Abstract
We present an application of HUGIN to solve problems related to diagnosis and control of autonomous vehicles. The application is based on a distributed architecture supporting diagnosis and control of autonomous units. The purpose of the architecture is to assist the operator or piloting system in managing fault detection, risk assessment, and recovery plans under uncertainty. To handle uncertainty, we focus on the use of probabilistic graphical models (PGMs) as implemented in the HUGIN tool.
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Madsen, A.L., Kjærulff, U.B. (2007). Applications of HUGIN to Diagnosis and Control of Autonomous Vehicles. In: Lucas, P., Gámez, J.A., Salmerón, A. (eds) Advances in Probabilistic Graphical Models. Studies in Fuzziness and Soft Computing, vol 213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68996-6_15
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DOI: https://doi.org/10.1007/978-3-540-68996-6_15
Publisher Name: Springer, Berlin, Heidelberg
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