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Indoor Multi-Vehicle Flight Testbed for Fault Detection, Isolation, and Recovery

Valenti, Mario, Bethke, Brett, Fiore, Gaston, How, Jonathan, Feron, Eric·2006·AIAA Guidance, Navigation, and Control Conference and Exhibit

Abstract

This paper presents flight tests of a unique indoor, multi-vehicle testbed that was developed to study long duration UAV missions in a controlled environment. This testbed uses real hardware to examine research questions related to single and multi-vehicle health management, such as vehicle failures, refueling, and maintenance. The primary goal of the project is to embed health management into the full UAV planning system, thereby leading to improved overall mission performance, even when using simple aircraft that are prone to failures. The testbed has both aerial and ground vehicles that operate autonomously in a large test region and can be used to execute many different mission scenarios. The success of this testbed is largely related to our choice of vehicles, sensors, and the system’s command and control architecture, which has resulted in a testbed that is very simple to operate. This paper discusses this testbed infrastructure and presents flight test results from some of our most recent single- and multi-vehicle experiments. I.

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Metadata

Authors
Valenti, M., Bethke, B., Fiore, G., How, J., & Feron, E.
Venue
AIAA Guidance, Navigation, and Control Conference and Exhibit
Published
2006-06-15
OpenAlex
W2333318233
Cited by
167
References
0
FWCI
24.15
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Indoor Multi-Vehicle Flight Testbed for Fault Detection, Isolation, and Recovery. https://app.cochat.ai/papers/10.2514/6.2006-6200
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Valenti, M., Bethke, B., Fiore, G., How, J., & Feron, E. (2006). Indoor Multi-Vehicle Flight Testbed for Fault Detection, Isolation, and Recovery. AIAA Guidance, Navigation, and Control Conference and Exhibit. https://doi.org/10.2514/6.2006-6200

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.