Particle Filter for Fault Diagnosis and Ropbust Navigation of Underwater Robot
Conference object, Journal article, Peer reviewed
Date
2014Metadata
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- Institutt for marin teknikk [2472]
- Institutt for teknisk kybernetikk [2290]
- Publikasjoner fra CRIStin - NTNU [22428]
Abstract
A particle filter (PF)-based robust navigation with
fault diagnosis (FD) is designed for an underwater robot, where
10 failure modes of sensors and thrusters are considered. The
nominal underwater robot and its anomaly are described by a
switching-mode hidden Markov model. By extensively running
a PF on the model, the FD and robust navigation are achieved.
Closed-loop full-scale experimental results show that the proposed
method is robust, can diagnose faults effectively, and can
provide good state estimation even in cases where multiple faults
occur. Comparing with other methods, the proposed method can
diagnose all faults within a single structure, it can diagnose
simultaneous faults, and it is easily implemented.
Description
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