developed test modules targeting endurance testing of a multirotor sUAS and Fault Detection (FD) for abnormal behaviour detection.

Original languageEnglish
Title of host publicationProceedings of the 2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021
Publication date19. Jul 2021
Article number9476699
ISBN (Print)978-1-6654-4704-1
ISBN (Electronic)978-1-6654-1535-4
Publication statusPublished - 19. Jul 2021
Event2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021 - Athens, Greece
Duration: 15. Jun 202118. Jun 2021


Conference2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

Bibliographical note

Funding Information:
This work is part of the HealthDrone project funded by the Innovation Fund Denmark [33]. The authors would like to thank UAS Denmark [34], the Danish National UAS Test Center, at Hans Christian Andersen Airport for providing testing facilities for development and sUAS test flights, especially for the use of the MoCap system funded by the UAS-ability project [35].

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