2008 IEEE Latin American Robotic Symposium 2008
DOI: 10.1109/lars.2008.19
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Execution Monitoring Applied to Data Estimation Processes

Abstract: This paper presents how execution monitoring can be applied to detect sensor measurements faults and shows how to use this information to improve data estimation processes. Experimental results based on ultrasonic sensors measurement data are presented and the estimation process improvement could be verified.

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Cited by 5 publications
(5 citation statements)
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“…Freire et al also considered the use of fault detection methods applied to data estimation [16]. An adaptive threshold is used to detect and eliminate faulty measurements before submit the data to fusion processes based on the Information Filter.…”
Section: B Environmental Information Extraction and Mappingmentioning
confidence: 99%
See 1 more Smart Citation
“…Freire et al also considered the use of fault detection methods applied to data estimation [16]. An adaptive threshold is used to detect and eliminate faulty measurements before submit the data to fusion processes based on the Information Filter.…”
Section: B Environmental Information Extraction and Mappingmentioning
confidence: 99%
“…Target Detection and Tracking Kalman Filter [9], [10] Monte Carlo Filter [11], [12] Environmental Information Extraction and Mapping Information Filter [13] Decentralized Information Filter [16], [17] Information Filter / α-β Filter [14] Extended Kalman Filter [18] Other Sensing Tasks Descriptor Kalman Filter [19], [21] Extended Kalman Filter [20] Pose Tracking Extended Kalman Filter [22][23][24][25][26][27], [30] Unscented Kalman Filter [28], [29] Information Filter / α-β Filter [32] Decentralized Information Filter [33] Descriptor Kalman Filter [34], [35] Global Localization…”
Section: Application Tool Referencesmentioning
confidence: 99%
“…comparison is performed by the "Decision When a fault is detected, the "Decision signalizes the "Estimation" block that observation vector is not reliable. In this cas phase of the α-β Filter is not executed, an obtained in the output of the prediction phase the output vector of parameters [5] [16].…”
Section: The Fault-tolerant Estimation Processmentioning
confidence: 99%
“…Para um bom funcionamento de qualquer sistema automatizado, seja estacionário ou dinâmico, na indústria química ou em sistemas robóticos, é imprescindível o emprego de um projeto de sistema de controle com auxílio de um modelo adequado do processo, e alimentado com medições confiáveis das variáveis de estado de interesse (FREIRE et al, 2008).…”
Section: Introductionunclassified