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ICRA
2010
IEEE

Detecting anomalies in unmanned vehicles using the Mahalanobis distance

13 years 10 months ago
Detecting anomalies in unmanned vehicles using the Mahalanobis distance
The use of unmanned autonomous vehicles is becoming more and more significant in recent years. The fact that the vehicles are unmanned (whether autonomous or not), can lead to greater difficulties in identifying failure and anomalous states, since the operator cannot rely on its own body perceptions to identify failures. Moreover, as the autonomy of unmanned vehicles increases, it becomes more difficult for operators to monitor them closely, and this further exacerbates the difficulty of identifying anomalous states, in a timely manner. Model-based diagnosis and fault-detection systems have been proposed to recognize failures. However, these rely on the capabilities of the underlying model, cessarily abstracts away from the physical reality of the robot. In this paper we propose a novel, model-free, approach for detecting anomalies in unmanned autonomous vehicles, based on their sensor readings (internal and external). Experiments conducted on Unmanned Aerial Vehicles (UAVs) and Un...
Raz Lin, Eliahu Khalastchi, Gal A. Kaminka
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where ICRA
Authors Raz Lin, Eliahu Khalastchi, Gal A. Kaminka
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